Distributed Constraint Optimization Problems and Applications: A Survey
- Ferdinando Fioretto, Enrico Pontelli, W. Yeoh
- Computer ScienceJournal of Artificial Intelligence Research
- 20 February 2016
An overview of the DCOP model is provided, giving a classification of its multiple extensions and addressing both resolution methods and applications that find a natural mapping within each class of DCOPs.
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods
- Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck
- EngineeringAAAI Conference on Artificial Intelligence
- 19 September 2019
A deep learning approach to the Optimal Power Flow problem that exploits the information available in the prior states of the system, as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF.
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach
- Cuong D. Tran, Ferdinando Fioretto, Pascal Van Hentenryck
- Computer ScienceAAAI Conference on Artificial Intelligence
- 26 September 2020
This paper studies a model that protects the privacy of the individuals’ sensitive information while also allowing it to learn non-discriminatory predictors and relies on the notion of differential privacy and the use of Lagrangian duality to design neural networks that can accommodate fairness constraints while guaranteeing the Privacy of sensitive attributes.
Lagrangian Duality for Constrained Deep Learning
- Ferdinando Fioretto, P. V. Hentenryck, Terrence W.K. Mak, Cuong D. Tran, Federico Baldo, M. Lombardi
- Computer ScienceECML/PKDD
- 26 January 2020
Lagrangian duality can be used to enforce fairness constraints on a predictor and obtain state-of-the-art results when minimizing disparate treatments and can complement deep learning to impose monotonicity constraints on the predictor without sacrificing accuracy.
A GPU Implementation of Large Neighborhood Search for Solving Constraint Optimization Problems
- F. Campeotto, A. Dovier, Ferdinando Fioretto, Enrico Pontelli
- Computer ScienceEuropean Conference on Artificial Intelligence
- 18 August 2014
This paper describes a novel framework which exploits parallelism from a popular local search method (the Large Neighborhood Search method), using GPUs.
A Multiagent System Approach to Scheduling Devices in Smart Homes
- Ferdinando Fioretto, W. Yeoh, Enrico Pontelli
- Engineering, Computer ScienceAdaptive Agents and Multi-Agent Systems
- 8 May 2017
The Smart Home Device Scheduling (SHDS) problem is introduced, which formalizes the device scheduling and coordination problem across multiple smart homes as a multi-agent system.
End-to-End Constrained Optimization Learning: A Survey
- James Kotary, Ferdinando Fioretto, P. V. Hentenryck, B. Wilder
- Computer ScienceInternational Joint Conference on Artificial…
- 30 March 2021
This paper presents a conceptual review of the recent advancements in this emerging area of hybrid machine learning and optimization to predict fast, approximate, solutions to combinatorial problems and to enable structural logical inference.
Improving DPOP with Branch Consistency for Solving Distributed Constraint Optimization Problems
- Ferdinando Fioretto, Tiep Le, W. Yeoh, Enrico Pontelli, Tran Cao Son
- Computer ScienceInternational Conference on Principles and…
- 8 September 2014
Experimental results shows that BrC-DPOP uses messages that are up to one order of magnitude smaller than DPOP, and that it can scale up well, being able to solve problems that its counterpart can not.
Infinite-Horizon Proactive Dynamic DCOPs
- Khoi D. Hoang, P. Hou, Ferdinando Fioretto, W. Yeoh, Roie Zivan, M. Yokoo
- Computer ScienceAdaptive Agents and Multi-Agent Systems
- 8 May 2017
This work proposes the Infinite-Horizon PD-DCOP (IPD-DC OP) model, which extends PD- DCOPs to handle infinite horizons, and exploits the convergence properties of Markov chains to determine the optimal solution to the problem after it has converged.
A Large Neighboring Search Schema for Multi-agent Optimization
- Khoi D. Hoang, Ferdinando Fioretto, W. Yeoh, Enrico Pontelli, Roie Zivan
- Computer ScienceInternational Conference on Principles and…
- 27 August 2018
The Distributed Large Neighborhood Search (DLNS) is proposed, a novel iterative local search framework to solve DCOPs, which provides guarantees on solution quality refining lower and upper bounds in an iterative process.
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