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Aaron M. Ferber
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2020 – today
- 2024
- [i10]Weimin Huang, Taoan Huang, Aaron M. Ferber, Bistra Dilkina:
Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP Methods. CoRR abs/2406.06954 (2024) - 2023
- [c10]Taoan Huang
, Aaron M. Ferber
, Yuandong Tian
, Bistra Dilkina
, Benoit Steiner
:
Local Branching Relaxation Heuristics for Integer Linear Programs. CPAIOR 2023: 96-113 - [c9]Aaron M. Ferber, Emily Griffin, Bistra Dilkina, Burcu B. Keskin, Meredith Gore:
Predicting Wildlife Trafficking Routes with Differentiable Shortest Paths. CPAIOR 2023: 460-476 - [c8]Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian:
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. ICML 2023: 10034-10052 - [c7]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. ICML 2023: 13869-13890 - [c6]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. NeurIPS 2023 - [i9]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. CoRR abs/2302.01578 (2023) - [i8]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. CoRR abs/2307.08964 (2023) - [i7]Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian:
GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. CoRR abs/2310.02442 (2023) - [i6]Augustin Parjadis, Quentin Cappart, Bistra Dilkina, Aaron M. Ferber, Louis-Martin Rousseau:
Learning Lagrangian Multipliers for the Travelling Salesman Problem. CoRR abs/2312.14836 (2023) - 2022
- [c5]Aaron M. Ferber
, Jialin Song
, Bistra Dilkina
, Yisong Yue
:
Learning Pseudo-Backdoors for Mixed Integer Programs. CPAIOR 2022: 91-102 - [i5]Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian:
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems. CoRR abs/2210.12547 (2022) - [i4]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Local Branching Relaxation Heuristics for Integer Linear Programs. CoRR abs/2212.08183 (2022) - 2021
- [c4]Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg:
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. AAAI 2021: 7610-7619 - [c3]Aaron M. Ferber, Jialin Song, Bistra Dilkina, Yisong Yue:
Learning Pseudo-Backdoors for Mixed Integer Programs. SOCS 2021: 170-172 - [i3]Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg:
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. CoRR abs/2101.04108 (2021) - [i2]Aaron M. Ferber, Jialin Song, Bistra Dilkina, Yisong Yue:
Learning Pseudo-Backdoors for Mixed Integer Programs. CoRR abs/2106.05080 (2021) - 2020
- [j1]Alice Paul, Daniel Freund
, Aaron M. Ferber
, David B. Shmoys
, David P. Williamson:
Budgeted Prize-Collecting Traveling Salesman and Minimum Spanning Tree Problems. Math. Oper. Res. 45(2): 576-590 (2020) - [c2]Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe:
MIPaaL: Mixed Integer Program as a Layer. AAAI 2020: 1504-1511
2010 – 2019
- 2019
- [i1]Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe:
MIPaaL: Mixed Integer Program as a Layer. CoRR abs/1907.05912 (2019) - 2017
- [c1]Alice Paul, Daniel Freund
, Aaron M. Ferber
, David B. Shmoys
, David P. Williamson:
Prize-Collecting TSP with a Budget Constraint. ESA 2017: 62:1-62:14
Coauthor Index
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