Search Results for author: Weiran Shen

Found 6 papers, 1 papers with code

Learning to Persuade

no code implementations29 Sep 2021 Xiaodong Liu, Zhikang Fan, Xun Wang, Weiran Shen

Then we update the sender model to obtain an approximately optimal scheme using the receiver model.

Bayesian Nash Equilibrium in First-Price Auction with Discrete Value Distributions

1 code implementation22 Jun 2019 Weiran Shen, Zihe Wang, Song Zuo

Some of the previous results in the case of continuous value distributions do not apply to the case of discrete value distributions.

Computer Science and Game Theory

Learning to Clear the Market

no code implementations4 Jun 2019 Weiran Shen, Sébastien Lahaie, Renato Paes Leme

The problem of market clearing is to set a price for an item such that quantity demanded equals quantity supplied.

Incremental training of multi-generative adversarial networks

no code implementations ICLR 2019 Qi Tan, Pingzhong Tang, Ke Xu, Weiran Shen, Song Zuo

Generative neural networks map a standard, possibly distribution to a complex high-dimensional distribution, which represents the real world data set.

Automated Mechanism Design via Neural Networks

no code implementations9 May 2018 Weiran Shen, Pingzhong Tang, Song Zuo

We then apply our framework to a number of multi-item revenue optimal design settings, for a few of which the theoretically optimal mechanisms are unknown.

Optimal Vehicle Dispatching Schemes via Dynamic Pricing

no code implementations6 Jul 2017 Mengjing Chen, Weiran Shen, Pingzhong Tang, Song Zuo

To this end, we use a so-called "ironing" technique to convert the problem into an equivalent convex optimization one via a clean Markov decision process (MDP) formulation, where the states are the driver distributions and the decision variables are the prices for each pair of locations.

Cannot find the paper you are looking for? You can Submit a new open access paper.