ICML 2024 "combinatorial optimization" Papers
18 papers found
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner
A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
Guyard Theo, Cédric Herzet, Clément Elvira et al.
Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS
Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani
Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better
Vicente Balmaseda, Ying Xu, Yixin Cao et al.
Contrastive Predict-and-Search for Mixed Integer Linear Programs
Taoan Huang, Aaron Ferber, Arman Zharmagambetov et al.
Ensemble Pruning for Out-of-distribution Generalization
Fengchun Qiao, Xi Peng
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Tong Xialiang, Mingxuan Yuan et al.
Federated Combinatorial Multi-Agent Multi-Armed Bandits
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
Fewer Truncations Improve Language Modeling
Hantian Ding, Zijian Wang, Giovanni Paolini et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem
Zhentao Tan, Yadong Mu
Learning to Remove Cuts in Integer Linear Programming
Pol Puigdemont, EFSTRATIOS PANTELEIMON SKOULAKIS, Grigorios Chrysos et al.
Measures of diversity and space-filling designs for categorical data
AstraZeneca Pharmaceutica, Emilio Domínguez-Sánchez, Merwan Barlier et al.
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng, Shibal Ibrahim, Kayhan Behdin et al.
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu et al.
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
Hyeonah Kim, Minsu Kim, Sungsoo Ahn et al.
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee et al.
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
Yufei Kuang, Jie Wang, Yuyan Zhou et al.