research
∙
06/22/2023
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness
Limit order books are a fundamental and widespread market mechanism. Thi...
share
research
∙
06/08/2023
Ordinal Potential-based Player Rating
A two-player symmetric zero-sum game is transitive if for any pure strat...
research
∙
01/26/2023
First Order Methods for Geometric Optimization of Crystal Structures
The geometric optimization of crystal structures is a procedure widely u...
research
∙
09/16/2022
Model-based gym environments for limit order book trading
Within the mathematical finance literature there is a rich catalogue of ...
research
∙
07/07/2022
Market Making with Scaled Beta Policies
This paper introduces a new representation for the actions of a market m...
research
∙
10/28/2021
Trading via Selective Classification
A binary classifier that tries to predict if the price of an asset will ...
research
∙
06/04/2021
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures
Recently, Optimistic Multiplicative Weights Update (OMWU) was proven to ...
research
∙
06/02/2021
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
Nash equilibrium is a central concept in game theory. Several Nash solve...
research
∙
12/21/2020
Difference Rewards Policy Gradients
Policy gradient methods have become one of the most popular classes of a...
research
∙
11/03/2020
The Complexity of Gradient Descent: CLS = PPAD ∩ PLS
We study search problems that can be solved by performing Gradient Desce...
research
∙
10/06/2020
A faster algorithm for finding Tarski fixed points
Dang et al. have given an algorithm that can find a Tarski fixed point i...
research
∙
07/09/2020
A deep learning approach to identify unhealthy advertisements in street view images
While outdoor advertisements are common features within towns and cities...
research
∙
07/08/2020
A Natural Actor-Critic Algorithm with Downside Risk Constraints
Existing work on risk-sensitive reinforcement learning - both for symmet...
research
∙
03/03/2020
Robust Market Making via Adversarial Reinforcement Learning
We show that adversarial reinforcement learning (ARL) can be used to pro...
research
∙
02/27/2020
Tree Polymatrix Games are PPAD-hard
We prove that it is PPAD-hard to compute a Nash equilibrium in a tree po...
research
∙
02/21/2020
The Automated Inspection of Opaque Liquid Vaccines
In the pharmaceutical industry the screening of opaque vaccines containi...
research
∙
01/13/2020
One-Clock Priced Timed Games are PSPACE-hard
The main result of this paper is that computing the value of a one-clock...
research
∙
04/12/2019
Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT
Simultaneous Localisation and Mapping (SLAM) algorithms are expensive to...
research
∙
02/20/2019
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning
Recent years have seen the application of deep reinforcement learning te...
research
∙
11/09/2018
Unique End of Potential Line
This paper studies the complexity of problems in PPAD ∩ PLS that have un...
research
∙
09/13/2018
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning
In Multi-Agent Reinforcement Learning, independent cooperative learners ...
research
∙
06/18/2018
Beyond Local Nash Equilibria for Adversarial Networks
Save for some special cases, current training methods for Generative Adv...
research
∙
04/11/2018
Market Making via Reinforcement Learning
Market making is a fundamental trading problem in which an agent provide...
research
∙
04/10/2018
End of Potential Line
We introduce the problem EndOfPotentialLine and the corresponding comple...
research
∙
12/02/2017
GANGs: Generative Adversarial Network Games
Generative Adversarial Networks (GAN) have become one of the most succes...
research
∙
11/14/2017
Symmetric Decomposition of Asymmetric Games
We introduce new theoretical insights into two-population asymmetric gam...
research
∙
09/26/2017
Reachability Switching Games
In this paper, we study the problem of deciding the winner of reachabili...
research
∙
07/14/2017
