Ferber, Aaron M

15 publications

AAAI 2025 Constraint-Aware Pareto Optimization for Tree-Structured Networks: Addressing Decarbonization Targets with Hydropower Expansion Marc Grimson, Zhongdi Qu, Yue Mao, Aaron M. Ferber, Felipe Siqueira Pacheco, Sebastian Heilpern, Hector Angarita, Alexander Flecker, Carla P. Gomes

AISTATS 2025 Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M Ferber, Yian Ma, Carla P Gomes, Chao Zhang

IJCAI 2025 Expanding Connected Components from Alternative Terminals: Global Optimization for Freshwater Fishes Under the UN's 30x30 Conservation Goal Yue Mao, Zhongdi Qu, Imanol Miqueleiz, Aaron M. Ferber, Sami Wolf, Marc Grimson, Sebastian Heilpern, Felipe Siqueira Pacheco, Alexander S. Flecker, Peter B. McIntyre, Carla P. Gomes

ICLR 2025 Learning to Explore and Exploit with GNNs for Unsupervised Combinatorial Optimization Utku Umur Acikalin, Aaron M Ferber, Carla P Gomes

ICML 2024 Contrastive Predict-and-Search for Mixed Integer Linear Programs Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

ICML 2024 GenCO: Generating Diverse Designs with Combinatorial Constraints Aaron M Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

NeurIPSW 2023 Contrastive Predict-and-Search for Mixed Integer Linear Programs Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

ICMLW 2023 Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information Arman Zharmagambetov, Brandon Amos, Aaron M Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICMLW 2023 Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information Arman Zharmagambetov, Brandon Amos, Aaron M Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICML 2023 Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

ICMLW 2023 Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

ICML 2023 SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems Aaron M Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian

ICMLW 2023 SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems Aaron M Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian

AAAI 2021 Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg

AAAI 2020 MIPaaL: Mixed Integer Program as a Layer Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe