Pascal Van Hentenryck
28 papers · 2013–2025 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (38) π Academic Marathon Β· Half π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
(3)
π€
Dynamic Duo
(15)
π
Conference Pioneer
π₯
Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(6)
ποΈ
Keyword Collector
(118)
Venues
Top co-authors
Research topics
Machine Learning
(20)
Mathematics & Optimization
(11)
Application Areas
(10)
Optimization
(10)
Optimization & Theory Β· Machine Learning
(10)
Artificial Intelligence
(7)
Deep Learning
(6)
Core AI
(6)
Learning Types
(4)
Data Science & Analytics
(3)
Security & Privacy
(3)
Architectures
(3)
Differential Privacy
(3)
Optimization & Theory Β· Deep Learning
(3)
Core Methods
(2)
Keywords
differential privacy
(8)
census data
(3)
combinatorial optimization
(3)
lagrangian duality
(3)
algorithmic fairness
(3)
adversarial robustness
(2)
deep learning
(2)
privacy preservation
(2)
optimality gap
(2)
constraint satisfaction
(2)
self-supervised learning
(2)
disparate impact
(2)
model predictive control
(2)
constrained optimization
(2)
machine learning
(2)
fairness optimization
(2)
neural network
(2)
neural network training
(1)
supervised learning
(1)
reinforcement learning
(1)
Papers
Contextual Stochastic Optimization for School Desegregation Policymaking
AAAI 2025
Compact Optimality Verification for Optimization Proxies
ICML 2024
Dual Lagrangian Learning for Conic Optimization
NeurIPS 2024
Empathy and AI: Achieving Equitable Microtransit for Underserved Communities
IJCAI 2024
Finding Ξ΅ and Ξ΄ of Traditional Disclosure Control Systems
AAAI 2024
On the Effects of Fairness to Adversarial Vulnerability
IJCAI 2024
Reinforcement Learning from Optimization Proxy for Ride-Hailing Vehicle Relocation (Extended Abstract)
IJCAI 2023
Self-Supervised Primal-Dual Learning for Constrained Optimization
AAAI 2023
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles
IJCAI 2023
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
IJCAI 2022
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method
AAAI 2022
Post-processing of Differentially Private Data: A Fairness Perspective
IJCAI 2022
Bias and Variance of Post-processing in Differential Privacy
AAAI 2021
Branch and Price for Bus Driver Scheduling with Complex Break Constraints
AAAI 2021
Decision Making with Differential Privacy under a Fairness Lens
IJCAI 2021
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach
AAAI 2021
End-to-End Constrained Optimization Learning: A Survey
IJCAI 2021
Learning Hard Optimization Problems: A Data Generation Perspective
NeurIPS 2021
Real-Time Pricing Optimization for Ride-Hailing Quality of Service
IJCAI 2021
Differential Privacy for Stackelberg Games
IJCAI 2020
OptStream: Releasing Time Series Privately (Extended Abstract)
IJCAI 2020
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods
AAAI 2020
Real-Time Dispatching of Large-Scale Ride-Sharing Systems: Integrating Optimization, Machine Learning, and Model Predictive Control
IJCAI 2020
Privacy-Preserving Obfuscation of Critical Infrastructure Networks
IJCAI 2019
Asymptotic Optimality of Myopic Optimization in Trial-Offer Markets with Social Influence
IJCAI 2016
Interdependent Scheduling Games
IJCAI 2016
A Bargaining Mechanism for One-Way Games
IJCAI 2015
Computational Disaster Management
IJCAI 2013