Michele Lombardi

发表

Teaching the old dog new tricks: supervised learning with constraints

Fabrizio Detassis, Michele Lombardi, Michela Milano, 2020, NeHuAI@ECAI.

From Offline to Online Kidney Exchange Optimization

Barry O'Sullivan, Michele Lombardi, Michela Milano, 2018, 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI).

A Lagrangian Dual Framework for Deep Neural Networks with Constraints pdf

Michele Lombardi, Ferdinando Fioretto, Terrence WK Mak, 2020, ArXiv.

How to Tame Your Anticipatory Algorithm

Michele Lombardi, Michela Milano, Allegra De Filippo, 2019, DDC@AI*IA.

Empirical decision model learning

Andrea Bartolini, Michele Lombardi, Michela Milano, 2017, Artif. Intell..

Supervised Learning to Control Energetic Reasoning: A Feasibility Study

Pierre Schaus, Michele Lombardi, Sascha Van Cauwelaert, 2014 .

Injecting domain knowledge in neural networks: a controlled experiment on a constrained problem

Michele Lombardi, Michela Milano, Mattia Silvestri, 2020, NeHuAI@ECAI.

CROSS cyclic resource-constrained scheduling solver

Luca Benini, Michele Lombardi, Michela Milano, 2014, Artif. Intell..

Deterministic Estimation of the Expected Makespan of a POS Under Duration Uncertainty

Michele Lombardi, Michela Milano, Alessio Bonfietti, 2015, CP.

Optimization and Controlled Systems: A Case Study on Thermal Aware Workload Dispatching

Luca Benini, Andrea Bartolini, Michele Lombardi, 2012, AAAI.

An efficient and complete approach for throughput-maximal SDF allocation and scheduling on multi-core platforms

Luca Benini, Michele Lombardi, Michela Milano, 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

Neuron Constraints to Model Complex Real-World Problems

Luca Benini, Andrea Bartolini, Michele Lombardi, 2011, CP.

A Precedence Constraint Posting Approach for the RCPSP with Time Lags and Variable Durations

Michele Lombardi, Michela Milano, M. Milano, 2009, CP.

Discrepancy-Based Sliced Neighborhood Search

Michele Lombardi, Michela Milano, Fabio Parisini, 2010, AIMSA.

Embedding Decision Trees and Random Forests in Constraint Programming

Michele Lombardi, Michela Milano, Alessio Bonfietti, 2015, CPAIOR.

Stochastic Allocation and Scheduling for Conditional Task Graphs in MPSoCs

Michele Lombardi, Michela Milano, 2006, CP.

Anomaly Detection using Autoencoders in High Performance Computing Systems

Luca Benini, Andrea Bartolini, Andrea Borghesi, 2018, DDC@AI*IA.

Challenging Scheduling Problem in the field of System Design

Michele Lombardi, Michela Milano, Alessio Guerri, 2007 .

Disregarding Duration Uncertainty in Partial Order Schedules? Yes, We Can!

Michele Lombardi, Michela Milano, Alessio Bonfietti, 2014, CPAIOR.

An Analysis of Regularized Approaches for Constrained Machine Learning pdf

Andrea Borghesi, Michele Lombardi, Michela Milano, 2020, ArXiv.

Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study

Paola Mello, Michele Lombardi, Michela Milano, 2018, CPAIOR.

Stochastic allocation and scheduling for conditional task graphs in multi-processor systems-on-chip

Luca Benini, Michele Lombardi, Michela Milano, 2010, J. Sched..

Introduction to the CPAIOR 2017 fast track issue

Michele Lombardi, Domenico Salvagnin, 2017, Constraints.

A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems

Luca Benini, Andrea Borghesi, Michele Lombardi, 2019, Eng. Appl. Artif. Intell..

Boosting Combinatorial Problem Modeling with Machine Learning

Michele Lombardi, Michela Milano, Allegra De Filippo, 2018, IJCAI.

Hybrid Offline/Online Optimization Under Uncertainty

Michele Lombardi, Michela Milano, Allegra De Filippo, 2020, European Conference on Artificial Intelligence.

MPOpt-Cell: a high-performance data-flow programming environment for the CELL BE processor

Luca Benini, Michele Lombardi, Paolo Burgio, 2011, CF '11.

Allocation and scheduling of Conditional Task Graphs

Michele Lombardi, Michela Milano, M. Milano, 2010, Artif. Intell..

Maximum-throughput mapping of SDFGs on multi-core SoC platforms

Luca Benini, Michele Lombardi, Michela Milano, 2013, J. Parallel Distributed Comput..

