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2024
Realistic Counterfactual Explanations with Learned Relations
This paper proposes a DAG-GNN based VAE to reflect the inter-feature relationships in the produced counterfactuals.
Oct 2, 2024 12:30 PM — 1:10 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Can Language Models Solve Graph Problems in Natural Language?
This presentation discusses the NLGraph benchmark, which was created to evaluate LLMs on graph problems.
Sep 26, 2024 12:00 PM — 1:00 PM
Online (Zoom)
Saman Khamesian
PDF
Slides
Reinforcement Learning for Solving the Vehicle Routing Problem
A reinforcement learning approach to solve the vehicle routing problem.
Sep 18, 2024 12:30 PM — 1:00 PM
Online (Zoom)
Abdullah Mamun
PDF
slides
Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI
This study aims to quantify the influence of various meal-related factors on predicting postprandial blood glucose levels (BGLs) at different time intervals (15 min, 60 min, and 120 min) after meals by using deep neural network (DNN) models.
Sep 18, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Ebrahim Farahmand
PDF
slides
LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications
This paper proposes a series of adaptations and enhancements around BERT to best work with IMU data in mobile sensing applications.
Sep 11, 2024 12:00 PM — 12:40 PM
Online (Zoom)
Shovito Barua Soumma
PDF
Slides
ECG classification using Deep CNN and Gramian Angular Field
This paper study provides a novel contribution to the field of signal processing and DL for ECG signal analysis by introducing a new feature representation method for ECG signals.
Sep 11, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Sayyed Mostafa Mostafavi
PDF
slides
DualNet: Continual Learning, Fast and Slow
DualNet is a state-of-the-art neural net architecture that uses the idea of self-supervised learning to learn general features of image data to prevent catastrophic forgetting.
Sep 4, 2024 12:00 PM — 1:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
slides
Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota—Data from the MEDGI-Carb Randomized Controlled Trial
The authors aimed to fit a simple mathematical model on dynamic postprandial glucose data from repeated MMTTs among participants with elevated T2DM risk to identify response clusters and investigate their association with T2DM risk factors and gut microbiota.
Sep 4, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Pegah Khorasani
PDF
slides
LLM-Guided Counterfactual Data Generation for Fairer AI
This paper introduces a technique to produce synthetic counterfactual images to train a model free of bias.
Aug 28, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections
This presentation discusses label-free tunning of zero-shot classifiers using language and unlabeled image collections.
Aug 21, 2024 12:00 PM — 1:00 PM
Health Futures Center, ASU
Saman Khamesian
PDF
Slides
Random Erasing Data Augmentation
In this paper, the authors introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN). In training, Random Erasing randomly selects a rectangle region in an image and erases its pixels with random values.
Aug 7, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
PDF
Slides
Self-Supervised Representation Learning from Electroencephalography Signals
In this work, the authors present self-supervision strategies that can be used to learn informative representations from multivariate time series.
Jul 31, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Nooshin Taheri Chatrudi
PDF
Slides
Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data
This paper proposes Health-LLM, a framework in the healthcare domain that aims to bridge the gap between pre-trained knowledge in current LLMs and consumer health problems.
Jul 17, 2024 12:00 PM — 12:40 PM
Online (Zoom)
Shovito Barua Soumma
PDF
Slides
Dynamic Associations Between Glucose and Ecological Momentary Cognition In Type 1 Diabetes
This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments.
Jul 10, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Pegah Khorasani
PDF
EmojiCrypt: Prompt Encryption for Secure Communication with Large Language Models
This presentation discusses a new way to encrypt data with the help of LLMs.
Jun 19, 2024 12:00 PM — 1:00 PM
Online (Zoom)
Saman Khamesian
PDF
Slides
Scaling MLPs: A Tale of Inductive Bias
In this work, the authors revisit the most fundamental building block in deep learning, the multi-layer perceptron (MLP), and study the limits of its performance on vision tasks.
Jun 12, 2024 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
PDF
Slides
Counterfactual Explainable Recommendation
CountER tells us under what conditions a chosen item would not be recommended to a person anymore.
May 28, 2024 3:00 PM — 3:40 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Contrastive Representation Learning for Electroencephalogram Classification
This paper presents a framework for learning representations from EEG signals via contrastive learning.
May 21, 2024 3:00 PM — 3:45 PM
Online (Zoom)
Nooshin Taheri Chatrudi
PDF
Slides
A robotic object hitting task to quantify sensorimotor impairments in participants with stroke
This paper presents a robotic object hitting task to quantify sensorimotor impairments in participants with stroke
Apr 30, 2024 3:00 PM — 3:45 PM
Health Futures Center, ASU
Sayyed Mostafa Mostafavi
PDF
Slides
Introducing Meta Llama 3
This presentation introduced the latest AI assistance from Meta company.
Apr 23, 2024 3:00 PM — 4:00 PM
Health Futures Center, ASU
Saman Khamesian
Slides
Video
Self-Supervised Learning of Pretext-Invariant Representations
This presentation presents self-supervised method that learns invariant representations rather than covariant ones.
Apr 16, 2024 3:00 PM — 3:40 PM
Health Futures Center, ASU
Shovito Barua Soumma
PDF
Slides
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks
This paper proposes a framework for better understanding what is happening behind the training of over-parameterized neural nets, for which the objective function is not convex, not even locally
Apr 9, 2024 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Adversarial Counterfactual Visual Explanations
Adversarial Counterfactual Explanations propose to develop a filter that robustifies a model against adversarial attacks and helps to transform them into counterfactual explanations.
Apr 2, 2024 3:00 PM — 3:40 PM
Health Futures Center, ASU
Asiful Arefeen
PDF
Slides
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
This presentation discusses solving complex AI tasks with a new model named HuggingGPT.
