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08/19/2021
Mixture-Based Correction for Position and Trust Bias in Counterfactual Learning to Rank
In counterfactual learning to rank (CLTR) user interactions are used as ...
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04/28/2021
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization
As the size and complexity of models and datasets grow, so does the need...
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05/25/2020
Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank
Unbiased CLTR requires click propensities to compensate for the differen...
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02/02/2020
Safe Exploration for Optimizing Contextual Bandits
Contextual bandit problems are a natural fit for many information retrie...
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03/07/2019
ViTOR: Learning to Rank Webpages Based on Visual Features
The visual appearance of a webpage carries valuable information about it...
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12/12/2018
Online Learning to Rank with List-level Feedback for Image Filtering
Online learning to rank (OLTR) via implicit feedback has been extensivel...
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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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05/09/2018
A Click Sequence Model for Web Search
Getting a better understanding of user behavior is important for advanci...
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09/15/2017
