research
∙
07/18/2023
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information
Recent works in learning-integrated optimization have shown promise in s...
share
research
∙
04/27/2023
Moccasin: Efficient Tensor Rematerialization for Neural Networks
The deployment and training of neural networks on edge computing devices...
research
∙
04/10/2023
Artificial Intelligence/Operations Research Workshop 2 Report Out
This workshop Report Out focuses on the foundational elements of trustwo...
research
∙
02/03/2023
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
Integer Linear Programs (ILPs) are powerful tools for modeling and solvi...
research
∙
12/15/2022
Local Branching Relaxation Heuristics for Integer Linear Programs
Large Neighborhood Search (LNS) is a popular heuristic algorithm for sol...
research
∙
10/22/2022
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems
Optimization problems with expensive nonlinear cost functions and combin...
research
∙
10/16/2021
Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework
In Mixed Integer Linear Programming (MIP), a (strong) backdoor is a "sma...
research
∙
07/07/2021
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling
There is significant interest in learning and optimizing a complex syste...
research
∙
06/09/2021
Learning Pseudo-Backdoors for Mixed Integer Programs
We propose a machine learning approach for quickly solving Mixed Integer...
research
∙
04/23/2021
Becoming Good at AI for Good
AI for good (AI4G) projects involve developing and applying artificial i...
research
∙
01/11/2021
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation
Controlling bias in training datasets is vital for ensuring equal treatm...
research
∙
12/10/2020
Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search
Conflict-Based Search (CBS) is a state-of-the-art algorithm for multi-ag...
research
∙
10/13/2020
Video Game Level Repair via Mixed Integer Linear Programming
Recent advancements in procedural content generation via machine learnin...
research
∙
03/29/2020
A General Large Neighborhood Search Framework for Solving Integer Programs
This paper studies how to design abstractions of large-scale combinatori...
research
∙
06/10/2019
Human-Machine Collaboration for Fast Land Cover Mapping
We propose incorporating human labelers in a model fine-tuning system th...
research
∙
06/06/2019
Evolution of Hierarchical Structure Reuse in iGEM Synthetic DNA Sequences
Many complex systems, both in technology and nature, exhibit hierarchica...
research
∙
05/31/2019
End to end learning and optimization on graphs
Real-world applications often combine learning and optimization problems...
research
∙
04/23/2019
Migration patterns under different scenarios of sea level rise
We propose a framework to examine future migration patterns of people un...
research
∙
03/08/2019
Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations
Illegal wildlife poaching threatens ecosystems and drives endangered spe...
research
∙
03/03/2019
Decision-Focused Learning of Adversary Behavior in Security Games
Stackelberg security games are a critical tool for maximizing the utilit...
research
∙
02/05/2019
Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data
Digital Adherence Technologies (DATs) are an increasingly popular method...
research
∙
10/08/2018
Combinatorial Attacks on Binarized Neural Networks
Binarized Neural Networks (BNNs) have recently attracted significant int...
research
∙
09/14/2018
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization
Creating impact in real-world settings requires artificial intelligence ...
research
∙
05/13/2018
Emergence and Evolution of Hierarchical Structure in Complex Systems
It is well known that many complex systems, both in technology and natur...
research
∙
12/12/2017
Hawkes Processes for Invasive Species Modeling and Management
The spread of invasive species to new areas threatens the stability of e...
research
∙
08/30/2017
A Deep Learning Approach for Population Estimation from Satellite Imagery
Knowing where people live is a fundamental component of many decision ma...
research
∙
04/05/2017
Learning Combinatorial Optimization Algorithms over Graphs
The design of good heuristics or approximation algorithms for NP-hard co...
research
∙
02/23/2016
δ-MAPS: From spatio-temporal data to a weighted and lagged network between functional domains
We propose δ-MAPS, a method that analyzes spatio-temporal data to first ...
research
∙
02/17/2016