“There are some things which cannot be learned quickly, and time, which is all we have, must be paid heavily for their acquiring. They are the very simplest things, and because it takes a man’s life to know them the little new that each man gets from life is very costly and the only heritage he has to leave.” - Ernest Hemingway (More…)
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Stochastic Combinatorial Optimization
Stochastic Combinatorial Optimization # Stochastic Combinatorial Optimization addresses CO problems where some parameters are random or uncertain, requiring robust or adaptive solutions that perform well under uncertainty. Recent Literature # Robust Combinatorial Optimization with Locally Predictable Uncertainty ICLR, 2023. paper Haozhe Sun, Shaoyu Wang, Jiaqi Ma, Chen Gong, Chen Tian Learning Robust Policies for Combinatorial Optimization ICML, 2022. paper, code Ankit Anupam, Joon Oh, Jure Leskovec Stochastic Combinatorial Optimization with Oracle Subsampling NeurIPS, 2021. paper
Travelling Salesman Problem (TSP)
Travelling Salesman Problem (TSP) # The Travelling Salesman Problem is one of the most famous NP-hard optimization problems, with extensive research on neural and ML-based approaches. Recent Literature # Learning Combinatorial Optimization Algorithms over Graphs. NeurIPS, 2017. paper Dai, Hanjun and Khalil, Elias B and Zhang, Yuyu and Dilkina, Bistra and Song, Le Learning Heuristics for the TSP by Policy Gradient CPAIOR, 2018. paper, code Michel DeudonPierre CournutAlexandre Lacoste Attention, Learn to Solve Routing Problems! ICLR, 2019. paper
Useful resources for studying Algebraic and Analytic Number Theory
General # Elements of Number Theory by John Stillwell Elementary Number Theory: Primes, Congruences, and Secrets by William Stein MIT’s Theory of Numbers Berkeley’s Number Theory by Richard E Borcherds, 1998 Fields Medalist UCLA’s Introduction to Number Theory Algebraic Number Theory # Algebraic Number Theory, by J.S. Milne An Algebraic introduction to Number Theory by Kimball Martin Analytic Number Theory #
Vehicle Routing Problem (VRP)
Vehicle Routing Problem (VRP) # The Vehicle Routing Problem is about finding optimal routes for a fleet of vehicles to serve a set of customers, a fundamental problem in logistics and transportation. Recent Literature # Learning to Perform Local Rewriting for Combinatorial Optimization. NeurIPS, 2019. paper, code Chen, Xinyun and Tian, Yuandong. Deep Reinforcement Learning for the Electric Vehicle Routing Problem with Time Windows. Arxiv, 2020. paper Lin, Bo and Ghaddar, Bissan and Nathwani, Jatin.
Vertex Cover
Vertex Cover # The Vertex Cover problem seeks the smallest set of vertices such that every edge in the graph is incident to at least one vertex in the set. This is a fundamental NP-hard problem in graph theory. Recent Literature # Learning Vertex Cover via Reinforcement Learning ICLR, 2024. paper Kevin Kuo, Adeola Oscar Adeniyi, Henry Hoffmann ⭐NN-Baker: Neural Network-Guided Baker’s Algorithm for Vertex Cover NeurIPS, 2024. paper, code Jiale Ma and Wenzheng Pan and Yang Li and Junchi Yan