De-Cycling Cyclic Scheduling Problems

Michele Lombardi, Michela Milano, Alessio Bonfietti, 2013, ICAPS.

Combining learning and optimization for transprecision computing

Luca Benini, Andrea Borghesi, Michele Lombardi, 2020, CF.

Lagrangian Duality for Constrained Deep Learning

Michele Lombardi, Ferdinando Fioretto, Terrence WK Mak, 2020, ECML/PKDD.

Robust Scheduling of Task Graphs under Execution Time Uncertainty

Luca Benini, Michele Lombardi, Michela Milano, 2013, IEEE Transactions on Computers.

Communication-aware stochastic allocation and scheduling framework for conditional task graphs in multi-processor systems-on-chip

Luca Benini, Michele Lombardi, Michela Milano, 2007, EMSOFT '07.

Scheduling-based power capping in high performance computing systems

Andrea Borghesi, Michele Lombardi, Luca Benini, 2018, Sustain. Comput. Informatics Syst..

Power Capping in High Performance Computing Systems

Luca Benini, Andrea Borghesi, Michele Lombardi, 2015, CP.

Understanding the Potential of Propagators

Pierre Schaus, Michele Lombardi, Sascha Van Cauwelaert, 2015, CPAIOR.

Multi-stage Benders Decomposition for Optimizing Multicore Architectures

Luca Benini, Marco Mantovani, Michele Lombardi, 2008, CPAIOR.

Integration of AI and OR Techniques in Constraint Programming: 12th International Conference, CPAIOR 2015, Barcelona, Spain, May 18-22, 2015, Proceedings

Michele Lombardi, Domenico Salvagnin, Domenico Salvagnin, 2015, CPAIOR.

Constraint Based Scheduling to Deal with Uncertain Durations and Self-Timed Execution

Michele Lombardi, Michela Milano, M. Milano, 2010, CP.

MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot!

Andrea Bartolini, Andrea Borghesi, Michele Lombardi, 2015, 2015 International Conference on High Performance Computing & Simulation (HPCS).

A Constraint Based Approach to Cyclic RCPSP

Luca Benini, Michele Lombardi, Michela Milano, 2011, CP.

A Sampling-Free Anticipatory Algorithm for the Kidney Exchange Problem

Barry O'Sullivan, Michele Lombardi, Michela Milano, 2019, CPAIOR.

Optimal methods for resource allocation and scheduling: a cross-disciplinary survey

Michele Lombardi, Michela Milano, M. Milano, 2011, Constraints.

Proactive Workload Dispatching on the EURORA Supercomputer

Andrea Bartolini, Andrea Borghesi, Michele Lombardi, 2014, CP.

DARDIS: Distributed And Randomized DIspatching and Scheduling

Luca Benini, Andrea Bartolini, Michele Lombardi, 2016, International Conference of the Italian Association for Artificial Intelligence.

A CP Scheduler for High-Performance Computers

Luca Benini, Andrea Bartolini, Michele Lombardi, 2015, DC@AI*IA.

Predictive Modeling for Job Power Consumption in HPC Systems

Luca Benini, Andrea Bartolini, Andrea Borghesi, 2016, ISC.

A Constraint Programming Approach for Allocation and Scheduling on the CELL Broadband Engine

Luca Benini, Michele Lombardi, Michela Milano, 2008, CP.

A Simple and Effective Decomposition for the Multidimensional Binpacking Constraint

Michele Lombardi, Stefano Gualandi, 2013, CP.

A lagrangian propagator for artificial neural networks in constraint programming

Michele Lombardi, Stefano Gualandi, Stefano Gualandi, 2016, Constraints.

DARDIS: Distributed And Randomized DIspatching and Scheduling

Luca Benini, Andrea Bartolini, Michele Lombardi, 2016, AI*IA.

A Constraint Programming Scheduler for Heterogeneous High-Performance Computing Machines

Luca Benini, Andrea Bartolini, Michele Lombardi, 2016, IEEE Transactions on Parallel and Distributed Systems.

Robust Optimization for Virtual Power Plants

Alberto Borghetti, Michele Lombardi, Michela Milano, 2017, AI*IA.

A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling

Michele Lombardi, Michela Milano, M. Milano, 2012, Artif. Intell..

Discrete solution pools and noise-contrastive estimation for predict-and-optimize pdf

Tias Guns, Michele Lombardi, Michelangelo Diligenti, 2020, ArXiv.

