“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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Posts #
Influence Maximization
Influence Maximization # Influence Maximization seeks to select a set of influential nodes in a network to maximize information spread. It has applications in social network marketing. Recent Literature # Learning Heuristics over Large Graphs via Deep Reinforcement Learning. NeurIPS, 2020. paper Mittal, Akash and Dhawan, Anuj and Manchanda, Sahil and Medya, Sourav and Ranu, Sayan and Singh, Ambuj. Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. ICML, 2021. paper
Job Shop Scheduling Problem (JSSP)
Job Shop Scheduling Problem (JSSP) # The Job Shop Scheduling Problem is a classic combinatorial optimization problem where jobs must be scheduled on machines with precedence constraints. Recent Literature # Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network Transactions on Industrial Informatics, 2019. journal Chun-Cheng Lin, Der-Jiunn Deng, Yen-Ling Chih, Hsin-Ting Chiu Multi-Agent Reinforcement Learning for Job Shop Scheduling in Flexible Manufacturing Systems International Conference on Artificial Intelligence for Industries (AI4I), 2019. paper
Knapsack Problem
Knapsack Problem # The Knapsack Problem is a classic optimization problem where items with weights and values must be selected to maximize total value while respecting a weight constraint. Recent Literature # A Novel Method to Solve Neural Knapsack Problems ICML, 2021. paper, code Li Duanshun and Liu Jing and Lee Dongeun and Seyedmazloom Ali and Kaushik Giridhar and Lee Kookjin and Park Noseong DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization NeurIPS, 2023. paper, code
Max Clique
Max Clique # The Maximum Clique problem seeks the largest clique in a graph. A clique is a subset of vertices where every vertex is connected to every other vertex. Recent Literature # Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem NeurIPS, 2022. paper, code Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf Variational Annealing on Graphs for Combinatorial Optimization NeurIPS, 2023. paper, code Sanokowski, Sebastian and Berghammer, Wilhelm Franz and Hochreiter, Sepp and Lehner, Sebastian
Maximal Common Subgraph (MCS)
Maximal Common Subgraph (MCS) # The Maximal Common Subgraph problem finds the largest subgraph common to two graphs, with applications in molecular matching and pattern discovery. Recent Literature # Fast Detection of Maximum Common Subgraph via Deep Q-Learning. Arxiv, 2020. paper Bai, Yunsheng and Xu, Derek and Wang, Alex and Gu, Ken and Wu, Xueqing and Marinovic, Agustin and Ro, Christopher and Sun, Yizhou and Wang, Wei.