Lalit Jain

According to our database, Lalit Jain authored at least 40 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Effective Adaptive Exploration of Prices and Promotions in Choice-Based Demand Models.

Lalit Jain, Zhaoqi Li, Erfan Loghmani, Blake Mason, Hema Yoganarasimhan

Mark. Sci., 2024

Adaptive Experimentation When You Can't Experiment.

Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain

CoRR, 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 T. Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak

CoRR, 2024

Off-Policy Evaluation from Logged Human Feedback.

Aniruddha Bhargava, Lalit Jain, Branislav Kveton, Ge Liu, Subhojyoti Mukherjee

CoRR, 2024

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice.

Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain

Proceedings of the ACM on Web Conference 2024, 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 G. Jamieson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Optimal Exploration is no harder than Thompson Sampling.

Zhaoqi Li, Kevin G. Jamieson, Lalit Jain

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Pessimistic Off-Policy Multi-Objective Optimization.

Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

DIRECT: Deep Active Learning under Imbalance and Label Noise.

Shyam Nuggehalli, Jifan Zhang, Lalit Jain, Robert D. Nowak

CoRR, 2023

Fair Active Learning in Low-Data Regimes.

Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson

CoRR, 2023

Minimax Optimal Submodular Optimization with Bandit Feedback.

Artin Tajdini, Lalit Jain, Kevin Jamieson

CoRR, 2023

Experimental Designs for Heteroskedastic Variance.

Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design.

Jennifer Brennan, Lalit Jain, Sofia Garman, Ann E. Donnelly, Erik Scott Wright, Kevin G. Jamieson

PLoS Comput. Biol., 2022

Adaptive Experimental Design and Counterfactual Inference.

Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain

CoRR, 2022

Active Learning with Safety Constraints.

Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin G. Jamieson

CoRR, 2022

Instance-optimal PAC Algorithms for Contextual Bandits.

Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin G. Jamieson, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Learning with Safety Constraints.

Romain Camilleri, Andrew Wagenmaker, Jamie H. Morgenstern, Lalit Jain, Kevin G. Jamieson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nearly Optimal Algorithms for Level Set Estimation.

Blake Mason, Lalit Jain, Subhojyoti Mukherjee, Romain Camilleri, Kevin G. Jamieson, Robert D. Nowak

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits.

Blake Mason, Kwang-Sung Jun, Lalit Jain

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Selective Sampling for Online Best-arm Identification.

Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improved Algorithms for Agnostic Pool-based Active Classification.

Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson

Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits.

Kwang-Sung Jun, Lalit Jain, Houssam Nassif, Blake Mason

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits.

Kwang-Sung Jun, Lalit Jain, Houssam Nassif

CoRR, 2020

Finding All ε-Good Arms in Stochastic Bandits.

Blake Mason, Lalit Jain, Ardhendu Tripathy, Robert D. Nowak

CoRR, 2020

Spectral Methods for Ranking with Scarce Data.

Lalit Jain, Anna C. Gilbert, Umang Varma

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Finding All $\epsilon$-Good Arms in Stochastic Bandits.

Blake Mason, Lalit Jain, Ardhendu Tripathy, Robert Nowak

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

A New Perspective on Pool-Based Active Classification and False-Discovery Control.

Lalit Jain, Kevin G. Jamieson

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sequential Experimental Design for Transductive Linear Bandits.

Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Bandit Approach to Multiple Testing with False Discovery Control.

Kevin G. Jamieson, Lalit Jain

CoRR, 2018

A Bandit Approach to Sequential Experimental Design with False Discovery Control.

Kevin G. Jamieson, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Firing Bandits: Optimizing Crowdfunding.

Lalit Jain, Kevin G. Jamieson

Proceedings of the 35th International Conference on Machine Learning, 2018

The Landscape of Non-Convex Quadratic Feasibility.

Amanda Bower, Lalit Jain, Laura Balzano

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Deep Learning for Military Image Captioning.

Subrata Das, Lalit Jain, Arup Das

Proceedings of the 21st International Conference on Information Fusion, 2018

Adaptive Sampling for Coarse Ranking.

Sumeet Katariya, Lalit Jain, Nandana Sengupta, James Evans, Robert Nowak

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

NEXT: A system to easily connect crowdsourcing and adaptive data collection.

Scott Sievert, Daniel Ross, Lalit Jain, Kevin Jamieson, Robert Nowak, Robert Mankoff

Proceedings of the 16th Python in Science Conference 2017, 2017

Learning Low-Dimensional Metrics.

Blake Mason, Lalit Jain, Robert D. Nowak

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

If it ain't broke, don't fix it: Sparse metric repair.

Anna C. Gilbert, Lalit Jain

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Finite Sample Prediction and Recovery Bounds for Ordinal Embedding.

Lalit Jain, Kevin G. Jamieson, Robert D. Nowak

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning.

Kevin G. Jamieson, Lalit Jain, Chris Fernandez, Nicholas J. Glattard, Robert D. Nowak

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015