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Black-Box Reductions for Parameter-free Online Learning in Banach Spaces
v1v2 (latest)

Black-Box Reductions for Parameter-free Online Learning in Banach Spaces

17 February 2018
Ashok Cutkosky
Francesco Orabona
ArXiv (abs)PDFHTML

Papers citing "Black-Box Reductions for Parameter-free Online Learning in Banach Spaces"

8 / 58 papers shown
Title
Anytime Online-to-Batch Conversions, Optimism, and Acceleration
Anytime Online-to-Batch Conversions, Optimism, and Acceleration
Ashok Cutkosky
63
7
0
03 Mar 2019
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
Zakaria Mhammedi
Wouter M. Koolen
T. Erven
97
36
0
27 Feb 2019
Combining Online Learning Guarantees
Combining Online Learning Guarantees
Ashok Cutkosky
80
27
0
24 Feb 2019
Adaptive scale-invariant online algorithms for learning linear models
Adaptive scale-invariant online algorithms for learning linear models
Michal Kempka
W. Kotłowski
Manfred K. Warmuth
78
31
0
20 Feb 2019
Improved Path-length Regret Bounds for Bandits
Improved Path-length Regret Bounds for Bandits
Sébastien Bubeck
Yuanzhi Li
Haipeng Luo
Chen-Yu Wei
121
46
0
29 Jan 2019
Online Adaptive Methods, Universality and Acceleration
Online Adaptive Methods, Universality and Acceleration
Kfir Y. Levy
A. Yurtsever
Volkan Cevher
ODL
76
93
0
08 Sep 2018
On the Convergence of Stochastic Gradient Descent with Adaptive
  Stepsizes
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyun Li
Francesco Orabona
89
299
0
21 May 2018
Online Learning: Sufficient Statistics and the Burkholder Method
Online Learning: Sufficient Statistics and the Burkholder Method
Dylan J. Foster
Alexander Rakhlin
Karthik Sridharan
63
27
0
20 Mar 2018
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