131 citations · 149 across the 8 of their papers we have counts for
8 papers
SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness
Sangamesh Kodge, Deepak Ravikumar, Gobinda Saha +1
Label corruption, where training samples are mislabeled due to non-expert annotation or adversarial attacks, significantly degrades model performance. Acquiring large, perfectly la…
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class Forgetting
Sangamesh Kodge, Gobinda Saha, Kaushik Roy
Machine unlearning is a prominent and challenging field, driven by regulatory demands for user data deletion and heightened privacy awareness. Existing approaches involve retrainin…
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions
Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy
Decentralized learning over distributed datasets can have significantly different data distributions across the agents. The current state-of-the-art decentralized algorithms mostly…
Low Precision Decentralized Distributed Training over IID and non-IID Data
Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy
Decentralized distributed learning is the key to enabling large-scale machine learning (training) on edge devices utilizing private user-generated local data, without relying on th…
BERMo: What can BERT learn from ELMo?
Sangamesh Kodge, Kaushik Roy
We propose BERMo, an architectural modification to BERT, which makes predictions based on a hierarchy of surface, syntactic and semantic language features. We use linear combinatio…
Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection
Deepak Ravikumar, Sangamesh Kodge, Isha Garg +1
Deep neural networks have found widespread adoption in solving complex tasks ranging from image recognition to natural language processing. However, these networks make confident m…
TREND: Transferability based Robust ENsemble Design
Deepak Ravikumar, Sangamesh Kodge, Isha Garg +1
Deep Learning models hold state-of-the-art performance in many fields, but their vulnerability to adversarial examples poses threat to their ubiquitous deployment in practical sett…
IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array
Mustafa Ali, Akhilesh Jaiswal, Sangamesh Kodge +3
`In-memory computing' is being widely explored as a novel computing paradigm to mitigate the well known memory bottleneck. This emerging paradigm aims at embedding some aspects of…