Stochastic Allocation and Scheduling for Conditional Task Graphs in MPSoCs. - Michele Lombardi 001; Michela Milano (CP, 2006)

Optimal Multi-Agent Scheduling with Constraint Programming. - Willem Jan van Hoeve; Carla P. Gomes; Bart Selman; Michele Lombardi 001 (AAAI, 2007)

Scheduling Conditional Task Graphs. - Michele Lombardi 001; Michela Milano (CP, 2007)

Communication-aware stochastic allocation and scheduling framework for conditional task graphs in multi-processor systems-on-chip. - Emiliano Dolif; Michele Lombardi 001; Martino Ruggiero; Michela Milano; Luca Benini (EMSOFT, 2007)

A Constraint Programming Approach for Allocation and Scheduling on the CELL Broadband Engine. - Luca Benini; Michele Lombardi 001; Michela Milano; Martino Ruggiero (CP, 2008)

Multi-stage Benders Decomposition for Optimizing Multicore Architectures. - Luca Benini; Michele Lombardi 001; Marco Mantovani 001; Michela Milano; Martino Ruggiero (CPAIOR, 2008)

Cellflow: A Parallel Application Development Environment with Run-Time Support for the Cell BE Processor. - Martino Ruggiero; Michele Lombardi 001; Michela Milano; Luca Benini (DSD, 2008)

A Precedence Constraint Posting Approach for the RCPSP with Time Lags and Variable Durations. - Michele Lombardi 001; Michela Milano (CP, 2009)

Throughput Constraint for Synchronous Data Flow Graphs. - Alessio Bonfietti; Michele Lombardi 001; Michela Milano; Luca Benini (CPAIOR, 2009)

Robust non-preemptive hard real-time scheduling for clustered multicore platforms. - Michele Lombardi 001; Michela Milano; Luca Benini (DATE, 2009)

Discrepancy-Based Sliced Neighborhood Search. - Fabio Parisini; Michele Lombardi 001; Michela Milano (AIMSA, 2010)

Methods for Designing Reliable Probe Arrays. - Michele Lombardi 001; Luca Benini; Abhishek Garg; Giovanni De Micheli (BIBE, 2010)

Constraint Based Scheduling to Deal with Uncertain Durations and Self-Timed Execution. - Michele Lombardi 001; Michela Milano (CP, 2010)

An efficient and complete approach for throughput-maximal SDF allocation and scheduling on multi-core platforms. - Alessio Bonfietti; Luca Benini; Michele Lombardi 001; Michela Milano (DATE, 2010)

Allocation and scheduling of Conditional Task Graphs. - Michele Lombardi 001; Michela Milano (Artif. Intell., 2010)

Stochastic allocation and scheduling for conditional task graphs in multi-processor systems-on-chip. - Michele Lombardi 001; Michela Milano; Martino Ruggiero; Luca Benini (J. Sched., 2010)

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments. - Michele Lombardi 001 (2010)

MPOpt-Cell: a high-performance data-flow programming environment for the CELL BE processor. - Alessio Franceschelli; Paolo Burgio; Giuseppe Tagliavini; Andrea Marongiu; Martino Ruggiero; Michele Lombardi 001; Alessio Bonfietti; Michela Milano; Luca Benini (Conf. Computing Frontiers, 2011)

Neuron Constraints to Model Complex Real-World Problems. - Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (CP, 2011)

A Constraint Based Approach to Cyclic RCPSP. - Alessio Bonfietti; Michele Lombardi 001; Luca Benini; Michela Milano (CP, 2011)

Precedence Constraint Posting for Cyclic Scheduling Problems. - Michele Lombardi 001; Alessio Bonfietti; Michela Milano; Luca Benini (CPAIOR, 2011)

Optimal resource allocation and scheduling for the CELL BE platform. - Luca Benini; Michele Lombardi 001; Michela Milano; Martino Ruggiero (Ann. Oper. Res., 2011)

Deriving Information from Sampling and Diving. - Michele Lombardi 001; Michela Milano; Andrea Roli; Alessandro Zanarini (Fundam. Informaticae, 2011)

Optimization and Controlled Systems: A Case Study on Thermal Aware Workload Dispatching. - Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (AAAI, 2012)

The Weighted Average Constraint. - Alessio Bonfietti; Michele Lombardi 001 (CP, 2012)

Global Cyclic Cumulative Constraint. - Alessio Bonfietti; Michele Lombardi 001; Luca Benini; Michela Milano (CPAIOR, 2012)

A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling. - Michele Lombardi 001; Michela Milano (Artif. Intell., 2012)

Optimal methods for resource allocation and scheduling: a cross-disciplinary survey. - Michele Lombardi 001; Michela Milano (Constraints An Int. J., 2012)

