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01/27/2023
Are Equivariant Equilibrium Approximators Beneficial?
Recently, remarkable progress has been made by approximating Nash equili...
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01/29/2022
A Context-Integrated Transformer-Based Neural Network for Auction Design
One of the central problems in auction design is developing an incentive...
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08/17/2021
Learning to Compute Approximate Nash Equilibrium for Normal-form Games
In this paper, we propose a general meta learning approach to computing ...
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04/19/2020
Role-Wise Data Augmentation for Knowledge Distillation
Knowledge Distillation (KD) is a common method for transferring the “kno...
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06/22/2019
Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning
This paper studies recommender systems with knowledge graphs, which can ...
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10/29/2018