Cellflow: A Parallel Application Development Environment with Run-Time Support for the Cell BE Processor

Luca Benini, Michele Lombardi, Michela Milano, 2008, 2008 11th EUROMICRO Conference on Digital System Design Architectures, Methods and Tools.

Non-linear Optimization of Business Models in the Electricity Market

Michele Lombardi, Michela Milano, Allegra De Filippo, 2016, CPAIOR.

Precedence Constraint Posting for Cyclic Scheduling Problems

Luca Benini, Michele Lombardi, Michela Milano, 2011, CPAIOR.

Global Cyclic Cumulative Constraint

Luca Benini, Michele Lombardi, Michela Milano, 2012, CPAIOR.

Optimal resource allocation and scheduling for the CELL BE platform

Luca Benini, Michele Lombardi, Michela Milano, 2011, Ann. Oper. Res..

Optimal Multi-Agent Scheduling with Constraint Programming

Bart Selman, Willem Jan van Hoeve, Michele Lombardi, 2007, AAAI.

Throughput Constraint for Synchronous Data Flow Graphs

Luca Benini, Michele Lombardi, Michela Milano, 2009, CPAIOR.

The Multirate Resource Constraint

Alessandro Zanarini, Michele Lombardi, Michela Milano, 2016, CP.

Injective Domain Knowledge in Neural Networks for Transprecision Computing

Andrea Borghesi, Michele Lombardi, Michela Milano, 2020, LOD.

Scheduling Conditional Task Graphs

Michele Lombardi, Michela Milano, 2007, CP.

Boosting Combinatorial Problem Modeling with Machine Learning pdf

Michele Lombardi, Michela Milano, M. Milano, 2018, IJCAI.

Integrated Offline and Online Decision Making under Uncertainty

Michele Lombardi, Allegra De Filippo, M. Lombardi, 2021, J. Artif. Intell. Res..

Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem

Barry O'Sullivan, Michele Lombardi, Michela Milano, 2019, CP.

The Weighted Average Constraint

Michele Lombardi, Alessio Bonfietti, Alessio Bonfietti, 2012, CP.

Nash implementation via simple stochastic mechanisms: strategy space reduction

Michele Lombardi, 2012 .

Cost Impact Guided LNS

Pierre Schaus, Michele Lombardi, 2014, CPAIOR.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

Michele Lombardi, M. Lombardi, Michele Lombardi, 2010 .

Methods for Designing Reliable Probe Arrays

Luca Benini, Giovanni De Micheli, Michele Lombardi, 2010, 2010 IEEE International Conference on BioInformatics and BioEngineering.

A Visual Web Tool to Perform What-If Analysis of Optimization Approaches pdf

Pierre Schaus, Michele Lombardi, Sascha Van Cauwelaert, 2017, ArXiv.

Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management

Michele Lombardi, Michela Milano, Allegra De Filippo, 2018, CPAIOR.

The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty

Michele Lombardi, Michela Milano, Allegra De Filippo, 2020, IJCAI.

Closure under interim utility equivalence implies two-agent Bayesian implementation

Ville Korpela, Michele Lombardi, M. Lombardi, 2020, Games Econ. Behav..

A New Propagator for Two-Layer Neural Networks in Empirical Model Learning

Michele Lombardi, Stefano Gualandi, Stefano Gualandi, 2013, CP.

How efficient is a global constraint in practice?

Pierre Schaus, Michele Lombardi, Sascha Van Cauwelaert, 2017, Constraints.

Strategic decision making on complex systems

Michele Lombardi, Michela Milano, 2014, Constraints.

Deriving Information from Sampling and Diving

Alessandro Zanarini, Andrea Roli, Michele Lombardi, 2009, AI*IA.

Robust non-preemptive hard real-time scheduling for clustered multicore platforms

Luca Benini, Michele Lombardi, Michela Milano, 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.

Deriving Information from Sampling and Diving

Alessandro Zanarini, Andrea Roli, Michele Lombardi, 2009, Fundamenta Informaticae.

Machine-Learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains

Michele Lombardi, Antonio Tirri, Attilio Castellarin, 2021, Natural Hazards and Earth System Sciences.

Contrastive Losses and Solution Caching for Predict-and-Optimize

Tias Guns, Michele Lombardi, Michelangelo Diligenti, 2021, IJCAI.

Deep Learning for Virus-Spreading Forecasting: a Brief Survey pdf

Stefano Diciotti, Michele Lombardi, Michela Milano, 2021, ArXiv.