Lalit Jain
26 papers · 2015–2024 · 5 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (9) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (5) π Cross-Pollinator (13)
π
Cross-Pollinator
(13)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(35)
π¬
Deep Specialist
(12)
π
Keyword Champion
(8)
ποΈ
Keyword Collector
(109)
β‘
Prolific Year
(7)
π₯
Unstoppable
(10)
π
Trend Setter
π
Century Club
(26)
Conferences
NIPS (15)
AISTATS (5)
ICML (3)
UAI (2)
AAAI (1)
Top co-authors
Keywords
experimental design
(8)
sample complexity
(6)
best-arm identification
(6)
linear bandit
(6)
active learning
(6)
pure exploration
(5)
multi-armed bandit
(4)
stochastic optimization
(3)
regret minimization
(3)
combinatorial bandit
(3)
binary classification
(2)
ordinal embedding
(2)
adaptive experimental design
(2)
adaptive sampling
(2)
convex optimization
(1)
image classification
(1)
interactive learning
(1)
online learning
(1)
regret analysis
(1)
causal inference
(1)
Papers
Fair Active Learning in Low-Data Regimes
UAI 2024
Nearly Minimax Optimal Submodular Maximization with Bandit Feedback
NIPS 2024
Adaptive Experimentation When You Can't Experiment
NIPS 2024
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning
NIPS 2024
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
AISTATS 2024
Optimal Exploration is no harder than Thompson Sampling
AISTATS 2024
Pessimistic Off-Policy Multi-Objective Optimization
AISTATS 2024
Experimental Designs for Heteroskedastic Variance
NIPS 2023
Active Learning with Safety Constraints
NIPS 2022
Instance-optimal PAC Algorithms for Contextual Bandits
NIPS 2022
An Experimental Design Approach for Regret Minimization in Logistic Bandits
AAAI 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
NIPS 2021
Finding All $\epsilon$-Good Arms in Stochastic Bandits
NIPS 2020
Spectral Methods for Ranking with Scarce Data
UAI 2020
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
NIPS 2020
Sequential Experimental Design for Transductive Linear Bandits
NIPS 2019
A New Perspective on Pool-Based Active Classification and False-Discovery Control
NIPS 2019
Firing Bandits: Optimizing Crowdfunding
ICML 2018
A Bandit Approach to Sequential Experimental Design with False Discovery Control
NIPS 2018
Adaptive Sampling for Coarse Ranking
AISTATS 2018
Learning Low-Dimensional Metrics
NIPS 2017
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding
NIPS 2016
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
NIPS 2015