255 citations · 2.4k across the 127 of their papers we have counts for
8 papers · 2 filters
Stochastic Low-Rank Bandits
Branislav Kveton, Csaba Szepesvari, Anup Rao +3
Many problems in computer vision and recommender systems involve low-rank matrices. In this work, we study the problem of finding the maximum entry of a stochastic low-rank matrix…
Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging
Chandrashekar Lakshminarayanan, Csaba Szepesvári
We consider -dimensional linear stochastic approximation algorithms (LSAs) with a constant step-size and the so called Polyak-Ruppert (PR) averaging of iterates. LSAs are widely…
A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds
Pooria Joulani, András György, Csaba Szepesvári
Recently, much work has been done on extending the scope of online learning and incremental stochastic optimization algorithms. In this paper we contribute to this effort in two wa…
Crowdsourcing with Sparsely Interacting Workers
Yao Ma, Alex Olshevsky, Venkatesh Saligrama +1
We consider estimation of worker skills from worker-task interaction data (with unknown labels) for the single-coin crowd-sourcing binary classification model in symmetric noise. W…
Structured Best Arm Identification with Fixed Confidence
Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári +1
We study the problem of identifying the best action among a set of possible options when the value of each action is given by a mapping from a number of noisy micro-observables in…
Bernoulli Rank- Bandits for Click Feedback
Sumeet Katariya, Branislav Kveton, Csaba Szepesvári +2
The probability that a user will click a search result depends both on its relevance and its position on the results page. The position based model explains this behavior by ascrib…