ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2004.13465
  4. Cited By
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed
  Payoffs

Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs

International Joint Conference on Artificial Intelligence (IJCAI), 2020
28 April 2020
Bo Xue
Guanghui Wang
Yimu Wang
Lijun Zhang
ArXiv (abs)PDFHTML

Papers citing "Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs"

24 / 24 papers shown
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang
Yu Zhang
Peng Zhao
Zhi Zhou
416
4
0
01 Mar 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye
Yujia Jin
Alekh Agarwal
Tong Zhang
491
1
0
04 Feb 2025
Low-rank Matrix Bandits with Heavy-tailed Rewards
Low-rank Matrix Bandits with Heavy-tailed Rewards
Yue Kang
Cho-Jui Hsieh
T. C. Lee
327
5
0
26 Apr 2024
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed
  Rewards
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed RewardsNeural Information Processing Systems (NeurIPS), 2023
Bo Xue
Yimu Wang
Yuanyu Wan
Jinfeng Yi
Lijun Zhang
267
12
0
28 Oct 2023
Towards Robust Offline Reinforcement Learning under Diverse Data
  Corruption
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang
Han Zhong
Jiawei Xu
Amy Zhang
Chong Zhang
Lei Han
Tong Zhang
OffRLOnRL
501
28
0
19 Oct 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function
  Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret BoundsNeural Information Processing Systems (NeurIPS), 2023
Jiayi Huang
Han Zhong
Liwei Wang
Lin F. Yang
465
14
0
12 Jun 2023
Variance-aware robust reinforcement learning with linear function
  approximation under heavy-tailed rewards
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards
Xiang Li
Qiang Sun
307
10
0
09 Mar 2023
GraphSR: A Data Augmentation Algorithm for Imbalanced Node
  Classification
GraphSR: A Data Augmentation Algorithm for Imbalanced Node ClassificationAAAI Conference on Artificial Intelligence (AAAI), 2023
Mengting Zhou
Zhiguo Gong
241
47
0
24 Feb 2023
Quantum Heavy-tailed Bandits
Quantum Heavy-tailed Bandits
Yulian Wu
Chaowen Guan
Vaneet Aggarwal
Haiyan Zhao
280
6
0
23 Jan 2023
Graph Convolutional Network for Multi-Target Multi-Camera Vehicle
  Tracking
Graph Convolutional Network for Multi-Target Multi-Camera Vehicle Tracking
Elena Luna
Juan Carlos San Miguel
J. Sanchez
Marcos Escudero-Viñolo
212
7
0
28 Nov 2022
The Devil is in the Conflict: Disentangled Information Graph Neural
  Networks for Fraud Detection
The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud DetectionIndustrial Conference on Data Mining (IDM), 2022
Zhixun Li
Dingshuo Chen
Qiang Liu
Shu Wu
AAML
284
26
0
22 Oct 2022
Rethinking Efficiency and Redundancy in Training Large-scale Graphs
Rethinking Efficiency and Redundancy in Training Large-scale Graphs
Xin Liu
Xunbin Xiong
Yurui Lai
Runzhen Xue
Shirui Pan
Xiaochun Ye
Xiaochun Ye
303
1
0
02 Sep 2022
NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction
NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction
Xueyan Yin
Fei Li
Yanming Shen
Heng Qi
Baocai Yin
GNNAI4TS
153
11
0
04 Jul 2022
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node ClassificationInternational Conference on Machine Learning (ICML), 2022
Jae-gyun Song
Joonhyung Park
Eunho Yang
209
86
0
26 Jun 2022
Knowledge Learning with Crowdsourcing: A Brief Review and Systematic
  Perspective
Knowledge Learning with Crowdsourcing: A Brief Review and Systematic PerspectiveIEEE/CAA Journal of Automatica Sinica (JCAS), 2022
Jing Zhang
HAI
169
50
0
19 Jun 2022
Stochastic Contextual Dueling Bandits under Linear Stochastic
  Transitivity Models
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity ModelsInternational Conference on Machine Learning (ICML), 2022
Viktor Bengs
Aadirupa Saha
Eyke Hüllermeier
288
30
0
09 Feb 2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed
  Bandits
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed BanditsInternational Conference on Machine Learning (ICML), 2022
Jiatai Huang
Yan Dai
Longbo Huang
370
24
0
28 Jan 2022
Graph Decipher: A transparent dual-attention graph neural network to
  understand the message-passing mechanism for the node classification
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classificationInternational Journal of Intelligent Systems (IJIS), 2022
Yan Pang
Chao Liu
GNN
199
15
0
04 Jan 2022
Imbalanced Graph Classification via Graph-of-Graph Neural Networks
Imbalanced Graph Classification via Graph-of-Graph Neural Networks
Yu Wang
Yuying Zhao
Neil Shah
Hanyu Wang
396
69
0
01 Dec 2021
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits
  with Super Heavy-Tailed Payoffs
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Han Zhong
Jiayi Huang
Lin F. Yang
Liwei Wang
195
11
0
26 Oct 2021
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Tianyi Yao
Minjie Wang
Genevera I. Allen
292
1
0
22 Oct 2021
Tackling the Imbalance for GNNs
Tackling the Imbalance for GNNs
Rui Wang
Weixuan Xiong
Qing-Hu Hou
Ou Wu
250
8
0
17 Oct 2021
Topology-Imbalance Learning for Semi-Supervised Node Classification
Topology-Imbalance Learning for Semi-Supervised Node ClassificationNeural Information Processing Systems (NeurIPS), 2021
Deli Chen
Yankai Lin
Guangxiang Zhao
Xuancheng Ren
Peng Li
Jie Zhou
Xu Sun
302
121
0
08 Oct 2021
Graph Classification by Mixture of Diverse Experts
Graph Classification by Mixture of Diverse Experts
Fenyu Hu
Liping Wang
Shu Wu
Liang Wang
Tieniu Tan
288
20
0
29 Mar 2021
1
Page 1 of 1