mlsanityData to 7 Oct 2026

Generalized non-stationary bandits

arXiv 2102.00725 ↗First posted 1 Feb 2021stat.ML cs.LG math.STcited by 8

Not on the map. Why?

Abstract (arXiv)

In this paper, we study a non-stationary stochastic bandit problem, which generalizes the switching bandit problem. On top of the switching bandit problem (Case a), we are interested in three concrete examples: (b) the means of the arms are local polynomials, (c) the means of the arms are locally smooth, and (d) the gaps of the arms have a bounded number of inflexion points and where the highest arm mean cannot vary too much in a short range. These three settings are very different, but have in common the following: (i) the number of similarly-sized level sets of the logarithm of the gaps can be controlled, and (ii) the highest mean has a limited number of abrupt changes, and otherwise has limited variations. We propose a single algorithm in this general setting, that in particular solves in an efficient and unified way the four problems (a)-(d) mentioned.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 11 of its 31 references that are in the map. First posted on arXiv 1 Feb 2021.

Builds on

11 of 31 references.

References · 11

  1. 2018Learning to Optimize under Non-Stationaritycited by 85
  2. 2019Weighted Linear Bandits for Non-Stationary Environmentscited by 84
  3. 2019A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-freecited by 71
  4. 2018What Doubling Tricks Can and Can't Do for Multi-Armed Banditscited by 69
  5. 2017Rotting Banditscited by 57
  6. 2018Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Banditcited by 49
  7. 2017A Change-Detection based Framework for Piecewise-stationary Multi-Armed Bandit Problemcited by 48
  8. 2014Unimodal Bandits: Regret Lower Bounds and Optimal Algorithmscited by 36
  9. 2017Tracking the Best Expert in Non-stationary Stochastic Environmentscited by 35
  10. 2015Multi-armed Bandit Problem with Known Trendcited by 17
  11. 2016On the Whittle Index for Restless Multi-armed Hidden Markov Banditscited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3; 2025: 1; 2026: 1.

8 papers.