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ORCIDElias B. Khalil
Person information
- affiliation: University of Toronto, Department of Mechanical and Industrial Engineering, ON, Canada
- affiliation: Georgia Institute of Technology, College of Computing, Atlanta, GA, USA
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2020 – today
- 2024
[j7]Bo Tang
, Elias B. Khalil:
PyEPO: a PyTorch-based end-to-end predict-then-optimize library for linear and integer programming. Math. Program. Comput. 16(3): 297-335 (2024)- [j6]Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias Boutros Khalil:
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations. Trans. Mach. Learn. Res. 2024 (2024) - [c34]Rahul Patel, Elias B. Khalil:
LEO: Learning Efficient Orderings for Multiobjective Binary Decision Diagrams. CPAIOR (2) 2024: 83-110 - [c33]Bo Tang, Elias B. Khalil:
CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs. CPAIOR (2) 2024: 193-210 - [c32]Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias Boutros Khalil:
Neur2RO: Neural Two-Stage Robust Optimization. ICLR 2024 - [c31]Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias B. Khalil:
Neur2BiLO: Neural Bilevel Optimization. NeurIPS 2024 - [i27]Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias B. Khalil:
Neur2BiLO: Neural Bilevel Optimization. CoRR abs/2402.02552 (2024) - [i26]Rahul Patel, Elias B. Khalil, David Bergman:
MORBDD: Multiobjective Restricted Binary Decision Diagrams by Learning to Sparsify. CoRR abs/2403.02482 (2024) - [i25]Arnaud Deza, Elias B. Khalil, Zhenan Fan, Zirui Zhou, Yong Zhang:
Learn2Aggregate: Supervised Generation of Chvátal-Gomory Cuts Using Graph Neural Networks. CoRR abs/2409.06559 (2024) - [i24]Wenhao Li, Yudong Xu, Scott Sanner, Elias Boutros Khalil:
Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects. CoRR abs/2410.06405 (2024) - [i23]Bo Tang, Elias B. Khalil, Ján Drgona:
Learning to Optimize for Mixed-Integer Non-linear Programming. CoRR abs/2410.11061 (2024) - 2023
- [j5]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial Optimization and Reasoning with Graph Neural Networks. J. Mach. Learn. Res. 24: 130:1-130:61 (2023) - [c30]Yudong Xu, Elias B. Khalil, Scott Sanner:
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. AAAI 2023: 4115-4122 - [c29]Weimin Huang, Elias B. Khalil:
Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto. AAAI 2023: 14249-14258 - [c28]Elias B. Khalil:
Recent Developments in Data-Driven Algorithms for Discrete Optimization. AAAI 2023: 15443 - [c27]Arnaud Deza, Chang Liu, Pashootan Vaezipoor, Elias B. Khalil:
Fast Matrix Multiplication Without Tears: A Constraint Programming Approach. CP 2023: 14:1-14:15 - [c26]Aravinth Chembu, Scott Sanner, Elias B. Khalil:
Scalable and Near-Optimal ε-Tube Clusterwise Regression. CPAIOR 2023: 254-263 - [c25]Arnaud Deza, Elias B. Khalil:
Machine Learning for Cutting Planes in Integer Programming: A Survey. IJCAI 2023: 6592-6600 - [c24]Bo Tang, Elias B. Khalil:
Multi-task Predict-then-Optimize. LION 2023: 506-522 - [c23]Omar ElSamadisy, Yazeed Abdulhai, Haoyuan Xue, Ilia Smirnov, Elias B. Khalil, Baher Abdulhai:
SMAC-tuned Deep Q-learning for Ramp Metering. SM 2023: 65-72 - [c22]Joseph Scott, Guanting Pan, Piyush Jha, Elias B. Khalil, Vijay Ganesh:
Pierce: A Testing Tool for Neural Network Verification Solvers. VSTTE 2023: 31-43 - [i22]Arnaud Deza, Elias B. Khalil:
Machine Learning for Cutting Planes in Integer Programming: A Survey. CoRR abs/2302.09166 (2023) - [i21]Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias B. Khalil:
