5 citations · 10 across the 13 of their papers we have counts for
13 papers
Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity
Riddhiman Bhattacharyya, Sayak Chakrabarty, Imon Banerjee
Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline datasets has been challenging due…
Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation
Sayak Chakrabarty, Souradip Pal
Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic memory and latency budgets.…
Identifying and Mitigating Gender Cues in Academic Recommendation Letters: An Interpretability Case Study
Charlotte S. Alexander, Shane Storks, Souradip Pal +4
Letters of recommendation (LoRs) can carry patterns of implicitly gendered language that can inadvertently influence downstream decisions, e.g. in hiring and admissions. In this wo…
PixRec: Leveraging Visual Context for Next-Item Prediction in Sequential Recommendation
Sayak Chakrabarty, Souradip Pal
Large Language Models (LLMs) have recently shown strong potential for usage in sequential recommendation tasks through text-only models, which combine advanced prompt design, contr…
Time-Constrained Recommendations: Reinforcement Learning Strategies for E-Commerce
Sayak Chakrabarty, Souradip Pal
Unlike traditional recommendation tasks, finite user time budgets introduce a critical resource constraint, requiring the recommender system to balance item relevance and evaluatio…
CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
Randeep Bhatia, Nikos Papadis, Murali Kodialam +2
We propose CLoVE (Clustering of Loss Vector Embeddings), a novel algorithm for Clustered Federated Learning (CFL). In CFL, clients are naturally grouped into clusters based on thei…
CLT and Edgeworth Expansion for m-out-of-n Bootstrap Estimators of The Studentized Median
Imon Banerjee, Sayak Chakrabarty
The m-out-of-n bootstrap, originally proposed by Bickel, Gotze, and Zwet (1992), approximates the distribution of a statistic by repeatedly drawing m subsamples (with m much smalle…
MM-PoE: Multiple Choice Reasoning via. Process of Elimination using Multi-Modal Models
Sayak Chakrabarty, Souradip Pal
This paper introduces Multiple Choice Reasoning via. Process of Elimination using Multi-Modal models, herein referred to as Multi-Modal Process of Elimination (MM-PoE). This novel…
Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
Sayak Chakrabarty, Souradip Pal
Automated documentation of programming source code is a challenging task with significant practical and scientific implications for the developer community. We present a large lang…
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
Arghya Datta, Sayak Chakrabarty
Probabilistic principal component analysis (PPCA) is currently one of the most used statistical tools to reduce the ambient dimension of the data. From multidimensional scaling to…
Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!
Sayak Chakrabarty, Konstantin Makarychev
We show that a simple single-pass semi-streaming variant of the Pivot algorithm for Correlation Clustering gives a (3 + ε)-approximation using O(n/ε) words of memory. This is a sli…
The Repeated Divisor Function and Possible Correlation with Highly Composite Numbers
Sayak Chakrabarty, Arghya Dutta
Let n be a non-null positive integer and is the number of positive divisors of n, called the divisor function. Of course, . if and only if . F…
Non Existence of any Arithmetic Progression or Geometric Progression whose each term is a Palindrome
Sayak Chakrabarty, Argya Datta
We investigate whether there exists an arithmetic progression or geometric progression consisting only palindromic numbers. In this paper we show that the answer to this question i…