16 citations · 35 across the 20 of their papers we have counts for
24 papers
Inference-time Unlearning Using Conformal Prediction
Somnath Basu Roy Chowdhury, Rahul Kidambi, Avinava Dubey +4
Machine unlearning is the process of efficiently removing specific information from a trained machine learning model without retraining from scratch. Existing unlearning methods, w…
Fundamental Limits of Perfect Concept Erasure
Somnath Basu Roy Chowdhury, Avinava Dubey, Ahmad Beirami +4
Concept erasure is the task of erasing information about a concept (e.g., gender or race) from a representation set while retaining the maximum possible utility -- information from…
Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning
Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski +4
Recent efforts to scale Transformer models have demonstrated rapid progress across a wide range of tasks (Wei et al., 2022). However, fine-tuning these models for downstream tasks…
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
Somnath Basu Roy Chowdhury, Krzysztof Choromanski, Arijit Sehanobish +2
Machine unlearning is the process of efficiently removing the influence of a training data instance from a trained machine learning model without retraining it from scratch. A popu…
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury +4
We present a new class of fast polylog-linear algorithms based on the theory of structured matrices (in particular low displacement rank) for integrating tensor fields defined on w…
Exploring Safety-Utility Trade-Offs in Personalized Language Models
Anvesh Rao Vijjini, Somnath Basu Roy Chowdhury, Snigdha Chaturvedi
As large language models (LLMs) become increasingly integrated into daily applications, it is essential to ensure they operate fairly across diverse user demographics. In this work…
Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity
Jake Varley, Sumeet Singh, Deepali Jain +5
We present an embodied AI system which receives open-ended natural language instructions from a human, and controls two arms to collaboratively accomplish potentially long-horizon…
Incremental Extractive Opinion Summarization Using Cover Trees
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey +4
Extractive opinion summarization involves automatically producing a summary of text about an entity (e.g., a product's reviews) by extracting representative sentences that capture…
Robust Concept Erasure via Kernelized Rate-Distortion Maximization
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey +2
Distributed representations provide a vector space that captures meaningful relationships between data instances. The distributed nature of these representations, however, entangle…
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami +4
Fairness, especially group fairness, is an important consideration in the context of machine learning systems. The most commonly adopted group fairness-enhancing techniques are in-…
Efficient Graph Field Integrators Meet Point Clouds
Krzysztof Choromanski, Arijit Sehanobish, Han Lin +13
We present two new classes of algorithms for efficient field integration on graphs encoding point clouds. The first class, SeparatorFactorization(SF), leverages the bounded genus o…
Sustaining Fairness via Incremental Learning
Somnath Basu Roy Chowdhury, Snigdha Chaturvedi
Machine learning systems are often deployed for making critical decisions like credit lending, hiring, etc. While making decisions, such systems often encode the user's demographic…
Read Top News First: A Document Reordering Approach for Multi-Document News Summarization
Chao Zhao, Tenghao Huang, Somnath Basu Roy Chowdhury +3
A common method for extractive multi-document news summarization is to re-formulate it as a single-document summarization problem by concatenating all documents as a single meta-do…
Unsupervised Extractive Opinion Summarization Using Sparse Coding
Somnath Basu Roy Chowdhury, Chao Zhao, Snigdha Chaturvedi
Opinion summarization is the task of automatically generating summaries that encapsulate information from multiple user reviews. We present Semantic Autoencoder (SemAE) to perform…
Learning Fair Representations via Rate-Distortion Maximization
Somnath Basu Roy Chowdhury, Snigdha Chaturvedi
Text representations learned by machine learning models often encode undesirable demographic information of the user. Predictive models based on these representations can rely on s…
Adversarial Scrubbing of Demographic Information for Text Classification
Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li +3
Contextual representations learned by language models can often encode undesirable attributes, like demographic associations of the users, while being trained for an unrelated targ…
Does Commonsense help in detecting Sarcasm?
Somnath Basu Roy Chowdhury, Snigdha Chaturvedi
Sarcasm detection is important for several NLP tasks such as sentiment identification in product reviews, user feedback, and online forums. It is a challenging task requiring a dee…
Is Everything in Order? A Simple Way to Order Sentences
Somnath Basu Roy Chowdhury, Faeze Brahman, Snigdha Chaturvedi
The task of organizing a shuffled set of sentences into a coherent text has been used to evaluate a machine's understanding of causal and temporal relations. We formulate the sente…
Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing
Somnath Basu Roy Chowdhury, K M Annervaz, Ambedkar Dukkipati
Supervised learning models are typically trained on a single dataset and the performance of these models rely heavily on the size of the dataset, i.e., amount of data available wit…
Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing
K M Annervaz, Somnath Basu Roy Chowdhury, Ambedkar Dukkipati
Machine Learning has been the quintessential solution for many AI problems, but learning is still heavily dependent on the specific training data. Some learning models can be incor…
SIMILARnet: Simultaneous Intelligent Localization and Recognition Network
Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury
Global Average Pooling (GAP) [4] has been used previously to generate class activation for image classification tasks. The motivation behind SIMILARnet comes from the fact that the…
Location Optimization of ATM Networks
Somnath Basu Roy Chowdhury, Biswarup Bhattacharya, Sumit Agarwal
ATMs enable the public to perform financial transactions. Banks try to strategically position their ATMs in order to maximize transactions and revenue. In this paper, we introduce…
Handwriting Profiling using Generative Adversarial Networks
Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury
Handwriting is a skill learned by humans from a very early age. The ability to develop one's own unique handwriting as well as mimic another person's handwriting is a task learned…
SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks
Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury
Autonomous driving is one of the most recent topics of interest which is aimed at replicating human driving behavior keeping in mind the safety issues. We approach the problem of l…