Jain, Lalit

25 publications

AISTATS 2024 A/B Testing and Best-Arm Identification for Linear Bandits with Robustness to Non-Stationarity Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson

NeurIPS 2024 Adaptive Experimentation When You Can't Experiment Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain

UAI 2024 Fair Active Learning in Low-Data Regimes Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson

NeurIPS 2024 Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak

NeurIPS 2024 Nearly Minimax Optimal Submodular Maximization with Bandit Feedback Artin Tajdini, Lalit Jain, Kevin Jamieson

AISTATS 2024 Optimal Exploration Is No Harder than Thompson Sampling Zhaoqi Li, Kevin Jamieson, Lalit Jain

AISTATS 2024 Pessimistic Off-Policy Multi-Objective Optimization Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu

NeurIPS 2023 Experimental Designs for Heteroskedastic Variance Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain

AISTATS 2022 Nearly Optimal Algorithms for Level Set Estimation Blake Mason, Lalit Jain, Subhojyoti Mukherjee, Romain Camilleri, Kevin Jamieson, Robert Nowak

NeurIPS 2022 Active Learning with Safety Constraints Romain Camilleri, Andrew Wagenmaker, Jamie H Morgenstern, Lalit Jain, Kevin G. Jamieson

AAAI 2022 An Experimental Design Approach for Regret Minimization in Logistic Bandits Blake Mason, Kwang-Sung Jun, Lalit Jain

NeurIPS 2022 Instance-Optimal PAC Algorithms for Contextual Bandits Zhaoqi Li, Lillian Ratliff, Houssam Nassif, Kevin G. Jamieson, Lalit Jain

ICML 2021 Improved Algorithms for Agnostic Pool-Based Active Classification Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson

ICML 2021 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif

NeurIPS 2021 Selective Sampling for Online Best-Arm Identification Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson

NeurIPS 2020 An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits Julian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin G. Jamieson

NeurIPS 2020 Finding All $\epsilon$-Good Arms in Stochastic Bandits Blake Mason, Lalit Jain, Ardhendu Tripathy, Robert Nowak

UAI 2020 Spectral Methods for Ranking with Scarce Data Lalit Jain, Anna Gilbert, Umang Varma

NeurIPS 2019 A New Perspective on Pool-Based Active Classification and False-Discovery Control Lalit Jain, Kevin G. Jamieson

NeurIPS 2019 Sequential Experimental Design for Transductive Linear Bandits Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian Ratliff

NeurIPS 2018 A Bandit Approach to Sequential Experimental Design with False Discovery Control Kevin G. Jamieson, Lalit Jain

ICML 2018 Firing Bandits: Optimizing Crowdfunding Lalit Jain, Kevin Jamieson

NeurIPS 2017 Learning Low-Dimensional Metrics Blake Mason, Lalit Jain, Robert Nowak

NeurIPS 2016 Finite Sample Prediction and Recovery Bounds for Ordinal Embedding Lalit Jain, Kevin G. Jamieson, Rob Nowak

NeurIPS 2015 NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning Kevin G. Jamieson, Lalit Jain, Chris Fernandez, Nicholas J. Glattard, Rob Nowak