Mar 19, 2024 3:00 PM — 4:00 PM
Health Futures Center, ASU
Saman Khamesian
PDF
Slides
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
This paper proposes a contrastive learning based approach to solve the problem of causal representation learning, under the assumption of linear-gaussian representation, and a non-linear mixing function
Mar 12, 2024 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
U-Net: Convolutional Networks for Biomedical Image Segmentation
In this paper, the authors present a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more efficiently.
Mar 5, 2024 3:00 PM — 3:45 PM
Abdullah Mamun
PDF
Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks
This paper proposes a novel approach for learning such representations from multi-channel EEG time-series, and demonstrate its advantages in the context of mental load classification task.
Feb 27, 2024 3:00 PM — 4:00 PM
Health Futures Center, ASU
Nooshin Taheri Chatrudi
PDF
Slides
Real-Time Patient Adaptivity for Freezing of Gait Classification Through Semi-Supervised Neural Networks
This presentation presents semi-supervised neural network for freezing of gait classification.
Feb 20, 2024 3:00 PM — 3:40 PM
Health Futures Center, ASU
Shovito Barua Soumma
PDF
Slides
HbA1c and brain health across the entire glycaemic spectrum
This presentation aims understanding the relationship between HbA1c and brain health across the entire glycaemic spectrum.
Feb 13, 2024 3:00 PM — 3:40 PM
Health Futures Center, ASU
Pegah Khorasani
PDF
Slides
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
CounterNet proposes an end-to-end training of the predictor and explanation generator to solve some key issues associated with post-hoc/model agnostic explainers.
Feb 6, 2024 3:00 PM — 3:40 PM
Health Futures Center, ASU
Asiful Arefeen
PDF
Slides
A hybrid method for imputation of missing values using optimized fuzzy c-means with support vector regression and a genetic algorithm
This presentation discusses missing data imputation through fuzzy c-means clustering.
Jan 23, 2024 3:00 PM — 4:00 PM
Health Futures Center, ASU
Saman Khamesian
PDF
Slides
Contrastive learning based self-supervised time-series analysis
This paper proposes a new self-supervised learning based approach for industrial time-series analysis which uses data-augmentation techniques
Jan 16, 2024 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Binary imbalanced data classification based on diversity oversampling by generative models
This paper proposes two binary imbalanced data classification methods with extreme learning machine autoencoders and generative models. Their methods outperform SMOTE and similar data balancing tools on most benchmark datasets.
Jan 9, 2024 3:45 PM — 5:00 PM
Health Futures Center, ASU
Abdullah Mamun
PDF
Slides
Fourier Transform, Short-Time Fourier Transform, and Wavelet Transform
This presentation describes and explains Fourier Transform, Short-Time Fourier Transform, and Wavelet Transform.
Jan 2, 2024 3:00 PM — 4:00 PM
Online (Zoom)
Nooshin Taheri Chatrudi
Slides
2023
Data Augmentation of Wearable Sensor Data for Parkinson’s Disease Monitoring using Convolutional Neural Networks
In this paper, various data augmentation methods for wearable sensor data are proposed. The proposed methods and CNNs are applied to the classification of the motor state of Parkinson’s Disease patients.
Dec 20, 2023 1:30 PM — 2:00 PM
Online (Zoom)
Shovito Barua Soumma
PDF
Slides
Counterfactual diagnosis
inability to recognize counterrfactual diagnosis from associative diagnosis can lead to disastrous outcomes.
Nov 22, 2023 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Generating Interpretable Counterfactual Explanations By Implicit Minimization of Epistemic and Aleatoric Uncertainties
This article demonstrate a new approach to implement counterfactual explanations (CE) without necessarily employing any generative model. As generative models come with several drawbacks in CE generation, the approach in this paper is based on Epistemic and Aleatoric Uncertainty reduction.
Nov 15, 2023 1:50 PM — 2:25 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
A Survey of Methods for Time Series Change Point Detection
This paper discusses the available methods to detect change points in time-series data.
Nov 8, 2023 1:30 PM — 2:00 PM
Health Futures Center, ASU
Abdullah Mamun
PDF
Slides
SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
This paper presents SimCLR, a simple framework for contrastive learning of visual representations.
Nov 1, 2023 1:30 PM — 2:00 PM
Health Futures Center, ASU
Shovito Barua Soumma
PDF
Slides
Brief Introduction to Causality and Conuterfactual Reasoning
A brief introduction to causality with the emphasis on the book “The Book of Why”, by Judea Pearl.
Oct 25, 2023 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Counterfactual Explanations for Multivariate Time Series
This article focuses on defining what counterfactuals mean in the context of timeseries data and proposed an algorithm that generates plausible and minimally distant counterfactual explanations.
Oct 5, 2023 1:00 PM — 1:40 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Open-World Semi-Supervised Learning
A fundamental limitation of applying semi-supervised learning in real-world settings is the assumption that unlabeled test data contains only classes previously encountered in the labeled training data. However, this assumption rarely holds for data in-the-wild, where instances belonging to novel classes may appear at testing time. Here, we introduce a novel open-world semi-supervised learning setting that formalizes the notion that novel classes may appear in the unlabeled test data.
Sep 27, 2023 1:30 PM — 2:00 PM
Health Futures Center, ASU
Abdullah Mamun
PDF
Slides
Estimating Average Treatment Effects via Orthogonal Regularization
Conducting a causal inference study with observational data is a difficult endeavor that necessitates a slew of assumptions. One of the most common assumptions is “ignorability,” which argues that given a patient (X), the pair of outcomes (Y0, Y1) is independent of the actual treatment received (T). This assumption is used in this paper to develop an AI model for calculating the Average Treatment Effect (ATE).
Sep 6, 2023 1:30 PM — 3:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
An introduction to counterfactual explanations using the novel approach developed by Microsoft Corporation, India.
