This paper examines the convergence of no-regret learning in Cournot games with continuous actions. Cournot games are the essential model for many socio-economic systems, where players compete by strategically setting their output quantity. We assume that players do not have full information of the game and thus cannot pre-compute a Nash equilibrium. Two types of feedback are considered: one is bandit feedback and the other is gradient feedback. To study the convergence of the induced sequence o...
Quantitative mode stability for the wave equation on the Kerr-Newman spacetime
Risk-Aware Objective-Based Forecasting in Inertia Management
Chainalysis: Geography of Cryptocurrency 2023
Periodicity in Cryptocurrency Volatility and Liquidity
Impact of Geometric Uncertainty on the Computation of Abdominal Aortic Aneurysm Wall Strain
Simulation-based Bayesian inference with ameliorative learned summary statistics -- Part I