Online Learning with Predictable Sequences

The nonstochastic multiarmed bandit problem

P. Auer, N. Cesa-Bianchi, Y. Freund, and R. E. Schapire · 2003

Earlier work this paper cites.

Mirror descent and nonlinear projected subgradient methods for convex optimization

A. Beck and M. Teboulle · 2003

Earlier work this paper cites.

Efficient algorithms for online decision problems

A. Kalai and S. Vempala · 2005

Earlier work this paper cites.

Prediction, Learning, and Games

N. Cesa-Bianchi and G. Lugosi · 2006

Earlier work this paper cites.

Adaptive online gradient descent

P.L. Bartlett, E. Hazan, and A. Rakhlin · 2007

Earlier work this paper cites.

Improved second-order bounds for prediction with expert advice

N. Cesa-Bianchi, Y. Mansour, and G. Stoltz · 2007

Earlier work this paper cites.

Competing in the dark: An efficient algorithm for bandit linear optimization

J. Abernethy, E. Hazan, and A. Rakhlin · 2008

Cited alongside, same era.

Interior-point methods for optimization

A.S. Nemirovski and M.J. Todd · 2008

Cited alongside, same era.

Lecture notes on online learning, 2008

A. Rakhlin · 2008

Cited alongside, same era.

Beating the adaptive bandit with high probability

J. Abernethy and A. Rakhlin · 2009

Cited alongside, same era.

Better algorithms for benign bandits

E. Hazan and S. Kale · 2009

Cited alongside, same era.

Extracting certainty from uncertainty: Regret bounded by variation in costs

E. Hazan and S. Kale · 2010

Cited alongside, same era.

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: Stochastic, constrained, and smoothed adversaries

Original

A. Rakhlin, K. Sridharan, and A. Tewari · 2011

Later among the works it cites.

Interior-point methods for full-information and bandit online learning

J.D. Abernethy, E. Hazan, and A. Rakhlin · 2012

Closest in time.

Online optimization with gradual variations

C.-K. Chiang, T. Yang, C.-J. Lee, M. Mahdavi, C.-J. Lu, R. Jin, and S. Zhu · 2012

Closest in time.

Relax and localize: From value to algorithms

Original

A. Rakhlin, O. Shamir, and K. Sridharan · 2012

Closest in time.