Aug 31, 2023 1:30 PM — 2:00 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Towards A Rigorous Science of Interpretable Machine Learning
In this position paper, the authors define interpretability and describe when interpretability is needed (and when it is not). Next, they suggest a taxonomy for rigorous evaluation and expose open questions towards a more rigorous science of interpretable machine learning.
Aug 23, 2023 1:30 PM — 3:00 PM
Health Futures Center, ASU
Abdullah Mamun
PDF
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
Propensity score is the probability of a patient receiving the treatment. Given the propensity score, the covariates are independent from the treatment variable. Therefore, it can be used to turn an observational data into a data collected using a randomized trial. This paper talks about different methods of applying propensity scores to causal studies.
Aug 9, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Forecasting the future clinical events of a patient through contrastive learning
This study implemented SimCLR on EHR data to detect rare dseases. In general, rare diseases are underrepresentative classes in any clinical dataset. Therefore, using SimCLR (contrastive learning) boosts their classification accuracy.
Jul 12, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Neonatal Risk Modeling and Prediction
We propose an automated risk prediction system that can make recommendations to clinicians in real-time with machine learning classifiers that predict the risk of developing neurological impairment.
Jul 5, 2023 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
Neural Ordinary Differential Equations
Neural ODEs describe a flow from the input to the output. They utilize the traditional ODE solvers to reach this goal. By doing so, they introduce a trade-off between accuracy and computational cost.
Jun 28, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
Slides
Self-Supervised Adversarial Distribution Regularization for Medication Recommendation
This paper reduces drug-drug interaction in automated medication recommendation with help of self-supervised adversarial distribution regularization
Jun 21, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Abdullah Mamun
PDF
video
Feature Importance Explanations for Temporal Black-Box Models
TIME is a great tool for explaining the predictions made by a model. It is very similar to Grad-CAM, however, it can work with tabular data as well. Also, TIME can provide global expainability as well.
Jun 14, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Detecting moments of cannabis use with machine learning methods
This study used machine learning methods to identify and detect the moments of cannabis use in participants. The model was trained using a leave-one-subject-out method, and later personalized using transfer learning
Jun 7, 2023 12:30 PM — 12:50 PM
Online (Zoom)
Reza Rahimi Azghan
Entropy-based Logic Explanations of Neural Networks
This research paper aims at building an entropy layer for end-to-end explainable AI framework. Unlike LIME and Grad-CAM, Entropy Net does not rely on any auxuliary tool/model to explain its predictions. Also, Entropy Net focuses on downsizing the concepts required to explain predictions.
May 4, 2023 2:00 PM — 2:40 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Invited talk: Time-Series Wearable Activity Forecasting
This research aimed to develop a lifestyle intervention system with an emphasis on time series forecasting and also to develop a generic multimodal activity forecasting scheme that can be used with either early fusion or late fusion mechanisms.
Apr 14, 2023 11:30 AM — 11:50 AM
La Sala Ballroom, ASU West Campus
Abdullah Mamun
slides
Rep-Net: Efficient On-Device Learning via Feature Reprogramming
REP-Net is a counter to traditional transfer learning for On-board model training with more focus on memory efficiency.
Apr 6, 2023 2:00 PM — 2:30 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Adapting Neural Networks for the Estimation of Treatment Effects
TDragonnet is an end-to-end neural network architecture that uses propensity score to estimate the average treatment effect.
Mar 16, 2023 2:00 PM — 2:45 PM
Online (Zoom)
Reza Rahimi Azghan
PDF
PDF
slides
Time Series Data Augmentation for Deep Learning: A Survey
This paper provides an overview of basic and advanced approaches of time-series data augmentation.
Mar 9, 2023 2:00 PM — 2:00 PM
Online (Zoom)
Abdullah Mamun
PDF
slides
Training Generative Adversarial Networks with Limited Data
Training GANs require large amount of data. If tried with small datasets, the discriminator often times overfit producing meaningless feedback to the generator. One solution to training GANs with smaller dta could be using adaptive data augmentation.
Feb 23, 2023 2:00 PM — 2:40 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Language Models are Few-Shot Learners
This paper proposes GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting.
Feb 15, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Abdullah Mamun
PDF
slides
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response
Including domain knowledge can increase explainability without compromising on model performance. This paper mainly discusses a preprocessing technique to incorporate domain knowledge in a way they become very useful for explaining model’s predictions.
Feb 1, 2023 12:30 PM — 1:00 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Multi-Time Attention Networks for Irregularly Sampled Time Series
This paper proposes a new deep learning framework for irregularly sampled time-series data that is called Multi-Time Attention Networks.
Jan 18, 2023 12:00 PM — 12:30 PM
Online (Zoom)
Chia-Cheng Kuo
PDF
slides
Masked Autoencoders Are Scalable Vision Learners
This paper shows that masked autoencoders (MAE) are scalable self-supervised learners for computer vision.
Jan 11, 2023 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
PDF
2022
Augmented Experiment in Material Engineering Using Machine Learning
Incorporating domain knowledge to neural networks is a creative and case specific approach. This paper modifies the loss function of a fully-connected network with domain knowledge from kinetics which helped the model make precise prediction in its regression task.
Dec 21, 2022 3:00 PM — 3:40 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
An algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a variety of different learning problems, including classification, regression, and reinforcement learning.
Dec 14, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Chia-Cheng Kuo
PDF
slides
Wearable Systems and Machine Learning for Affect Recognition and Interventions
Prelim Exam Practice Presentation of Ramesh Sah.
Dec 7, 2022 11:00 AM — 12:00 PM
Online (Zoom)
Ramesh Kumar Sah
Reinforcement Learning for Solving the Vehicle Routing Problem
A reinforcement learning approach to solve the vehicle routing problem.
Nov 23, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
PDF
slides
Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge
Optimizes change in consumed nutrients while driving users to their desired diet.
