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A Second-order Bound with Excess Losses

A Second-order Bound with Excess Losses

10 February 2014
Pierre Gaillard
Gilles Stoltz
T. Erven
ArXivPDFHTML

Papers citing "A Second-order Bound with Excess Losses"

38 / 38 papers shown
Title
Random feature-based double Vovk-Azoury-Warmuth algorithm for online multi-kernel learning
Random feature-based double Vovk-Azoury-Warmuth algorithm for online multi-kernel learning
Dmitry B. Rokhlin
Olga V. Gurtovaya
53
0
0
25 Mar 2025
Forecasting time series with constraints
Forecasting time series with constraints
Nathan Doumèche
Francis Bach
Éloi Bedek
Gérard Biau
Claire Boyer
Y. Goude
AI4TS
45
0
0
14 Feb 2025
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel−-−Young Loss Perspective and Gap-Dependent Regret Analysis
Shinsaku Sakaue
Han Bao
Taira Tsuchiya
45
2
0
23 Jan 2025
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen
Jiatai Huang
Yan Dai
Longbo Huang
34
0
0
04 Oct 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
D. Tiapkin
Evgenii Chzhen
Gilles Stoltz
74
1
0
08 Jul 2024
A Simple and Adaptive Learning Rate for FTRL in Online Learning with
  Minimax Regret of $Θ(T^{2/3})$ and its Application to
  Best-of-Both-Worlds
A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of Θ(T2/3)Θ(T^{2/3})Θ(T2/3) and its Application to Best-of-Both-Worlds
Taira Tsuchiya
Shinji Ito
26
0
0
30 May 2024
Efficient Methods for Non-stationary Online Learning
Efficient Methods for Non-stationary Online Learning
Peng Zhao
Yan-Feng Xie
Lijun Zhang
Zhi-Hua Zhou
49
19
0
16 Sep 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
Christoph Dann
Chen-Yu Wei
Julian Zimmert
26
22
0
20 Feb 2023
Frugal day-ahead forecasting of multiple local electricity loads by
  aggregating adaptive models
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models
Guillaume Lambert
Bachir Hamrouche
Joseph de Vilmarest
AI4TS
26
3
0
16 Feb 2023
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
Emmanuel Esposito
Federico Fusco
Dirk van der Hoeven
Nicolò Cesa-Bianchi
24
14
0
09 Oct 2022
Adversarially Robust Multi-Armed Bandit Algorithm with
  Variance-Dependent Regret Bounds
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds
Shinji Ito
Taira Tsuchiya
Junya Honda
AAML
23
16
0
14 Jun 2022
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with
  Feedback Graphs
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs
Shinji Ito
Taira Tsuchiya
Junya Honda
35
24
0
02 Jun 2022
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with
  Feedback Graphs
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
Chloé Rouyer
Dirk van der Hoeven
Nicolò Cesa-Bianchi
Yevgeny Seldin
23
15
0
01 Jun 2022
Exploiting the Curvature of Feasible Sets for Faster Projection-Free
  Online Learning
Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning
Zakaria Mhammedi
23
8
0
23 May 2022
Adaptive Conformal Predictions for Time Series
Adaptive Conformal Predictions for Time Series
Margaux Zaffran
Aymeric Dieuleveut
Olivier Féron
Y. Goude
Julie Josse
AI4TS
44
129
0
15 Feb 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
Isotuning With Applications To Scale-Free Online Learning
Isotuning With Applications To Scale-Free Online Learning
Laurent Orseau
Marcus Hutter
21
5
0
29 Dec 2021
Expert Aggregation for Financial Forecasting
Expert Aggregation for Financial Forecasting
Carl Remlinger
M. Brière
C. Alasseur
Joseph Mikael
AI4TS
AIFin
32
5
0
25 Nov 2021
Hierarchical transfer learning with applications for electricity load
  forecasting
Hierarchical transfer learning with applications for electricity load forecasting
A. Antoniadis
Solenne Gaucher
Y. Goude
AI4TS
35
11
0
16 Nov 2021
On Optimal Robustness to Adversarial Corruption in Online Decision
  Problems
On Optimal Robustness to Adversarial Corruption in Online Decision Problems
Shinji Ito
42
22
0
22 Sep 2021
Low-Regret Active learning
Low-Regret Active learning
Cenk Baykal
Lucas Liebenwein
Dan Feldman
Daniela Rus
UQCV
41
3
0
06 Apr 2021
Online Strongly Convex Optimization with Unknown Delays
Online Strongly Convex Optimization with Unknown Delays
Yuanyu Wan
Wei-Wei Tu
Lijun Zhang
22
18
0
21 Mar 2021
CRPS Learning
CRPS Learning
Jonathan Berrisch
F. Ziel
50
25
0
01 Feb 2021
Adaptive Methods for Short-Term Electricity Load Forecasting During
  COVID-19 Lockdown in France
Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdown in France
David Obst
Joseph de Vilmarest
Y. Goude
16
70
0
14 Sep 2020
Dynamic Regret of Convex and Smooth Functions
Dynamic Regret of Convex and Smooth Functions
Peng Zhao
Yu-Jie Zhang
Lijun Zhang
Zhi-Hua Zhou
29
101
0
07 Jul 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
19
15
0
30 May 2019
Adaptive Regret of Convex and Smooth Functions
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang
Tie-Yan Liu
Zhi-Hua Zhou
ODL
29
45
0
26 Apr 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
Beating Stochastic and Adversarial Semi-bandits Optimally and
  Simultaneously
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
Julian Zimmert
Haipeng Luo
Chen-Yu Wei
11
79
0
25 Jan 2019
Online Aggregation of Unbounded Losses Using Shifting Experts with
  Confidence
Online Aggregation of Unbounded Losses Using Shifting Experts with Confidence
V. Výugin
V. Trunov
17
9
0
02 Aug 2018
More Adaptive Algorithms for Adversarial Bandits
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
25
180
0
10 Jan 2018
Refined Lower Bounds for Adversarial Bandits
Refined Lower Bounds for Adversarial Bandits
Sébastien Gerchinovitz
Tor Lattimore
AAML
25
58
0
24 May 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
32
37
0
20 May 2016
Second-order Quantile Methods for Experts and Combinatorial Games
Second-order Quantile Methods for Experts and Combinatorial Games
Wouter M. Koolen
T. Erven
32
101
0
27 Feb 2015
Achieving All with No Parameters: Adaptive NormalHedge
Achieving All with No Parameters: Adaptive NormalHedge
Haipeng Luo
Robert Schapire
ODL
31
18
0
20 Feb 2015
Optimal learning with Bernstein Online Aggregation
Optimal learning with Bernstein Online Aggregation
Olivier Wintenberger
FedML
39
75
0
04 Apr 2014
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