Elias B. Khalil

Orcid: 0000-0001-5844-9642

Affiliations:
  • University of Toronto, Department of Mechanical and Industrial Engineering, ON, Canada
  • Georgia Institute of Technology, College of Computing, Atlanta, GA, USA


According to our database1, Elias B. Khalil authored at least 43 papers between 2014 and 2024.

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Bibliography

2024
MORBDD: Multiobjective Restricted Binary Decision Diagrams by Learning to Sparsify.
CoRR, 2024

Neur2BiLO: Neural Bilevel Optimization.
CoRR, 2024

2023
Combinatorial Optimization and Reasoning with Graph Neural Networks.
J. Mach. Learn. Res., 2023

CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs.
CoRR, 2023

Neur2RO: Neural Two-Stage Robust Optimization.
CoRR, 2023

LEO: Learning Efficient Orderings for Multiobjective Binary Decision Diagrams.
CoRR, 2023

LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations.
CoRR, 2023

SMAC-tuned Deep Q-learning for Ramp Metering.
Proceedings of the IEEE International Conference on Smart Mobility, 2023

Multi-task Predict-then-Optimize.
Proceedings of the Learning and Intelligent Optimization - 17th International Conference, 2023

Machine Learning for Cutting Planes in Integer Programming: A Survey.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Scalable and Near-Optimal ε-Tube Clusterwise Regression.
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2023

Fast Matrix Multiplication Without Tears: A Constraint Programming Approach.
Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming, 2023

Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Recent Developments in Data-Driven Algorithms for Discrete Optimization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Lookback for Learning to Branch.
Trans. Mach. Learn. Res., 2022

Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach.
Trans. Mach. Learn. Res., 2022

Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty.
Int. J. Medical Informatics, 2022

PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming.
CoRR, 2022

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.
CoRR, 2022

Goose: A Meta-Solver for Deep Neural Network Verification.
Proceedings of the 20th Internal Workshop on Satisfiability Modulo Theories co-located with the 11th International Joint Conference on Automated Reasoning (IJCAR 2022) part of the 8th Federated Logic Conference (FLoC 2022), 2022

Neur2SP: Neural Two-Stage Stochastic Programming.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Deep Reinforcement Learning Framework for Column Generation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Note: Image-based Prediction of House Attributes with Deep Learning.
Proceedings of the COMPASS '22: ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, Seattle, WA, USA, 29 June 2022, 2022

Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Learning to Schedule Heuristics in Branch and Bound.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Towards Tighter Integration of Machine Learning and Discrete Optimization.
PhD thesis, 2020

Hybrid Models for Learning to Branch.
CoRR, 2020

Hybrid Models for Learning to Branch.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Combinatorial Attacks on Binarized Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2017
Human Resource Optimization for Bug Fixing: Balancing Short-Term and Long-Term Objectives.
Proceedings of the Search Based Software Engineering - 9th International Symposium, 2017

Learning Combinatorial Optimization Algorithms over Graphs.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Feature Engineering for Classification.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Learning to Run Heuristics in Tree Search.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Fake News Mitigation via Point Process Based Intervention.
Proceedings of the 34th International Conference on Machine Learning, 2017

CP-ORTHO: An Orthogonal Tensor Factorization Framework for Spatio-Temporal Data.
Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017

2016
Generating Graph Snapshots from Streaming Edge Data.
Proceedings of the 25th International Conference on World Wide Web, 2016

Machine Learning for Integer Programming.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning to Branch in Mixed Integer Programming.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2014
Large-scale insider trading analysis: patterns and discoveries.
Soc. Netw. Anal. Min., 2014

Scalable diffusion-aware optimization of network topology.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014


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