Nov 14, 2022 11:00 AM — 12:00 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Adversarial Examples in Embedded Systems
Practice presentation for Master defense of Ramesh Sah.
Nov 4, 2022 11:00 AM — 12:00 PM
Online (Zoom)
Ramesh Kumar Sah
Channel Pruning via Automatic Structure Search
This paper proposes a new channel pruning method based on artificial bee colony algorithm (ABC), dubbed as ABCPruner, which aims to efficiently find optimal pruned structure.
Oct 26, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Chia-Cheng Kuo
Paper
slides
Local Interpretable Model-Agnostic Explanations
LIME is a great tool for explaining the predictions made by a model. LIME can explain any model regardless of their type, it works by building a linear model on vicinity of the sample intended to be explained.
Oct 19, 2022 10:30 AM — 11:00 AM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
This paper addresses the generalization gap on large neural networks with adaptive gradient-based optimizers and proposes a partially adaptive solution to overcome the problem.
Oct 5, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
paper
Data Augmentation Strategies
In this talk, we present and discuss different strategies for data augmentation.
Sep 14, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Chia-Cheng Kuo
Paper
slides
Characterizing Decision Boundary for DNN on High Dimensional Data
Decision boundaries are imposible to be visualized in hogh dimensional feature sets. Instead of visualizing them, we can characterize them and make them useful
Sep 7, 2022 10:00 AM — Sep 7, 2021 10:30 AM
Online (Zoom)
Asiful Arefeen
PDF
Slides
Multimodal Time-Series Activity Forecasting for Adaptive Lifestyle Intervention Design
We focus on devising algorithms that combine data about physical activity and engagement with the app to predict future physical activity performance.
Aug 31, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
PDF
slides
Methods to Deal with Imbalanced Dataset
In this talk, Ramesh explained and highlighted different methods to deal with imbalanced dataset. He shared his experience working with imbalance datasets and partical tips and tricks.
Aug 24, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Ramesh Kumar Sah
PDF
Grad-CAM for Interpreting DNN Model Decisions
Neural networks have a bad reputations as they are treated like black boxes and lack interpretations on the results they make. Grad-CAM can slightly interprete what is driving the model to make a decision.
Jul 22, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Asiful Arefeen
PDF
Slides
ViViT: A Video Vision Transformer
Jul 1, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
paper
Boosting Lying Posture Classification with Transfer Learning
Enhancement of accuracy for wrist-worn sensor based lying posture classification via transfer learning
Jun 10, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Asiful Arefeen
Slides
Stressalyzer: Convolutional Neural Network Framework for Personalized Stress Classification
May 27, 2022 12:00 PM
Online (Zoom)
Ramesh Kumar Sah
PDF
A Review of Approximate Dynamic Programming and Feature-based Aggregation
May 6, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Abdullah Mamun
paper(Powell)
paper(Bertsekas)
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Apr 29, 2022 12:00 PM — 12:30 PM
Online (Zoom)
Iman Mirzadeh
paper
Optimizations in Sparse Coding
Optimization Algorithms to begin with Sparse Coding.
Apr 22, 2022 12:00 PM — 1:00 PM
Zoom
Asiful Arefeen
Slides
Continous Monitoring of Stress on Smartphone using Heart Rate Variability
Continous detection of stress using external heart rate monitor to drive inter beat interval feature on a smartphone.
Apr 15, 2022 10:00 PM — 10:30 PM
Online (Zoom)
Ramesh Kumar Sah
paper
slides
Multiagent Rollout Algorithms and Reinforcement Learning
Apr 8, 2022 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
2021
Variational Autoencoders
Introduction to variational autoencoders.
Nov 29, 2021 3:00 PM — 4:00 PM
Zoom
Asiful Arefeen
Slides
From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba
Oct 11, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
Recent Techniques in Semi-Supervised Learning
Techniques for training GANs using Semi-supervised learning.
Sep 27, 2021 3:00 PM — 4:00 PM
Zoom
Asiful Arefeen
PDF
Slides
Bidirectional Relationship of Stress and Affect with Physical Activity and Healthy Eating
Examine the relationship between stress and physical activity and healthy eating in both direction - negative and positive - using ecological momentary assessment (EMA).
Sep 20, 2021 3:00 PM — 4:00 PM
Zoom
Ramesh Kumar Sah
Slides
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Aug 23, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning
A novel framework called SubNetwork Routing (SNR) to achieve more flexible parameter sharing while maintaining the computational advantage of the classic multi-task neural-network model.
Aug 16, 2021 3:00 PM — 4:00 PM
Zoom
Asiful Arefeen
PDF
Slides
A Survey and Taxonomy of Electronics Toolkits for Interactive and Ubiquitous Device Prototyping
Jul 4, 2021 3:00 PM — 4:00 PM
Zoom
Mahdi Pedram
PDF
Slides
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
Jun 28, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
Which Tasks Should Be Learned Together in Multi-task Learning?
Jun 21, 2021 3:00 PM — 3:30 PM
Asiful Arefeen
PDF
Slides
A review of Binary Neural Networks (BNNs)
Introduction to binary neural networks with details about training and evaluation of these networks.
Jun 14, 2021 3:00 PM — 4:00 PM
Zoom
Ramesh Kumar Sah
Slides
Understanding ML Theory (1): Introduction to Statistical Learning Theory
Introduction to the statistical learning theory, and a prelude to PAC learning
Jun 7, 2021 3:00 PM — 4:00 PM
Zoom
Iman Mirzadeh
Slides
TinyOL: TinyML with Online-Learning on Microcontrollers
Adding Online-Learning ability to TinyML.
May 24, 2021 9:00 AM
Mahdi Pedram
PDF
Anywidth Networks
Review of the “Any-Width Networks” from CVPR 2020 workshops.
May 17, 2021 3:00 PM — 3:30 PM
Zoom
Asiful Arefeen
PDF
Slides
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
May 10, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
Rotational dynamics reduce interference between sensory and memory representations
How does the brain prevent interference of memory and sensory data?
