93 citations · 199 across the 28 of their papers we have counts for
29 papers
Gradient Under Microscope: Benchmarking Resource Utilization of Memory-Efficient Gradient Computation Methods
Sarthak Mahapatra, Zihan Zhou, Khatoon Khedri +2
AI training's rising resource intensity is straining electricity supplies and carbon budgets, motivating systematic study of memory-efficient training on constrained hardware. We b…
NeuroViz: Real-time Interactive Visualization of Forward and Backward Passes in Neural Network Training
Tanvi Sharma, Reza Rawassizadeh
Training neural networks is difficult to interpret, particularly for newcomers. We introduce NeuroViz, an interactive visualization tool that supports real-time exploration of full…
Interpretable Prostate Cancer Detection using a Small Cohort of MRI Images
Vahid Monfared, Mohammad Hadi Gharib, Ali Sabri +4
Prostate cancer is a leading cause of mortality in men, yet interpretation of T2-weighted prostate MRI remains challenging due to subtle and heterogeneous lesions. We developed an…
Pruning and Quantization Impact on Graph Neural Networks
Khatoon Khedri, Reza Rawassizadeh, Qifu Wen +1
Graph neural networks (GNNs) are known to operate with high accuracy on learning from graph-structured data, but they suffer from high computational and resource costs. Neural netw…
GradES: Significantly Faster Training in Transformers with Gradient-Based Early Stopping
Qifu Wen, Xi Zeng, Zihan Zhou +4
Early stopping monitors global validation loss and halts all parameter updates simultaneously, which is computationally costly for large transformers due to the extended time requi…
TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization
Hainan Wang, Mehdi Hosseinzadeh, Reza Rawassizadeh
The success of the generative model has gained unprecedented attention in the music generation area. Transformer-based architectures have set new benchmarks for model performance.…
Attentions Under the Microscope: A Comparative Study of Resource Utilization for Variants of Self-Attention
Zhengyu Tian, Anantha Padmanaban Krishna Kumar, Hemant Krishnakumar +1
As large language models (LLMs) and visual language models (VLMs) grow in scale and application, attention mechanisms have become a central computational bottleneck due to their hi…
From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis
Qifu Wen, Prishita Kochhar, Sherif Zeyada +2
The rapid proliferation of data science forced different groups of individuals with different backgrounds to adapt to statistical analysis. We hypothesize that conversational agent…
Analyzing the Resource Utilization of Lambda Functions on Mobile Devices: Case Studies on Kotlin and Swift
Chibundom U. Ejimuda, Gaston Longhitano, Reza Rawassizadeh
With billions of smartphones in use globally, the daily time spent on these devices contributes significantly to overall electricity consumption. Given this scale, even minor reduc…
The Impact of Quantization and Pruning on Deep Reinforcement Learning Models
Heng Lu, Mehdi Alemi, Reza Rawassizadeh
Deep reinforcement learning (DRL) has achieved remarkable success across various domains, such as video games, robotics, and, recently, large language models. However, the computat…
Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases
Xiang Zhang, Khatoon Khedri, Reza Rawassizadeh
Large Language Models (LLMs) can automate or substitute different types of tasks in the software engineering process. This study evaluates the resource utilization and accuracy of…
Augmenting Vision-Based Human Pose Estimation with Rotation Matrix
Milad Vazan, Fatemeh Sadat Masoumi, Ruizhi Ou +1
Fitness applications are commonly used to monitor activities within the gym, but they often fail to automatically track indoor activities inside the gym. This study proposes a mode…
A Survey of AI Music Generation Tools and Models
Yueyue Zhu, Jared Baca, Banafsheh Rekabdar +1
In this work, we provide a comprehensive survey of AI music generation tools, including both research projects and commercialized applications. To conduct our analysis, we classifi…
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image Analysis
Morteza Homayounfar, Mohamad Koohi-Moghadam, Reza Rawassizadeh +1
As deep neural networks include a high number of parameters and operations, it can be a challenge to implement these models on devices with limited computational resources. Despite…
LightDepth: A Resource Efficient Depth Estimation Approach for Dealing with Ground Truth Sparsity via Curriculum Learning
Fatemeh Karimi, Amir Mehrpanah, Reza Rawassizadeh
Advances in neural networks enable tackling complex computer vision tasks such as depth estimation of outdoor scenes at unprecedented accuracy. Promising research has been done on…
Longitudinal Analysis of Heart Rate and Physical Activity Collected from Smartwatches
Fatemeh Karimi, Zohre Amoozgar, Reza Reiazi +2
Smartwatches (SWs) can continuously and autonomously monitor vital signs, including heart rates and physical activities involving wrist movement. The monitoring capability of SWs h…
Speeding Up Question Answering Task of Language Models via Inverted Index
Xiang Ji, Yesim Sungu-Eryilmaz, Elaheh Momeni +1
Natural language processing applications, such as conversational agents and their question-answering capabilities, are widely used in the real world. Despite the wide popularity of…
ODSearch: Fast and Resource Efficient On-device Natural Language Search for Fitness Trackers' Data
Reza Rawassizadeh, Yi Rong
Mobile and wearable technologies have promised significant changes to the healthcare industry. Although cutting-edge communication and cloud-based technologies have allowed for the…
FEDZIP: A Compression Framework for Communication-Efficient Federated Learning
Amirhossein Malekijoo, Mohammad Javad Fadaeieslam, Hanieh Malekijou +3
Federated Learning marks a turning point in the implementation of decentralized machine learning (especially deep learning) for wireless devices by protecting users' privacy and sa…
Exploiting BERT to improve aspect-based sentiment analysis performance on Persian language
H. Jafarian, A. H. Taghavi, A. Javaheri +1
Aspect-based sentiment analysis (ABSA) is a more detailed task in sentiment analysis, by identifying opinion polarity toward a certain aspect in a text. This method is attracting m…
Immediate or Reflective?: Effects of Real-timeFeedback on Group Discussions over Videochat
Samiha Samrose, Reza Rawassizadeh, Ehsan Hoque
Having a group discussion with the members holding conflicting viewpoints is difficult. It is especially challenging for machine-mediated discussions in which the subtle social cue…
SEFR: A Fast Linear-Time Classifier for Ultra-Low Power Devices
Hamidreza Keshavarz, Mohammad Saniee Abadeh, Reza Rawassizadeh
A fundamental challenge for running machine learning algorithms on battery-powered devices is the time and energy limitations, as these devices have constraints on resources. There…
CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
Tahereh Javaheri, Morteza Homayounfar, Zohreh Amoozgar +19
Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease a…
Public vs Media Opinion on Robots
Alireza Javaheri, Navid Moghadamnejad, Hamidreza Keshavarz +4
Fast proliferation of robots in people's everyday lives during recent years calls for a profound examination of public consensus, which is the ultimate determinant of the future of…