26 citations · 59 across the 7 of their papers we have counts for
7 papers
Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning
Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi +3
We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classif…
A Configurable Pythonic Data Center Model for Sustainable Cooling and ML Integration
Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez +5
There have been growing discussions on estimating and subsequently reducing the operational carbon footprint of enterprise data centers. The design and intelligent control for data…
Sustainability of Data Center Digital Twins with Reinforcement Learning
Soumyendu Sarkar, Avisek Naug, Antonio Guillen +4
The rapid growth of machine learning (ML) has led to an increased demand for computational power, resulting in larger data centers (DCs) and higher energy consumption. To address t…
N-Critics: Self-Refinement of Large Language Models with Ensemble of Critics
Sajad Mousavi, Ricardo Luna Gutiérrez, Desik Rengarajan +5
We propose a self-correction mechanism for Large Language Models (LLMs) to mitigate issues such as toxicity and fact hallucination. This method involves refining model outputs thro…
Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness
Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi +6
We present a novel framework for generating adversarial benchmarks to evaluate the robustness of image classification models. Our framework allows users to customize the types of d…
ECGBERT: Understanding Hidden Language of ECGs with Self-Supervised Representation Learning
Seokmin Choi, Sajad Mousavi, Phillip Si +3
In the medical field, current ECG signal analysis approaches rely on supervised deep neural networks trained for specific tasks that require substantial amounts of labeled data. Ho…