May 3, 2021 3:00 PM — 3:30 PM
Zoom
Iman Mirzadeh
PDF
Slides
Self-Supervised Learning for ECG-Based Emotion Recognition
Emotion classification using self-supervised learning and six signal transformations as pretext tasks.
Apr 26, 2021 3:00 PM — 3:30 PM
Online (Zoom)
Ramesh Kumar Sah
PDF
Slides
A Wearable Electrochemical Sensing System for Non-Invasive Monitoring of Lithium Drug in Bipolar Disorder
Apr 19, 2021 10:00 PM — Apr 12, 2021 10:30 PM
Online (Zoom)
Mahdi Pedram
paper
Modeling Long and Short-Term Temporal Patterns with Deep Neural Networks
Apr 12, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
Paper Review: Attention is All You Need.
Review of the paper “Attention Is All You Need”
Apr 5, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Asiful Arefeen
paper
slides
Transformers in Computer Vision
Review of the recent research on bringing the transformer architecture to the computer vision field.
Mar 29, 2021 10:00 PM — 10:30 PM
Online (Zoom)
Iman Mirzadeh
slides
μEMA: Microinteraction-based Ecological Momentary Assessment (EMA) Using a Smartwatch
Quantifying user burden for EMA studies with frequent and one-question EMA assessment.
Mar 22, 2021 3:00 PM — 3:30 PM
Online (Zoom)
Ramesh Kumar Sah
Slides
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Review of the AI Economist paper by Salesforce Research.
Mar 8, 2021 11:00 PM — 11:30 PM
Online (Zoom)
Abdullah Mamun
paper
slides
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
Mar 1, 2021 11:00 PM — 11:30 PM
Zoom
Asiful Arefeen
paper
OpenAI CLIP & DALL.E
Overview of two visions systems by Open AI
Feb 22, 2021 11:00 PM — 11:30 PM
zoom
Iman Mirzadeh
Earthquake transformer—an attentive deeplearning model for simultaneous earthquake detection and phase picking
Picking phase and detecting earthquakes using encoder-decoder transformer model.
Feb 15, 2021 3:00 PM — 3:30 PM
Ramesh Kumar Sah
Slides
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.
Overview of the GPipe Paper:
https://openreview.net/pdf?id=SklqmESeIH
Feb 1, 2021 11:00 PM — 11:30 PM
Zoom Meeting
Abdullah Mamun
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Jan 11, 2021 3:00 PM
Asiful Arefeen
PDF
Sensitivity and Generalization in Neural Networks: an Empirical Study
Review of ICLR'18 paper by Novak et.al.
Jan 4, 2021 3:00 PM
Iman Mirzadeh
PDF
Slides
2020
U-Net: Convolutional Networks for Biomedical Image Segmentation
Dec 9, 2020 9:00 AM
Asiful Arefeen
PDF
Slides
A Multi-Sensor Approach to Automatically Recognize Breaks and Work Activities of Knowledge Workers in Academia
Oct 14, 2020 12:00 AM — 12:00 AM
Mahdi Pedram
PDF
Paper Review: What is being transferred in transfer learning?
Understanding why transfer learning is successful
Sep 30, 2020 11:00 AM — 11:30 AM
Iman Mirzadeh
PDF
Slides
Wearable sensor-based detection of stress and craving in patients.
Sep 24, 2020 11:05 AM — 11:05 AM
Ramesh Kumar Sah
Slides
Social and competition stress detection with wristband physiological signals
Sep 9, 2020 12:00 PM — 12:00 PM
Asiful Arefeen
PDF
Managing Machine Learning Experiments For Research Projects
Practical tips for researchers for managing ML experiments
Sep 2, 2020 2:00 PM — 2:30 PM
Iman Mirzadeh
Slides
Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial
Aug 19, 2020 11:08 AM — 11:08 AM
Ramesh Kumar Sah
Slides
NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions
Aug 12, 2020 12:00 AM — 12:00 AM
Mahdi Pedram
PDF
Introduction to Gaussian Processes
General high-level introduction to Gaussian Processes for time-series data modelling.
Jul 15, 2020 9:12 AM — 9:12 AM
Ramesh Kumar Sah
Slides
Neural Tangent Kernel
Introduction to neural tangent kernel
Jul 8, 2020 12:00 AM — 12:00 AM
Iman Mirzadeh
PDF
Why Sweat Will Power Your Next Wearable!
Jul 1, 2020 12:00 AM — 12:00 AM
Mahdi Pedram
PDF
Paper Review: Multi-modal Self-Supervised Learning for Human Activity Recognition
Review of self-supervised learning for human activity recognition
Jun 17, 2020 7:36 PM — 12:30 PM
Dana Hall
Ramesh Kumar Sah
PDF
Slides
Paper Review: Lottery Ticket Hypothesis
Review of The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Mar 15, 2020 7:36 PM — 12:30 PM
Dana Hall
Iman Mirzadeh
PDF
Slides
Introduction To Self-Supervised Learning
Re-presentation of Yann LeCun’s AAAI talk and discussion on semi-supervised learning methods.
Feb 24, 2020 12:00 PM — 12:30 PM
Iman Mirzadeh
Slides
Adversarial Reprogramming of Neural Networks
Paper Review:
Elsayed, G.F., Goodfellow, I.J., & Sohl-Dickstein, J. (2019). Adversarial Reprogramming of Neural Networks. ICLR.
Jan 27, 2020 12:00 PM
Ramesh Kumar Sah
PDF
Similarity of Neural Network Representations Revisited
Paper Review: Kornblith,
S., Norouzi, M., Lee, H., & Hinton, G.E. (2019). Similarity of Neural Network Representations Revisited. ICML
Jan 14, 2020 12:00 PM
Iman Mirzadeh
PDF
Slides
2019
Secure and Private AI: Differential Privacy and Federated Learning
An introduction to Differential Privacy and Federated Learning concepts.
