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04/26/2023
Learning to Bid in Repeated First-Price Auctions with Budgets
Budget management strategies in repeated auctions have received growing ...
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06/07/2022
False Consensus, Information Theory, and Prediction Markets
Our main result shows that when agents' private information about an eve...
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10/03/2021
Information Elicitation Meets Clustering
In the setting where we want to aggregate people's subjective evaluation...
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09/22/2021
Eliciting Thinking Hierarchy without Prior
A key challenge in crowdsourcing is that majority may make systematic mi...
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07/21/2021
Truthful Information Elicitation from Hybrid Crowds
Suppose a decision maker wants to predict weather tomorrow by eliciting ...
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07/17/2021
BONUS! Maximizing Surprise
Multi-round competitions often double or triple the points awarded in th...
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06/05/2021
SURPRISE! and When to Schedule It
Information flow measures, over the duration of a game, the audience's b...
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06/02/2021
Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels
In many classification tasks, the ground truth is either noisy or subjec...
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03/03/2021
Optimizing Multi-task Peer Prediction
In the setting where we ask participants multiple similar possibly subje...
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02/24/2021
Equal Affection or Random Selection: the Quality of Subjective Feedback from a Group Perspective
In the setting where a group of agents is asked a single subjective mult...
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07/14/2020
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
Fusing data from multiple modalities provides more information to train ...
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11/01/2019
Dominantly Truthful Multi-task Peer Prediction with a Constant Number of Tasks
In the setting where participants are asked multiple similar possibly su...
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10/31/2019
Outsourcing Computation: the Minimal Refereed Mechanism
We consider a setting where a verifier with limited computation power de...
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09/08/2019
L_DMI: An Information-theoretic Noise-robust Loss Function
Accurately annotating large scale dataset is notoriously expensive both ...
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05/31/2019
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
Eliciting labels from crowds is a potential way to obtain large labeled ...
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03/18/2019
Securely Trading Unverifiable Information without Trust
In future, information may become one of the most important assets in ec...
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02/24/2018
Water from Two Rocks: Maximizing the Mutual Information
Our goal is to forecast ground truth Y using two sources of information ...
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02/22/2018