45 citations · 111 across the 15 of their papers we have counts for
15 papers
Generating DDPM-based Samples from Tilted Distributions
Himadri Mandal, Dhruman Gupta, Rushil Gupta +5
Given independent samples from a -dimensional probability distribution, our aim is to generate diffusion-based samples from a distribution obtained by tilting the original,…
Functional Knowledge Transfer with Self-supervised Representation Learning
Prakash Chandra Chhipa, Muskaan Chopra, Gopal Mengi +7
This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge tra…
CueCAn: Cue Driven Contextual Attention For Identifying Missing Traffic Signs on Unconstrained Roads
Varun Gupta, Anbumani Subramanian, C. V. Jawahar +1
Unconstrained Asian roads often involve poor infrastructure, affecting overall road safety. Missing traffic signs are a regular part of such roads. Missing or non-existing object d…
MNL-Bandit in non-stationary environments
Ayoub Foussoul, Vineet Goyal, Varun Gupta
In this paper, we study the MNL-Bandit problem in a non-stationary environment and present an algorithm with a worst-case expected regret of $\tilde{O}\left( \min \left\{ \sqrt{NTL…
Multicalibrated Regression for Downstream Fairness
Ira Globus-Harris, Varun Gupta, Christopher Jung +3
We show how to take a regression function that is appropriately ``multicalibrated'' and efficiently post-process it into an approximately error minimizing classifier sati…
Practical Adversarial Multivalid Conformal Prediction
Osbert Bastani, Varun Gupta, Christopher Jung +3
We give a simple, generic conformal prediction method for sequential prediction that achieves target empirical coverage guarantees against adversarially chosen data. It is computat…
Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems
Yuwei Luo, Varun Gupta, Mladen Kolar
We consider the problem of controlling a Linear Quadratic Regulator (LQR) system over a finite horizon with fixed and known cost matrices , but unknown and non-stationary…
Adaptive Machine Unlearning
Varun Gupta, Christopher Jung, Seth Neel +3
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for seq…
Online Multivalid Learning: Means, Moments, and Prediction Intervals
Varun Gupta, Christopher Jung, Georgy Noarov +2
We present a general, efficient technique for providing contextual predictions that are "multivalid" in various senses, against an online sequence of adversarially chosen examples…
On BPS Strings in Yang-Mills Theory
Sujay K. Ashok, Varun Gupta, Nemani V. Suryanarayana
We study singular time-dependent -BPS configurations in the abelian sector of supersymmetric Yang-Mills theory that represent BPS string-like defec…
Constrained High Dimensional Statistical Inference
Ming Yu, Varun Gupta, Mladen Kolar
In typical high dimensional statistical inference problems, confidence intervals and hypothesis tests are performed for a low dimensional subset of model parameters under the assum…
Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching
Ming Yu, Varun Gupta, Mladen Kolar
Probabilistic graphical models provide a flexible yet parsimonious framework for modeling dependencies among nodes in networks. There is a vast literature on parameter estimation a…
Learning Influence-Receptivity Network Structure with Guarantee
Ming Yu, Varun Gupta, Mladen Kolar
Traditional works on community detection from observations of information cascade assume that a single adjacency matrix parametrizes all the observed cascades. However, in reality…
Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach
Ming Yu, Varun Gupta, Mladen Kolar
We study the problem of recovery of matrices that are simultaneously low rank and row and/or column sparse. Such matrices appear in recent applications in cognitive neuroscience, i…
Estimation of a Low-rank Topic-Based Model for Information Cascades
Ming Yu, Varun Gupta, Mladen Kolar
We consider the problem of estimating the latent structure of a social network based on the observed information diffusion events, or cascades, where the observations for a given c…