Aug 7, 2019 12:00 PM
Dana Hall, Washington State University
Iman Mirzadeh
Slides
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation
Jul 31, 2019 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Introduction on Electrodermal Activity and Human Physiological Response
Jul 18, 2019 12:00 PM
Dana Hall, Washington State University
Marco Antonio Arceo
Human Activity Recognition using Wearable Sensors by Deep Convolutional Neural Networks
Jul 10, 2019 12:00 PM
Dana Hall, Washington State University
Ramesh Kumar Sah
PhD Preliminary Exam Practice Talk #1: Resource Efficient Methods for Health Monitoring Systems.
Jun 26, 2019 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Resource-Efficient Computing in Wearable Systems (Presentation)
Practice presentation for SMARTCOMP conference.
May 29, 2019 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification (Presentaion)
May 8, 2019 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Transfer Learning via Learning to Transfer
Mar 27, 2019 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification
Mar 20, 2019 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Machine Learning Beyond Curve Fitting (Introduction to Causality)
Feb 27, 2019 12:00 PM
Dana Hall, Washington State University
Iman Mirzadeh
Distillation in Machine Learning
Feb 13, 2019 12:00 PM
Dana Hall, Washington State University
Ramesh Kumar Sah
Introduction to Adversarial Machine Learning
Jan 23, 2019 12:00 PM
Dana Hall, Washington State University
Ramesh Kumar Sah
Master Defense Practice III
Jan 16, 2019 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Machine Learning in 2018: an overview
Jan 9, 2019 12:00 PM
Dana Hall, Washington State University
Iman Mirzadeh
2018
Defense Practice II.
Nov 7, 2018 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
Oct 31, 2018 12:00 PM
Dana Hall, Washington State University
Iman Mirzadeh
Defense Practice I.
Oct 24, 2018 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Wearable Sensors for Human Activity Monitoring: A Review
Oct 3, 2018 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
An introduction to semi-supervised learning.
Sep 26, 2018 12:00 PM
Dana Hall, Washington State University
Iman Mirzadeh
Introduction to Long Short Term Memory Networks
Sep 5, 2018 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Defense Practice II
Aug 29, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Defense Practice I
Aug 22, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Defense Practice
Jul 2, 2018 12:00 PM
Dana Hall, Washington State University
Ali Rokni
,
Ramin Fallahzadeh
Fluid Intake Monitoring
Jun 5, 2018 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Cross-Platform Transfer Learning
May 29, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Stream-PAL (Proximity-based Active Learning)
May 22, 2018 12:00 PM
Dana Hall, Washington State University
Marjan Nourollahi
NN search with KD-trees
May 11, 2018 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
L2Knng: Fast Exact K-Nearest Neighbor Graph Construction with L2-Norm Pruning
May 4, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Liquid Intake Monitoring System
Apr 27, 2018 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Deep Convolutional Feature Transfer Across Mobile Activity Recognition Domains, Sensor Modalities and Locations
Apr 20, 2018 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Eating Moment Recognition, A Proximity-Based Active Learning Approach
Apr 13, 2018 12:00 PM
Dana Hall, Washington State University
Marjan Nourollahi
A Closed-loop Deep Learning Architecture for Robust Activity Recognition using Wearable Sensors
Mar 30, 2018 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Personalized recommenders
Mar 16, 2018 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Toward Visual Field Assessment Using Head-Worn Sensing Devices
Mar 2, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Cooking Risk Analysis to Enhance Safety of Elderly People in Smart Kitchen
Feb 16, 2018 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
TransNet: An Adaptable Deep Learner for Human Activity Recognition
Feb 9, 2018 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Label Propagation: An Unsupervised Similarity Based Method for Integrating New Sensors in Activity Recognition Systems
Feb 2, 2018 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Stratified Transfer Learning for Cross-domain Activity Recognition
Jan 19, 2018 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Structural Action Recognition in Body Sensor Networks: Distributed Classification Based on String Matching
Jan 3, 2018 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
2017
A Conformal Sensor for Wireless Sweat Level Monitoring
Dec 6, 2017 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Learn-on-the-Go: Autonomous Cross-Subject Context Learning for Internet-of-Things Applications
Nov 8, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Collegial Activity Learning Between Heterogeneous Sensors
Nov 1, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Transfer Learning via Dimensionality Reduction
Oct 25, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Oct 18, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Performance Prediction for Graph Queries.
Oct 11, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams
Oct 4, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Learning from less for better: semi-supervised activity recognition via shared structure discovery
Sep 27, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Modeling Skewed Class Distributions by Reshaping the Concept Space.
Sep 20, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Robust Computational Framework for Sensor-Based Systems in Healthcare
Sep 6, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Transferring multi-device localization models using latent multi-task learning
Aug 30, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Medical Survey Question Optimization
Aug 23, 2017 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Structured Perceptron (Part II)
Aug 17, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Reliable and reconfigurable framework for physical activity monitoring
Aug 10, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Monitoring and Planning Diet Behavior
Jul 13, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Enabling Effective Programming and Flexible Management of Efficient Body Sensor Network Applications,
Jun 29, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Assignment Problem (Part II)
Jun 22, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Language and Policy Learning from Human-delivered Feedback.
