Optimization

Course, tutorial

Linear Programming

Convex Optimization

Combinatorial Optimization


Non-Convex

Paper

Survey

workshop

Competition

Paper

SAT

  • Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver? NIPS 20
  • Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach, ICLR 19
  • SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver, PMLR 19
  • Learning local search heuristics for boolean satisfiability, NIPS 19
  • G2SAT: Learning to Generate SAT Formulas, NIPS 19
  • Combinatorial optimization with graph convolutional networks and guided tree search, NIPS 18
  • Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective
  • Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning

Here’s the slides link corresponding to the 2018 Fall CMU videos:
https://www.stat.cmu.edu/~ryantibs/convexopt-F18/