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Iljoo Yoon

2 accepted papers

2021

Matrix encoding networks for neural combinatorial optimization

NeurIPS 2021poster

Machine Learning (ML) can help solve combinatorial optimization (CO) problems better. A popular approach is to use a neural net to compute on the parameters of a given CO problem and extract useful information that guides the search for good solutions. Many CO problems of practical importance can be…

2020

POMO: Policy Optimization with Multiple Optima for Reinforcement Learning

NeurIPS 2020poster

In neural combinatorial optimization (CO), reinforcement learning (RL) can turn a deep neural net into a fast, powerful heuristic solver of NP-hard problems. This approach has a great potential in practical applications because it allows near-optimal solutions to be found without expert guides armed…