Jun 15, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Transportation Problem
Jun 8, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Structured Perceptron (Part I)
May 25, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
SmartStuff: A Case Study of a Smart Water Bottle
May 18, 2017 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Assignment Problem (Part I)
May 11, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Reinforcement learning for diet planning
May 4, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Graph Coloring and its applications
Apr 27, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Hypothesis Testing
Apr 20, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Synchronous Dynamic View Learning: A Framework for Autonomous Training of Activity Recognition Models using Wearable Sensors
Apr 13, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Towards Reliable Sensor-Based Wearable Systems for Healthcare (Part 2)
Mar 30, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Towards Reliable Sensor-Based Wearable Systems for Healthcare (Part 1)
Mar 23, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Convex Optimization II: Gradient descent (Part 2)
Mar 9, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Adaptive Compressed Sensing at the Fingertip of Internet-of-Things Sensors: An Ultra-Low Power Activity Recognition
Mar 9, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Reinforcement learning: Monte Carlo method
Mar 2, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Network-based relational knowledge transfer
Feb 23, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
A Beverage Intake Tracking System Based on Machine Learning Algorithms, and Ultrasonic and Color Sensors
Feb 23, 2017 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
SVM, TSVM and SVM Tree
Feb 16, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Outlier detection and analysis
Feb 9, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Active Learning on Time Series Data
Feb 9, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Power and Memory Efficient Cascading Binary Classifier for Activity Recognition
Feb 2, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Convex Optimization II: Gradient descent (Part 1)
Feb 2, 2017 12:00 PM
Dana Hall, Washington State University
Ali Rokni
NetSimile: A Scalable Approach to Size-Independent Network Similarity
Jan 26, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Approximating weighted vertex cover using linear programming
Jan 26, 2017 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Randomized 3-approximation MAX-CNF
Jan 19, 2017 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Active Learning Enabled Activity Recognition
Jan 19, 2017 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Semi-supervised learning using gaussian fields and harmonic functions
Jan 12, 2017 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
2016
Q-learning
Dec 7, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
User-guided reinforcement learning of robot assistive tasks for an intelligent environment.
Dec 5, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Minimum Makespan Scheduling
Nov 30, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Sequential Behavior Prediction Based on Hybrid Similarity and Cross-User Activity Transfer
Nov 28, 2016 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Transfer Learning in Decision Trees
Nov 7, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Mixture of Experts
Nov 2, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Autonomous Sensor-Context Learning in Dynamic Human-Centered Internet-of-Things Environments
Oct 31, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Personalized and Context-Based Sensing for Dehydration Monitoring
Oct 24, 2016 12:00 PM
Dana Hall, Washington State University
Mahdi Pedram
Data Collection and Language Understanding of Food Descriptions
Oct 10, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Convex Sets
Sep 28, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Designing and Evaluating Active Learning Methods for Activity Recognition
Sep 26, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Heapsort
Sep 21, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Using Smart Homes to Detect and Analyze Health Events
Sep 19, 2016 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Adaptive Model Fusion for Wearable Sensors Based Human Activity Recognition
Sep 12, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Random Forrest Algorithm
Aug 31, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Recognizing New Activities with Limited Training Data
Aug 29, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
An Energy-Efficient Computational Model for Uncertainty Management in Dynamically Changing Networked Wearables
Aug 1, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Cross-people mobile-phone based activity recognition
Jul 25, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Introduction to Transfer Learning
Jul 11, 2016 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Knapsack Problem
Jun 27, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Discreted Wavelet Transform
Jun 20, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Conditional Random Fields
Jun 6, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Bin Packing Problem: Asymptotic PTAS (AA Ch 9)
May 23, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Zero-Effort Camera-Assisted Calibration Techniques for Wearable Motion Sensors.
May 16, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
A food recognition system for diabetic patients based on an optimized bag-of-features model.
Apr 4, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Using Weka Java API
Mar 28, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Dietcam: Multi-view food recognition using a multi-kernel svm.
Mar 28, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Shortest Super-string Problem 2
Mar 21, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Shortest Super-string Problem
Mar 7, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Estimating energy expenditure using body-worn accelerometers: a comparison of methods, sensors number and positioning.
Mar 7, 2016 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
A wearable wireless sensor platform for interactive dance performances
Feb 29, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
K-center Problem
Feb 22, 2016 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
A practical approach for recognizing eating moments with wrist-mounted inertial sensing.
Feb 22, 2016 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Minimun K-cut Problem
Feb 15, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Modeling Physical Activity Behavior Change
Feb 8, 2016 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Multi-way Cut Problem (Approximation Algorithms)
Feb 1, 2016 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Efficient graph-based semi-supervised learning of structured tagging models.
Feb 1, 2016 12:00 PM
Dana Hall, Washington State University
Ali Rokni
TSP Part I (Approximation Algorithms)
Jan 25, 2016 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Trading off prediction accuracy and power consumption for context-aware wearable computing.
Jan 25, 2016 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
2015
Shortest Superstring(Approximation Algorithm)
Dec 2, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
A Machine Learning Approach For Medication Adherence Monitoring Using Body-Worn Sensors
Nov 30, 2015 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Set Cover Layering Approach
Nov 18, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Investigating the Accuracy of Fitbit Activity Trackers
Nov 16, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
An energy-aware method for the joint recognition of activities and gestures using wearable sensors.
Nov 9, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Hidden Markov Model Part II
Nov 4, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Gait Analysis Review
Nov 2, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Hidden Markov Model Part I
Oct 28, 2015 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Identifying Physical Activity Profiles in COPD Patients Using Topic Models.
Oct 26, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
I did not smoke 100 cigarettes today!: avoiding false positives in real-world activity recognition.
Oct 12, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Set cover Problem
Oct 7, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Transfer learning by borrowing examples for multiclass object detection
Oct 5, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Introduction of Deep Learning
Sep 30, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Predicting daily activities from egocentric images using deep learning.
Sep 28, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Ordering points to identify the clustering structure (OPTICS)
Sep 23, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
InterruptMe: Designing intelligent prompting mechanisms for pervasive applications.