De-Cycling Cyclic Scheduling Problems. - Alessio Bonfietti; Michele Lombardi 001; Michela Milano (ICAPS, 2013)

A Simple and Effective Decomposition for the Multidimensional Binpacking Constraint. - Stefano Gualandi; Michele Lombardi 001 (CP, 2013)

A New Propagator for Two-Layer Neural Networks in Empirical Model Learning. - Michele Lombardi 001; Stefano Gualandi (CP, 2013)

Maximum-throughput mapping of SDFGs on multi-core SoC platforms. - Alessio Bonfietti; Michele Lombardi 001; Michela Milano; Luca Benini (J. Parallel Distributed Comput., 2013)

Robust Scheduling of Task Graphs under Execution Time Uncertainty. - Michele Lombardi 001; Michela Milano; Luca Benini (IEEE Trans. Computers, 2013)

Proactive Workload Dispatching on the EURORA Supercomputer. - Andrea Bartolini; Andrea Borghesi; Thomas Bridi; Michele Lombardi 001; Michela Milano (CP, 2014)

Disregarding Duration Uncertainty in Partial Order Schedules? Yes, We Can! - Alessio Bonfietti; Michele Lombardi 001; Michela Milano (CPAIOR, 2014)

Cost Impact Guided LNS. - Michele Lombardi 001; Pierre Schaus (CPAIOR, 2014)

CROSS cyclic resource-constrained scheduling solver. - Alessio Bonfietti; Michele Lombardi 001; Luca Benini; Michela Milano (Artif. Intell., 2014)

Strategic decision making on complex systems. - Michela Milano; Michele Lombardi 001 (Constraints An Int. J., 2014)

A CP Scheduler for High-Performance Computers. - Thomas Bridi; Michele Lombardi 001; Andrea Bartolini; Luca Benini; Michela Milano (DC@AI*IA, 2015)

Power Capping in High Performance Computing Systems. - Andrea Borghesi; Francesca Collina; Michele Lombardi 001; Michela Milano; Luca Benini (CP, 2015)

Deterministic Estimation of the Expected Makespan of a POS Under Duration Uncertainty. - Michele Lombardi 001; Alessio Bonfietti; Michela Milano (CP, 2015)

Embedding Decision Trees and Random Forests in Constraint Programming. - Alessio Bonfietti; Michele Lombardi 001; Michela Milano (CPAIOR, 2015)

Understanding the Potential of Propagators. - Sascha Van Cauwelaert; Michele Lombardi 001; Pierre Schaus (CPAIOR, 2015)

MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot! - Andrea Borghesi; Christian Conficoni; Michele Lombardi 001; Andrea Bartolini (HPCS, 2015)

The Multirate Resource Constraint. - Alessio Bonfietti; Alessandro Zanarini; Michele Lombardi 001; Michela Milano (CP, 2016)

Non-linear Optimization of Business Models in the Electricity Market. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (CPAIOR, 2016)

DARDIS: Distributed And Randomized DIspatching and Scheduling. - Thomas Bridi; Michele Lombardi 001; Andrea Bartolini; Luca Benini; Michela Milano (ECAI, 2016)

Predictive Modeling for Job Power Consumption in HPC Systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (ISC, 2016)

A lagrangian propagator for artificial neural networks in constraint programming. - Michele Lombardi 001; Stefano Gualandi (Constraints An Int. J., 2016)

A Constraint Programming Scheduler for Heterogeneous High-Performance Computing Machines. - Thomas Bridi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (IEEE Trans. Parallel Distributed Syst., 2016)

Robust Optimization for Virtual Power Plants. - Allegra De Filippo; Michele Lombardi 001; Michela Milano; Alberto Borghetti (AI*IA, 2017)

Empirical decision model learning. - Michele Lombardi 001; Michela Milano; Andrea Bartolini (Artif. Intell., 2017)

Introduction to the CPAIOR 2017 fast track issue. - Domenico Salvagnin; Michele Lombardi 001 (Constraints An Int. J., 2017)

A Visual Web Tool to Perform What-If Analysis of Optimization Approaches. - Sascha Van Cauwelaert; Michele Lombardi 001; Pierre Schaus (CoRR, 2017)

Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (CPAIOR, 2018)

Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study. - Andrea Galassi; Michele Lombardi 001; Paola Mello; Michela Milano (CPAIOR, 2018)

From Offline to Online Kidney Exchange Optimization. - Danuta Sorina Chisca; Michele Lombardi 001; Michela Milano; Barry O'Sullivan (ICTAI, 2018)

Boosting Combinatorial Problem Modeling with Machine Learning. - Michele Lombardi 001; Michela Milano (IJCAI, 2018)

