“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…)
News #
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Posts #
Orienteering Problem (OP)
Orienteering Problem (OP) # The Orienteering Problem involves selecting a subset of locations to visit with profit maximization subject to distance constraints. Recent Literature # A reinforcement learning approach to the orienteering problem with time windows Computers & Operations Research, 2021. paper, code Ricardo Gama, Hugo L. Fernandes Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization ICML, 2023. paper Son, Jiwoo and Kim, Minsu and Kim, Hyeonah and Park, Jinkyoo
Portfolio Optimization (PortOpt)
Portfolio Optimization (PortOpt) # Portfolio Optimization is about selecting and managing assets to achieve financial goals. Machine learning is increasingly being applied to improve portfolio management strategies. Recent Literature # ⭐LinSATNet: The Positive Linear Satisfiability Neural Networks ICML, 2023. paper, code Runzhong Wang and Yunhao Zhang and Ziao Guo and Tianyi Chen and Xiaokang Yang and Junchi Yan Integrating prediction in mean-variance portfolio optimization Quantitative Finance, 2023. paper Butler, Andrew and Kwon, Roy H
Predict+Optimize
Predict+Optimize # Predict+Optimize (also called Decision-Focused Learning) integrates prediction and optimization into a unified framework, where predictions are optimized for decision quality rather than traditional accuracy metrics. Recent Literature # Predict then Optimize Operations Research, 2021. paper, code Adam Elmachtoub, Paul Grigas Decision-Focused Learning of Robust Predictive Models ICML, 2019. paper, code Adam N. Elmachtoub, Paul Grigas Optimization-Based Algorithms for Decision-Focused Evaluation ICML, 2021. paper, code Yochanan Kotary, Yehuda Navon, Atara Nowik, Yaron Lipman Decision-Focused Learning with Offline Data NeurIPS, 2022. paper, code
Quadratic Assignment Problem (QAP)
Quadratic Assignment Problem (QAP) # The Quadratic Assignment Problem is a classical NP-hard combinatorial optimization problem with applications in location theory and circuit design. Recent Literature # Revised Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks Arxiv, 2017. paper, code Nowak, Alex and Villar, Soledad and Bandeira, S. Afonso and Bruna, Joan ⭐Neural Graph Matching Network: Learning Lawler’s Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching. TPAMI, 2021. paper, code
Sorting & Ranking (Sort&Rank)
Sorting & Ranking (Sort&Rank) # Sorting and ranking problems involve learning to order elements according to some criteria, with applications in information retrieval and preference learning. Recent Literature # Ranking via sinkhorn propagation Arxiv, 2011. paper Ryan Prescott Adams, Richard S. Zemel Predict+optimise with ranking objectives: exhaustively learning linear functions IJCAI, 2019. paper Demirovic, Emir and Stuckey, Peter J. and Bailey, James and Chan, Jeffrey and Leckie, Christopher and Ramamohanarao, Kotagiri and Guns, Tias