Sep 21, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Stochastic methods (Simulated Annealing)
Sep 16, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Machine Learning Inspired Power Management in Multicore Chips
Sep 14, 2015 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
Dynamic Programming Parsing for Context-Free Grammars in Continuous Speech Recognition
Sep 9, 2015 12:00 PM
Dana Hall, Washington State University
Niloofar Hezarjaribi
DBSCAN
Sep 7, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Health Behavior Models in the Age of Mobile Interventions
Aug 5, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Data Collection Tool for Android Wearable and Handheld Devices
Jul 22, 2015 12:00 PM
Dana Hall, Washington State University
Deontae Pharr
Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors
Jul 15, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
derivative free optimization: direction search
Jul 8, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Kullback Leibler divergence
Jul 1, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Data sensing and analysis: Challenges for wearables,
Jul 1, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Approximation Problems (Vertex cover and TSP)
Jun 24, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Randomized Algorithms: The hiring problem
Jun 10, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
The Floyd-Warshall algorithm
Jun 3, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
A Novel Approach to Reducing the Number of the Sensing Units for Wearable Gait Analysis Systems
Jun 3, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
AdaBoost.R2 and Two-stage TrAdaBoost.R2 (Transfer Learning for regression models)
May 27, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Boosting for Regression Transfer
May 20, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Baum-Welch algorithm
May 20, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Linear Programming: Introduction, Formulation and Solving
May 13, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Transfer Learning Algorithms in Wearable Monitoring Platforms
Apr 30, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Medication Adherence Assessment Using Wearable Sensors
Apr 30, 2015 12:00 PM
Dana Hall, Washington State University
Ramyya Hari
Edema Monitoring Using Wearable Sensors
Apr 30, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Computational Reliability of Mobile Wearable Sensor Networks
Apr 30, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Robust Gait Analysis Algorithms with Wearable Sensors
Apr 28, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Google Glasses for Visual Field Expansion
Apr 28, 2015 12:00 PM
Dana Hall, Washington State University
Samaneh Aminikhanghahi
Assessing Accuracy Performance of Fitbit Activity Trackers
Apr 28, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
,
Chris Chain
Confidence-based Multiclass AdaBoost for Physical Activity Monitoring
Apr 23, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
,
Ramyar Saeedi
WiBreathe: Estimating Respiration Rate Using Wireless Signals in Natural Settings in the Home
Apr 16, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
,
Ramyya Hari
Viterbi Algorithm
Apr 15, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Inviz: Low-power Personalized Gesture Recognition using Wearable Textile Capacitive Sensor Arrays
Apr 9, 2015 12:00 PM
Dana Hall, Washington State University
Samaneh Aminikhanghahi
Gamification of Learning and Instruction
Apr 9, 2015 12:00 PM
Dana Hall, Washington State University
Chris Chain
Assessing physical activity during pregnancy and postpartum
Apr 2, 2015 12:00 PM
Dana Hall, Washington State University
Dr. Christopher Connolly
Set Cover Problem
Apr 1, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Gait and Falls
Mar 12, 2015 12:00 PM
Dana Hall, Washington State University
Dr. Robert Catena
Introduction to Algorithm Complexity
Mar 11, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Maximum relevancy maximum complementary feature selection for multi-sensor activity recognition
Mar 5, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
dynamic programming Problem, Knapsack
Mar 4, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Ultra Low Power Signal Processing in Wearable Monitoring Systems: A Tiered Screening Architecture with Optimal Bit Resolution
Feb 26, 2015 12:00 PM
Dana Hall, Washington State University
Hassan Ghasemzadeh
Network Flow Problem
Feb 18, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Chroma: A Wearable Augmented-Reality Solution for Color Blindness
Feb 12, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
String Matching
Feb 11, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Wearable coach for sport training: A quantitative model to evaluate wrist-rotation in golf.
Feb 5, 2015 12:00 PM
Dana Hall, Washington State University
Hassan Ghasemzadeh
Greedy Algorithms
Feb 4, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Using Google Glasses Technology for Visual Field Expansion.
Jan 29, 2015 12:00 PM
Dana Hall, Washington State University
Samaneh Aminikhanghahi
MET Calculation using Wearable Sensors.
Jan 29, 2015 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Hungarian Algorithms
Jan 28, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Semi-Learning of Activity Labels in Real-Time using Wearable Motion Sensors.
Jan 22, 2015 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Patient-Centric On-Body Sensor Localization in Smart Health Systems
Jan 22, 2015 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Shortest Path Problem
Jan 21, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Smart-Cuff: A Wearable Bio-Sensing Platform with Activity-Sensitive Information Quality Assessment for Monitoring Ankle Edema
Jan 15, 2015 12:00 PM
Dana Hall, Washington State University
Ramin Fallahzadeh
Investigation of Gait Characteristics in Glaucoma Patients with a Shoe-Integrated Sensing System
Jan 15, 2015 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
2014
Gait and Balance Analysis for Patients With Alzheimer's Disease Using an Inertial-Sensor-Based Wearable Instrument,
Nov 13, 2014 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
MoviPill: improving medication compliance for elders using a mobile persuasive social game
Oct 21, 2014 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
AutoSense: unobtrusively wearable sensor suite for inferring the onset, causality, and consequences of stress in the field.
Oct 2, 2014 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
Cost-sensitive feature selection for on-body sensor localization.
Sep 18, 2014 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Electronic Tools to Measure and Enhance Medication Adherence
Sep 11, 2014 12:00 PM
Dana Hall, Washington State University
Ali Rokni
Met calculations from on-body accelerometers for exergaming movements.
Sep 4, 2014 12:00 PM
Dana Hall, Washington State University
Parastoo Alinia
Toward seamless wearable sensing: Automatic on-body sensor localization for physical activity monitoring.
Aug 28, 2014 12:00 PM
Dana Hall, Washington State University
Ramyar Saeedi
Cancer Care Management through a Mobile Phone Health Approach: Key Consideration
Aug 28, 2014 12:00 PM
Dana Hall, Washington State University
Yuchao Ma
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