UNSAT Solver Synthesis via Monte Carlo Forest Search

1 code implementation • 22 Nov 2022 • Chris Cameron, Jason Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown

We introduce Monte Carlo Forest Search (MCFS), a class of reinforcement learning (RL) algorithms for learning policies in {tree MDPs}, for which policy execution involves traversing an exponential-sized tree.

reinforcement-learning Reinforcement Learning (RL)

Matching Papers and Reviewers at Large Conferences

1 code implementation • 24 Feb 2022 • Kevin Leyton-Brown, Mausam, Yatin Nandwani, Hedayat Zarkoob, Chris Cameron, Neil Newman, Dinesh Raghu

Peer-reviewed conferences, the main publication venues in CS, rely critically on matching highly qualified reviewers for each paper.

The Perils of Learning Before Optimizing

no code implementations • 18 Jun 2021 • Chris Cameron, Jason Hartford, Taylor Lundy, Kevin Leyton-Brown

Typically, learning the prediction model used to generate the optimization problem and solving that problem are performed in two separate stages.

Stochastic Optimization