Online Learning: Stochastic and Constrained Adversaries

Statistical decision theory and Bayesian analysis

J.O. Berger · 1985

Earlier work this paper cites.

Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm

N. Littlestone · 1988

Earlier work this paper cites.

Probability in Banach Spaces

M. Ledoux and M. Talagrand · 1991

Earlier work this paper cites.

Weak Convergence and Empirical Processes : With Applications to Statistics

A. W. Van Der Vaart and J. A. Wellner · 1996

Earlier work this paper cites.

Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time

D. A. Spielman and S. H. Teng · 2004

Earlier work this paper cites.

On the complexity of linear prediction: Risk bounds, margin bounds, and regularization

S.M. Kakade, K. Sridharan, and A. Tewari · 2008

Cited alongside, same era.

A stochastic view of optimal regret through minimax duality

J. Abernethy, A. Agarwal, P. Bartlett, and A. Rakhlin · 2009

Cited alongside, same era.

Agnostic online learning

S. Ben-David, D. Pal, and S. Shalev-Shwartz · 2009

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Better algorithms for benign bandits

E. Hazan and S. Kale · 2009

Cited alongside, same era.

Hybrid Stochastic-Adversarial On-line Learning

A. Lazaric and R. Munos · 2009

Cited alongside, same era.

Learning and Smoothed Analysis

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Later among the works it cites.

Online learning: Beyond regret

Original

A. Rakhlin, K. Sridharan, and A. Tewari · 2010

Later among the works it cites.

Online learning: Random averages, combinatorial parameters, and learnability

Original

A. Rakhlin, K. Sridharan, and A. Tewari · 2010

Later among the works it cites.

Online learning: Random averages, combinatorial parameters, and learnability

A. Rakhlin, K. Sridharan, and A. Tewari · 2010

Later among the works it cites.

Learnability, stability and uniform convergence

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Later among the works it cites.