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Second-order Quantile Methods for Experts and Combinatorial Games

Second-order Quantile Methods for Experts and Combinatorial Games

27 February 2015
Wouter M. Koolen
T. Erven
ArXivPDFHTML

Papers citing "Second-order Quantile Methods for Experts and Combinatorial Games"

23 / 23 papers shown
Title
Near Optimal Memory-Regret Tradeoff for Online Learning
Near Optimal Memory-Regret Tradeoff for Online Learning
Binghui Peng
A. Rubinstein
CLL
34
10
0
03 Mar 2023
Optimal Prediction Using Expert Advice and Randomized Littlestone
  Dimension
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
Yuval Filmus
Steve Hanneke
Idan Mehalel
Shay Moran
31
11
0
27 Feb 2023
Unconstrained Dynamic Regret via Sparse Coding
Unconstrained Dynamic Regret via Sparse Coding
Zhiyu Zhang
Ashok Cutkosky
I. Paschalidis
39
7
0
31 Jan 2023
Modifying Squint for Prediction with Expert Advice in a Changing
  Environment
Modifying Squint for Prediction with Expert Advice in a Changing Environment
Thom Neuteboom
T. Erven
24
1
0
14 Sep 2022
Bandit Sampling for Multiplex Networks
Bandit Sampling for Multiplex Networks
Cenk Baykal
Vamsi K. Potluru
Sameena Shah
Manuela Veloso
11
2
0
08 Feb 2022
Parameter-free Online Linear Optimization with Side Information via
  Universal Coin Betting
Parameter-free Online Linear Optimization with Side Information via Universal Coin Betting
Jeonghun Ryu
Alankrita Bhatt
Young-Han Kim
26
1
0
04 Feb 2022
$k\texttt{-experts}$ -- Online Policies and Fundamental Limits
k-expertsk\texttt{-experts}k-experts -- Online Policies and Fundamental Limits
S. Mukhopadhyay
Sourav Sahoo
Abhishek Sinha
OffRL
40
8
0
15 Oct 2021
Efficient First-Order Contextual Bandits: Prediction, Allocation, and
  Triangular Discrimination
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination
Dylan J. Foster
A. Krishnamurthy
48
43
0
05 Jul 2021
Low-Regret Active learning
Low-Regret Active learning
Cenk Baykal
Lucas Liebenwein
Dan Feldman
Daniela Rus
UQCV
41
3
0
06 Apr 2021
CRPS Learning
CRPS Learning
Jonathan Berrisch
F. Ziel
48
25
0
01 Feb 2021
Locally-Adaptive Nonparametric Online Learning
Locally-Adaptive Nonparametric Online Learning
Ilja Kuzborskij
Nicolò Cesa-Bianchi
15
5
0
05 Feb 2020
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive
  Regret of Convex Functions
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions
Lijun Zhang
G. Wang
Wei-Wei Tu
Zhi-Hua Zhou
ODL
23
18
0
26 Jun 2019
Model selection for contextual bandits
Model selection for contextual bandits
Dylan J. Foster
A. Krishnamurthy
Haipeng Luo
OffRL
34
90
0
03 Jun 2019
Equipping Experts/Bandits with Long-term Memory
Equipping Experts/Bandits with Long-term Memory
Kai Zheng
Haipeng Luo
Ilias Diakonikolas
Liwei Wang
OffRL
14
15
0
30 May 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
23
34
0
27 Feb 2019
Mixture Martingales Revisited with Applications to Sequential Tests and
  Confidence Intervals
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals
E. Kaufmann
Wouter M. Koolen
21
117
0
28 Nov 2018
Best of many worlds: Robust model selection for online supervised
  learning
Best of many worlds: Robust model selection for online supervised learning
Vidya Muthukumar
Mitas Ray
A. Sahai
Peter L. Bartlett
OffRL
40
8
0
22 May 2018
Online Learning: A Comprehensive Survey
Online Learning: A Comprehensive Survey
Guosheng Lin
Doyen Sahoo
Jing Lu
P. Zhao
OffRL
31
634
0
08 Feb 2018
More Adaptive Algorithms for Adversarial Bandits
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
22
180
0
10 Jan 2018
Parameter-free online learning via model selection
Parameter-free online learning via model selection
Dylan J. Foster
Satyen Kale
M. Mohri
Karthik Sridharan
32
59
0
30 Dec 2017
Tight Lower Bounds for Multiplicative Weights Algorithmic Families
Tight Lower Bounds for Multiplicative Weights Algorithmic Families
N. Gravin
Yuval Peres
Balasubramanian Sivan
19
16
0
11 Jul 2016
Combining Adversarial Guarantees and Stochastic Fast Rates in Online
  Learning
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning
Wouter M. Koolen
Peter Grünwald
T. Erven
29
37
0
20 May 2016
Optimal learning with Bernstein Online Aggregation
Optimal learning with Bernstein Online Aggregation
Olivier Wintenberger
FedML
37
75
0
04 Apr 2014
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