activity
20182026
collaborators

7 papers

cs.CL2026

DIVERSED: Relaxed Speculative Decoding via Dynamic Ensemble Verification

Ziyi Wang, Siva Rajesh Kasa, Ankith M S +6

Speculative decoding is an effective technique for accelerating large language model inference by drafting multiple tokens in parallel. In practice, its speedup is often bottleneck…

cs.CR2025

The Hidden Cost of Modeling P(X): Vulnerability to Membership Inference Attacks in Generative Text Classifiers

Owais Makroo, Siva Rajesh Kasa, Sumegh Roychowdhury +4

Membership Inference Attacks (MIAs) pose a critical privacy threat by enabling adversaries to determine whether a specific sample was included in a model's training dataset. Despit…

cs.LG2025

Generative or Discriminative? Revisiting Text Classification in the Era of Transformers

Siva Rajesh Kasa, Karan Gupta, Sumegh Roychowdhury +7

The comparison between discriminative and generative classifiers has intrigued researchers since Efron's seminal analysis of logistic regression versus discriminant analysis. While…

stat.ME2020

Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation

Siva Rajesh Kasa, Vaibhav Rajan

Copulas provide a modular parameterization of multivariate distributions that decouples the modeling of marginals from the dependencies between them. Gaussian Mixture Copula Model…

stat.ML2020

Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional Data

Siva Rajesh Kasa, Vaibhav Rajan

We study two practically important cases of model based clustering using Gaussian Mixture Models: (1) when there is misspecification and (2) on high dimensional data, in the light…

stat.CO2018

Automatic Differentiation in Mixture Models

Siva Rajesh Kasa, Vaibhav Rajan

In this article, we discuss two specific classes of models - Gaussian Mixture Copula models and Mixture of Factor Analyzers - and the advantages of doing inference with gradient de…