Methods for off-line/on-line optimization under uncertainty. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (IJCAI, 2018)

How efficient is a global constraint in practice? - A fair experimental framework. - Sascha Van Cauwelaert; Michele Lombardi 001; Pierre Schaus (Constraints An Int. J., 2018)

Scheduling-based power capping in high performance computing systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (Sustain. Comput. Informatics Syst., 2018)

Anomaly Detection Using Autoencoders in High Performance Computing Systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (AAAI, 2019)

Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem. - Danuta Sorina Chisca; Michele Lombardi 001; Michela Milano; Barry O'Sullivan (CP, 2019)

A Sampling-Free Anticipatory Algorithm for the Kidney Exchange Problem. - Danuta Sorina Chisca; Michele Lombardi 001; Michela Milano; Barry O'Sullivan (CPAIOR, 2019)

How to Tame Your Anticipatory Algorithm. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (IJCAI, 2019)

A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (Eng. Appl. Artif. Intell., 2019)

Combining learning and optimization for transprecision computing. - Andrea Borghesi; Giuseppe Tagliavini; Michele Lombardi 001; Luca Benini; Michela Milano (CF, 2020)

Hybrid Offline/Online Optimization Under Uncertainty. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (ECAI, 2020)

Injecting domain knowledge in neural networks: a controlled experiment on a constrained problem. - Mattia Silvestri; Michele Lombardi 001; Michela Milano (NeHuAI@ECAI, 2020)

The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (IJCAI, 2020)

Injective Domain Knowledge in Neural Networks for Transprecision Computing. - Andrea Borghesi; Federico Baldo; Michele Lombardi 001; Michela Milano (LOD (1), 2020)

Lagrangian Duality for Constrained Deep Learning. - Ferdinando Fioretto; Pascal Van Hentenryck; Terrence W. K. Mak; Cuong Tran 007; Federico Baldo; Michele Lombardi 001 (ECML/PKDD (5), 2020)

An Analysis of Regularized Approaches for Constrained Machine Learning. - Michele Lombardi 001; Federico Baldo; Andrea Borghesi; Michela Milano (TAILOR, 2020)

A Lagrangian Dual Framework for Deep Neural Networks with Constraints. - Ferdinando Fioretto; Terrence W. K. Mak; Federico Baldo; Michele Lombardi 001; Pascal Van Hentenryck (CoRR, 2020)

Discrete solution pools and noise-contrastive estimation for predict-and-optimize. - Maxime Mulamba; Jayanta Mandi; Michelangelo Diligenti; Michele Lombardi 001; Victor Bucarey; Tias Guns (CoRR, 2020)

Teaching the Old Dog New Tricks: Supervised Learning with Constraints. - Fabrizio Detassis; Michele Lombardi 001; Michela Milano (AAAI, 2021)

Robust Optimization Models For Local Flexibility Characterization of Virtual Power Plants. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (AI*IA, 2021)

Contrastive Losses and Solution Caching for Predict-and-Optimize. - Maxime Mulamba; Jayanta Mandi; Michelangelo Diligenti; Michele Lombardi 001; Victor Bucarey; Tias Guns (IJCAI, 2021)

Preface. - Yingqian Zhang 001; Michele Lombardi 001; Patrick De Causmaecker (Ann. Math. Artif. Intell., 2021)

Deep Learning for Virus-Spreading Forecasting: a Brief Survey. - Federico Baldo; Lorenzo Dall'Olio; Mattia Ceccarelli; Riccardo Scheda; Michele Lombardi 001; Andrea Borghesi; Stefano Diciotti; Michela Milano (CoRR, 2021)

Integrated Offline and Online Decision Making under Uncertainty. - Allegra De Filippo; Michele Lombardi 001; Michela Milano (J. Artif. Intell. Res., 2021)

Hybrid Offline/Online Optimization for Energy Management via Reinforcement Learning. - Mattia Silvestri; Allegra De Filippo; Federico Ruggeri; Michele Lombardi 001 (CPAIOR, 2022)

Informed Deep Learning for Epidemics Forecasting. - Federico Baldo; Michele Iannello; Michele Lombardi 001; Michela Milano (PAIS@ECAI, 2022)

Supervised Anomaly Detection in Crude Oil Stabilization. - Mattia Silvestri; Michele Lombardi 001; Emiliano Mucchi; Luca Cadei; Giovanna Magnago; Marco Piantanida; Valentina D'Ottavio; Nguyen Van Tu; Simona Duma; Silvia Taddei; Annagiulia Tiozzo; Andrea Corneo; et al. (PAIS@ECAI, 2022)