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations. CoRR abs/2305.18354 (2023) - [i20]Arnaud Deza, Chang Liu, Pashootan Vaezipoor, Elias B. Khalil:
Fast Matrix Multiplication Without Tears: A Constraint Programming Approach. CoRR abs/2306.01097 (2023) - [i19]Rahul Patel, Elias B. Khalil:
LEO: Learning Efficient Orderings for Multiobjective Binary Decision Diagrams. CoRR abs/2307.03171 (2023) - [i18]Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias B. Khalil:
Neur2RO: Neural Two-Stage Robust Optimization. CoRR abs/2310.04345 (2023) - [i17]Bo Tang, Elias B. Khalil:
CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs. CoRR abs/2312.07718 (2023) - 2022
- [j4]Aazad Abbas, Jacob Mosseri, Johnathan R. Lex, Jay Toor, Bheeshma Ravi, Elias B. Khalil, Cari M. Whyne:
Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty. Int. J. Medical Informatics 158(February): 104670 (2022) - [j3]Mohammad Ali Alomrani, Reza Moravej, Elias Boutros Khalil:
Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach. Trans. Mach. Learn. Res. 2022 (2022) - [j2]Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar:
Lookback for Learning to Branch. Trans. Mach. Learn. Res. 2022 (2022) - [c21]Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina:
Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework. AAAI 2022: 3786-3795 - [c20]Elias B. Khalil, Christopher Morris, Andrea Lodi:
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. AAAI 2022: 10219-10227 - [c19]Weimin Huang, Alex Olson, Elias B. Khalil, Shoshanna Saxe:
Note: Image-based Prediction of House Attributes with Deep Learning. COMPASS 2022: 693-695 - [c18]Cheng Chi, Amine Mohamed Aboussalah, Elias B. Khalil, Juyoung Wang, Zoha Sherkat-Masoumi:
A Deep Reinforcement Learning Framework for Column Generation. NeurIPS 2022 - [c17]Rahul Patel, Justin Dumouchelle, Elias B. Khalil, Merve Bodur:
Neur2SP: Neural Two-Stage Stochastic Programming. NeurIPS 2022 - [c16]Joseph Scott, Guanting Pan, Elias B. Khalil, Vijay Ganesh:
Goose: A Meta-Solver for Deep Neural Network Verification. SMT 2022: 99-113 - [i16]Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR abs/2203.02433 (2022) - [i15]Justin Dumouchelle, Rahul Patel, Elias B. Khalil, Merve Bodur:
Neur2SP: Neural Two-Stage Stochastic Programming. CoRR abs/2205.12006 (2022) - [i14]Elias B. Khalil, Christopher Morris, Andrea Lodi:
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. CoRR abs/2205.14210 (2022) - [i13]Cheng Chi, Amine Mohamed Aboussalah, Elias B. Khalil, Juyoung Wang, Zoha Sherkat-Masoumi:
A Deep Reinforcement Learning Framework For Column Generation. CoRR abs/2206.02568 (2022) - [i12]Bo Tang, Elias B. Khalil:
PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming. CoRR abs/2206.14234 (2022) - [i11]Prateek Gupta, Elias B. Khalil, Didier Chételat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar:
Lookback for Learning to Branch. CoRR abs/2206.14987 (2022) - [i10]Yudong Xu, Elias B. Khalil, Scott Sanner:
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. CoRR abs/2210.09880 (2022) - [i9]Weimin Huang, Elias B. Khalil:
Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto. CoRR abs/2212.05192 (2022) - 2021
- [c15]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial Optimization and Reasoning with Graph Neural Networks. IJCAI 2021: 4348-4355 - [c14]Maxime Gasse, Simon Bowly, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) 2021: 220-231 - [c13]Antonia Chmiela, Elias B. Khalil, Ambros M. Gleixner, Andrea Lodi, Sebastian Pokutta:
