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. 1810.07778
  4. Cited By
Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert
  Advice

Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice

29 September 2018
Kunkun Pang
Mingzhi Dong
Yang Wu
Timothy M. Hospedales
ArXivPDFHTML

Papers citing "Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice"

7 / 7 papers shown
Title
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang
Xueying Zhan
Siyu Huang
OOD
93
0
0
17 Oct 2024
Tracking the Best Expert in Non-stationary Stochastic Environments
Tracking the Best Expert in Non-stationary Stochastic Environments
Chen-Yu Wei
Yi-Te Hong
Chi-Jen Lu
39
59
0
02 Dec 2017
Learning Active Learning from Data
Learning Active Learning from Data
Ksenia Konyushkova
Raphael Sznitman
Pascal Fua
55
303
0
09 Mar 2017
Can Active Learning Experience Be Transferred?
Can Active Learning Experience Be Transferred?
Hong-Min Chu
Hsuan-Tien Lin
43
30
0
02 Aug 2016
Non-stationary Stochastic Optimization
Non-stationary Stochastic Optimization
Omar Besbes
Y. Gur
A. Zeevi
163
431
0
20 Jul 2013
Contextual Bandit Algorithms with Supervised Learning Guarantees
Contextual Bandit Algorithms with Supervised Learning Guarantees
A. Beygelzimer
John Langford
Lihong Li
L. Reyzin
Robert Schapire
OffRL
189
324
0
22 Feb 2010
On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems
On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems
Aurélien Garivier
Eric Moulines
84
295
0
22 May 2008
1