Towards Smart Cities for Tourism: the POLIS-EYE Project. - Alessandro Seravalli; Mariaelena Busani; Simone Venturi; Arianna Brutti; Carlo Petrovich; Angelo Frascella; Fabrizio Paolucci; Marco Di Felice; Michele Lombardi 001; Elena Bellodi; Riccardo Zese; Francesco Bertasi; et al. (ISC2, 2022)

Strategies for Improving the Error Robustness of Convolutional Neural Networks. - António Morais; Raul Barbosa; Nuno Lourenço 002; Frederico Cerveira; Michele Lombardi 001; Henrique Madeira (QRS, 2022)

Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. - Stefano Teso; Laurens Bliek; Andrea Borghesi; Michele Lombardi 001; Neil Yorke-Smith; Tias Guns; Andrea Passerini (CoRR, 2022)

UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning. - Mattia Silvestri; Allegra De Filippo; Michele Lombardi 001; Michela Milano (CoRR, 2022)

Data-Driven Combinatorial Optimisation (Dagstuhl Seminar 22431). - Emma Frejinger; Andrea Lodi 001; Michele Lombardi 001; Neil Yorke-Smith (Dagstuhl Reports, 2022)

A geometric framework for fairness. - Alessandro Maggio; Luca Giuliani; Roberta Calegari; Michele Lombardi 001; Michela Milano (AEQUITAS@ECAI, 2023)

FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System. - Eleonora Misino; Roberta Calegari; Michele Lombardi 001; Michela Milano (AEQUITAS@ECAI, 2023)

An Analysis of Universal Differential Equations for Data-Driven Discovery of Ordinary Differential Equations. - Mattia Silvestri; Federico Baldo; Eleonora Misino; Michele Lombardi 001 (ICCS (4), 2023)

Generalized Disparate Impact for Configurable Fairness Solutions in ML. - Luca Giuliani; Eleonora Misino; Michele Lombardi 001 (ICML, 2023)

Computational Asymmetries in Robust Classification. - Samuele Marro; Michele Lombardi 001 (ICML, 2023)

Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning. - Mattia Silvestri; Senne Berden; Jayanta Mandi; Ali Irfan Mahmutogullari; Maxime Mulamba; Allegra De Filippo; Tias Guns; Michele Lombardi 001 (CoRR, 2023)

QAL-BP: An Augmented Lagrangian Quantum Approach for Bin Packing Problem. - Lorenzo Cellini; Antonio Macaluso; Michele Lombardi 001 (CoRR, 2023)

Long-Term Fairness Strategies in Ranking with Continuous Sensitive Attributes. - Luca Giuliani; Eleonora Misino; Roberta Calegari; Michele Lombardi 001 (AEQUITAS@ECAI, 2024)

Swarm Intelligence: A Novel and Unconventional Approach to Dance Choreography Creation. - Michele Braccini; Allegra De Filippo; Michele Lombardi 001; Michela Milano (CREAI@ECAI, 2024)

Trustworthiness of AI in Planning and Scheduling: The Experience of the TUPLES Project. - Angelo Gordini; Matteo Pozzi; Michele Lombardi 001; Thomas Sergeys; Tias Guns; Andrea De Cesarei; Sofia Morandini; Sylvie Thiébaux (DSA ISC (2), 2024)

Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method. - Eleonora Misino; Roberta Calegari; Michele Lombardi 001; Michela Milano (IJCAI, 2024)

UNIFY: A unified policy designing framework for solving integrated Constrained Optimization and Machine Learning problems. - Mattia Silvestri; Allegra De Filippo; Michele Lombardi 001; Michela Milano (Knowl. Based Syst., 2024)

GUMBLE: Uncertainty-Aware Conditional Mobile Data Generation Using Bayesian Learning. - Marco Skocaj; Lorenzo Mario Amorosa; Michele Lombardi 001; Roberto Verdone (IEEE Trans. Mob. Comput., 2024)

SMLE: Safe Machine Learning via Embedded Overapproximation. - Matteo Francobaldi; Michele Lombardi 001 (AAAI, 2025)

Dance Choreography Driven by Swarm Intelligence in Extended Reality Scenarios: Perspectives and Implications. - Michele Braccini; Allegra De Filippo; Michele Lombardi 001; Michela Milano (AIxVR, 2025)

Constrained Machine Learning Through Hyperspherical Representation. - Gaetano Signorelli; Michele Lombardi 001 (CPAIOR (2), 2025)

Language Models Are Implicitly Continuous. - Samuele Marro; Davide Evangelista; X. Angelo Huang; Emanuele La Malfa; Michele Lombardi 001; Michael J. Wooldridge (ICLR, 2025)

Data science meets optimization II. - Yingqian Zhang 001; Tias Guns; Michele Lombardi 001; Patrick De Causmaecker (Ann. Math. Artif. Intell., 2025)