Learning to Schedule Heuristics in Branch and Bound. NeurIPS 2021: 24235-24246 - [i8]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial optimization and reasoning with graph neural networks. CoRR abs/2102.09544 (2021) - [i7]Antonia Chmiela, Elias B. Khalil, Ambros M. Gleixner, Andrea Lodi, Sebastian Pokutta:
Learning to Schedule Heuristics in Branch-and-Bound. CoRR abs/2103.10294 (2021) - [i6]Mohammad Ali Alomrani, Reza Moravej, Elias B. Khalil:
Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach. CoRR abs/2109.10380 (2021) - [i5]Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina:
Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework. CoRR abs/2110.08423 (2021) - 2020
- [b1]Elias Boutros Khalil:
Towards Tighter Integration of Machine Learning and Discrete Optimization. Georgia Institute of Technology, Atlanta, GA, USA, 2020 - [c12]Prateek Gupta, Maxime Gasse, Elias B. Khalil, Pawan Kumar Mudigonda, Andrea Lodi, Yoshua Bengio:
Hybrid Models for Learning to Branch. NeurIPS 2020 - [i4]Prateek Gupta, Maxime Gasse, Elias B. Khalil, M. Pawan Kumar, Andrea Lodi, Yoshua Bengio:
Hybrid Models for Learning to Branch. CoRR abs/2006.15212 (2020)
2010 – 2019
- 2019
- [c11]Elias B. Khalil, Amrita Gupta, Bistra Dilkina:
Combinatorial Attacks on Binarized Neural Networks. ICLR (Poster) 2019 - 2018
- [i3]Elias B. Khalil, Amrita Gupta, Bistra Dilkina:
Combinatorial Attacks on Binarized Neural Networks. CoRR abs/1810.03538 (2018) - 2017
- [c10]Ardavan Afshar, Joyce C. Ho, Bistra Dilkina, Ioakeim Perros, Elias B. Khalil, Li Xiong, Vaidy S. Sunderam:
CP-ORTHO: An Orthogonal Tensor Factorization Framework for Spatio-Temporal Data. SIGSPATIAL/GIS 2017: 67:1-67:4 - [c9]Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias B. Khalil, Shuang Li, Le Song, Hongyuan Zha:
Fake News Mitigation via Point Process Based Intervention. ICML 2017: 1097-1106 - [c8]Elias B. Khalil, Bistra Dilkina, George L. Nemhauser, Shabbir Ahmed, Yufen Shao:
Learning to Run Heuristics in Tree Search. IJCAI 2017: 659-666 - [c7]Fatemeh Nargesian, Horst Samulowitz, Udayan Khurana, Elias B. Khalil, Deepak S. Turaga:
Learning Feature Engineering for Classification. IJCAI 2017: 2529-2535 - [c6]Elias B. Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, Le Song:
Learning Combinatorial Optimization Algorithms over Graphs. NIPS 2017: 6348-6358 - [c5]Elias B. Khalil, Mustafa Assaf, Abdel Salam Sayyad:
Human Resource Optimization for Bug Fixing: Balancing Short-Term and Long-Term Objectives. SSBSE 2017: 124-129 - [i2]Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias Boutros Khalil, Shuang Li, Le Song, Hongyuan Zha:
Fake News Mitigation via Point Process Based Intervention. CoRR abs/1703.07823 (2017) - [i1]Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, Le Song:
Learning Combinatorial Optimization Algorithms over Graphs. CoRR abs/1704.01665 (2017) - 2016
- [c4]Elias Boutros Khalil, Pierre Le Bodic, Le Song, George L. Nemhauser, Bistra Dilkina:
Learning to Branch in Mixed Integer Programming. AAAI 2016: 724-731 - [c3]Elias B. Khalil:
Machine Learning for Integer Programming. IJCAI 2016: 4004-4005 - [c2]Sucheta Soundarajan, Acar Tamersoy, Elias B. Khalil, Tina Eliassi-Rad, Duen Horng Chau, Brian Gallagher, Kevin A. Roundy:
Generating Graph Snapshots from Streaming Edge Data. WWW (Companion Volume) 2016: 109-110 - 2014
- [j1]Acar Tamersoy, Elias B. Khalil, Bo Xie, Stephen L. Lenkey, Bryan R. Routledge, Duen Horng Chau, Shamkant B. Navathe:
Large-scale insider trading analysis: patterns and discoveries. Soc. Netw. Anal. Min. 4(1): 201 (2014) - [c1]Elias Boutros Khalil, Bistra Dilkina, Le Song:
Scalable diffusion-aware optimization of network topology. KDD 2014: 1226-1235
Coauthor Index
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