Lalit Jain
26 papers · 2015–2024 · 5 venues · across top CS/AI venues
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Machine Learning
(24)
Optimization & Theory
(19)
Mathematics & Optimization
(16)
Optimization
(16)
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(13)
Artificial Intelligence
(5)
Core Methods
(5)
Core AI
(4)
Reinforcement Learning
(2)
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experimental design
(8)
active learning
(7)
best arm identification
(6)
linear bandit
(6)
sample complexity
(6)
pure exploration
(5)
multi-armed bandit
(4)
stochastic optimization
(3)
combinatorial bandit
(3)
regret minimization
(3)
binary classification
(2)
ordinal embedding
(2)
adaptive experimental design
(2)
posterior sampling
(2)
adaptive sampling
(2)
convex optimization
(1)
image classification
(1)
interactive learning
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online learning
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regret analysis
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Papers
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
AISTATS 2024
Adaptive Experimentation When You Can't Experiment
NeurIPS 2024
Fair Active Learning in Low-Data Regimes
UAI 2024
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning
NeurIPS 2024
Nearly Minimax Optimal Submodular Maximization with Bandit Feedback
NeurIPS 2024
Optimal Exploration is no harder than Thompson Sampling
AISTATS 2024
Pessimistic Off-Policy Multi-Objective Optimization
AISTATS 2024
Experimental Designs for Heteroskedastic Variance
NeurIPS 2023
Active Learning with Safety Constraints
NeurIPS 2022
An Experimental Design Approach for Regret Minimization in Logistic Bandits
AAAI 2022
Instance-optimal PAC Algorithms for Contextual Bandits
NeurIPS 2022
Nearly Optimal Algorithms for Level Set Estimation
AISTATS 2022
Improved Algorithms for Agnostic Pool-based Active Classification
ICML 2021
Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
ICML 2021
Selective Sampling for Online Best-arm Identification
NeurIPS 2021
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
NeurIPS 2020
Finding All Ξ΅-Good Arms in Stochastic Bandits
NeurIPS 2020
Spectral Methods for Ranking with Scarce Data
UAI 2020
A New Perspective on Pool-Based Active Classification and False-Discovery Control
NeurIPS 2019
Sequential Experimental Design for Transductive Linear Bandits
NeurIPS 2019
A Bandit Approach to Sequential Experimental Design with False Discovery Control
NeurIPS 2018
Adaptive Sampling for Coarse Ranking
AISTATS 2018
Firing Bandits: Optimizing Crowdfunding
ICML 2018
Learning Low-Dimensional Metrics
NeurIPS 2017
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding
NeurIPS 2016
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
NeurIPS 2015