2024
When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories @CNeRG Reading Group
Despite their impressive performance on diverse tasks, large language models (LMs) still struggle with tasks requiring rich world …
2023
Scalable and Accurate Channel pruning @CNeRG Mini Retreat
The deeper and wider architectures of recent convolutional neural networks (CNN) are responsible for superior performance in computer …
Winning the Lottery Ahead of Time: Efficient Early Network Pruning @CNeRG Reading Group
Pruning, the task of sparsifying deep neural networks, received increasing attention recently. Although state-of-the-art pruning …
2022
Practical Adversarial Robustness in Deep Learning: Problems and Solutions @CNeRG Reading Group
Deep learning has brought us tremendous achievements in many fields such as computer vision, natural language processing. In spite of …
LearnDefend: Learning to Defend against Backdoor Attacks on Federated Learning @AIMLSystems Doctoral Symposium 2022
Federated Learning has emerged as an important paradigm for training Machine Learning (ML) models. The key idea is that many clients …
Accurate and efficient channel pruning via orthogonal matching pursuit @AIMLSystems 2022
The deeper and wider architectures of recent convolutional neural networks (CNN) are responsible for superior performance in computer …
When-To-Post on Social Networks @CNeRG Reading Group @CNeRG Reading Group
For many users on social networks, one of the goals when broadcasting content is to reach a large audience. The probability of …
2021
SummEval: Re-evaluating Summarization Evaluation @CNeRG Reading Group
The scarcity of comprehensive up-to-date studies on evaluation metrics for text summarization and the lack of consensus regarding …
COVID-19 Detection on Chest X-Ray and CT Scan Images Using Multi-image Augmented Deep Learning Model @ICMC 2021
COVID-19 is a deadly and highly infectious pneumonia type disease. RT-PCR is a proven testing methodology for the detection of …
2020
Some Applications of First and Second Order Derivative Operators in Machine Learning and Clinical Diagnosis @M.Tech Thesis, NIT Durgapur
Unlike image restoration, image enhancement techniques are found to be subjective in nature as the appropriateness of the appearance of …
