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