5 citations · 8 across the 4 of their papers we have counts for
3 papers · 1 filter
Accelerate Neural Subspace-Based Reduced-Order Solver of Deformable Simulation by Lipschitz Optimization
Aoran Lyu, Shixian Zhao, Chuhua Xian +3
Reduced-order simulation is an emerging method for accelerating physical simulations with high DOFs, and recently developed neural-network-based methods with nonlinear subspaces ha…
Offline Reinforcement Learning for Optimizing Production Bidding Policies
Dmytro Korenkevych, Frank Cheng, Artsiom Balakir +5
The online advertising market, with its thousands of auctions run per second, presents a daunting challenge for advertisers who wish to optimize their spend under a budget constrai…
Periodic-GP: Learning Periodic World with Gaussian Process Bandits
Hengrui Cai, Zhihao Cen, Ling Leng +1
We consider the sequential decision optimization on the periodic environment, that occurs in a wide variety of real-world applications when the data involves seasonality, such as t…