4 papers
Deep Learning for Markov Chains: Lyapunov Functions, Poisson's Equation, and Stationary Distributions
Yanlin Qu, Jose Blanchet, Peter Glynn
Lyapunov functions are fundamental to establishing the stability of Markovian models, yet their construction typically demands substantial creativity and analytical effort. In this…
AI paradigm for solving differential equations: first-principles data generation and scale-dilation operator AI solver
Xiangshu Gong, Zhiqiang Xie, Xiaowei Jin +4
Many problems are governed by differential equations (DEs). Artificial intelligence (AI) is a new path for solving DEs. However, data is very scarce and existing AI solvers struggl…
Rubik's Cube Scrambling Requires at Least 26 Random Moves
Yanlin Qu, Tomas Rokicki, Hillary Yang
Scrambling the standard 3x3x3 Rubik's Cube corresponds to a random walk on a group containing approximately 43 quintillion elements. Viewing the random walk as a Markov chain, its…
Double Distributionally Robust Bid Shading for First Price Auctions
Yanlin Qu, Ravi Kant, Yan Chen +4
Bid shading has become a standard practice in the digital advertising industry, in which most auctions for advertising (ad) opportunities are now of first price type. Given an ad o…