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01/25/2023
Overcoming Prior Misspecification in Online Learning to Rank
The recent literature on online learning to rank (LTR) has established t...
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09/02/2020
Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)
This report describes the aggregation and anonymization process applied ...
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12/11/2018
Merge Double Thompson Sampling for Large Scale Online Ranker Evaluation
Online ranker evaluation is one of the key challenges in information ret...
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06/15/2018
BubbleRank: Safe Online Learning to Rerank
We study the problem of online learning to re-rank, where users provide ...
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03/07/2017
Online Learning to Rank in Stochastic Click Models
Online learning to rank is a core problem in information retrieval and m...
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01/09/2013
Bayesian Optimization in a Billion Dimensions via Random Embeddings
Bayesian optimization techniques have been successfully applied to robot...
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06/27/2012
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
This paper analyzes the problem of Gaussian process (GP) bandits with de...
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03/09/2012