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← Optimization & Theory
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Optimization & Theory
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Sample Complexity
97 directly classified papers
Papers per year
2006: 1
2008: 2
2010: 2
2012: 1
2013: 1
2014: 1
2015: 2
2016: 4
2017: 3
2018: 6
2019: 9
2020: 14
2021: 13
2022: 9
2023: 11
2024: 14
2025: 4
Papers
On Oracle-Efficient PAC RL with Rich Observations
NIPS 2018
Query Complexity of Bayesian Private Learning
NIPS 2018
Data Amplification: A Unified and Competitive Approach to Property Estimation
NIPS 2018
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity
NIPS 2018
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights
NIPS 2018
Phase Transitions in the Pooled Data Problem
NIPS 2017
A Sample Complexity Measure with Applications to Learning Optimal Auctions
NIPS 2017
Optimal Sample Complexity of M-wise Data for Top-K Ranking
NIPS 2017
Adaptive Concentration Inequalities for Sequential Decision Problems
NIPS 2016
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators
NIPS 2016
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems
NIPS 2016
The Power of Adaptivity in Identifying Statistical Alternatives
NIPS 2016
Sample Complexity of Learning Mahalanobis Distance Metrics
NIPS 2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
NIPS 2015
Time--Data Tradeoffs by Aggressive Smoothing
NIPS 2014
More data speeds up training time in learning halfspaces over sparse vectors
NIPS 2013
Dimensionality Dependent PAC-Bayes Margin Bound
NIPS 2012
Tight Sample Complexity of Large-Margin Learning
NIPS 2010
Multi-View Active Learning in the Non-Realizable Case
NIPS 2010
Rademacher Complexity Bounds for Non-I.I.D. Processes
NIPS 2008
Risk Bounds for Randomized Sample Compressed Classifiers
NIPS 2008
Sample Complexity of Policy Search with Known Dynamics
NIPS 2006
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