ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2405.02881
  4. Cited By
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous
  Clients

FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients

5 May 2024
Zhuohua Li
Maoli Liu
J. C. Lui
    FedML
ArXivPDFHTML

Papers citing "FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients"

5 / 5 papers shown
Title
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li
Maoli Liu
Xiangxiang Dai
John C. S. Lui
25
0
0
03 Jan 2025
Efficient Explorative Key-term Selection Strategies for Conversational
  Contextual Bandits
Efficient Explorative Key-term Selection Strategies for Conversational Contextual Bandits
Zhiyong Wang
Xutong Liu
Shuai Li
John C. S. Lui
35
14
0
01 Mar 2023
Hierarchical Conversational Preference Elicitation with Bandit Feedback
Hierarchical Conversational Preference Elicitation with Bandit Feedback
Jinhang Zuo
Songwen Hu
Tong Yu
Shuai Li
Handong Zhao
Carlee Joe-Wong
27
9
0
06 Sep 2022
Asynchronous Upper Confidence Bound Algorithms for Federated Linear
  Bandits
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
Chuanhao Li
Hongning Wang
FedML
16
35
0
04 Oct 2021
Advances and Challenges in Conversational Recommender Systems: A Survey
Advances and Challenges in Conversational Recommender Systems: A Survey
Chongming Gao
Wenqiang Lei
Xiangnan He
Maarten de Rijke
Tat-Seng Chua
128
270
0
23 Jan 2021
1