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ORCIDMichele Lombardi 0001
Person information
- affiliation: University of Bologna, Italy
Other persons with the same name
- Michele Lombardi 0002
![[0000-0002-8613-053X]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-8613-053X")
— University of Glasgow, UK (and 4 more)
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2020 – today
- 2020
[c58]Andrea Borghesi, Giuseppe Tagliavini, Michele Lombardi, Luca Benini, Michela Milano:
Combining learning and optimization for transprecision computing. CF 2020: 10-18- [c57]Fabrizio Detassis, Michele Lombardi, Michela Milano:
Teaching the old dog new tricks: supervised learning with constraints. NeHuAI@ECAI 2020: 44-51 - [c56]Mattia Silvestri, Michele Lombardi, Michela Milano:
Injecting domain knowledge in neural networks: a controlled experiment on a constrained problem. NeHuAI@ECAI 2020: 52-58 - [c55]Allegra De Filippo, Michele Lombardi, Michela Milano:
Hybrid Offline/Online Optimization Under Uncertainty. ECAI 2020: 2899-2900 - [c54]Allegra De Filippo, Michele Lombardi, Michela Milano:
The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty. IJCAI 2020: 4840-4846 - [c53]Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano:
Injective Domain Knowledge in Neural Networks for Transprecision Computing. LOD (1) 2020: 587-600 - [i10]Ferdinando Fioretto, Terrence W. K. Mak, Federico Baldo, Michele Lombardi, Pascal Van Hentenryck:
A Lagrangian Dual Framework for Deep Neural Networks with Constraints. CoRR abs/2001.09394 (2020) - [i9]Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano:
Injective Domain Knowledge in Neural Networks for Transprecision Computing. CoRR abs/2002.10214 (2020) - [i8]Mattia Silvestri, Michele Lombardi, Michela Milano:
Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem. CoRR abs/2002.10742 (2020) - [i7]Fabrizio Detassis, Michele Lombardi, Michela Milano:
Teaching the Old Dog New Tricks: Supervised Learning with Constraints. CoRR abs/2002.10766 (2020) - [i6]Andrea Borghesi, Giuseppe Tagliavini, Michele Lombardi, Luca Benini, Michela Milano:
Combining Learning and Optimization for Transprecision Computing. CoRR abs/2002.10890 (2020) - [i5]Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano:
An Analysis of Regularized Approaches for Constrained Machine Learning. CoRR abs/2005.10674 (2020) - [i4]Maxime Mulamba, Jayanta Mandi, Michelangelo Diligenti, Michele Lombardi, Victor Bucarey, Tias Guns:
Discrete solution pools and noise-contrastive estimation for predict-and-optimize. CoRR abs/2011.05354 (2020)
2010 – 2019
- 2019
- [j17]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems. Eng. Appl. Artif. Intell. 85: 634-644 (2019) - [c52]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection Using Autoencoders in High Performance Computing Systems. AAAI 2019: 9428-9433 - [c51]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection using Autoencoders in High Performance Computing Systems. DDC@AI*IA 2019: 24-32 - [c50]Allegra De Filippo, Michele Lombardi, Michela Milano:
How to Tame Your Anticipatory Algorithm. DDC@AI*IA 2019: 36-44 - [c49]Danuta Sorina Chisca, Michele Lombardi, Michela Milano, Barry O'Sullivan:
Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem. CP 2019: 108-125 - [c48]Danuta Sorina Chisca, Michele Lombardi, Michela Milano, Barry O'Sullivan:
A Sampling-Free Anticipatory Algorithm for the Kidney Exchange Problem. CPAIOR 2019: 146-162 - [c47]Allegra De Filippo, Michele Lombardi, Michela Milano:
How to Tame Your Anticipatory Algorithm. IJCAI 2019: 1071-1077 - 2018
- [j16]Sascha Van Cauwelaert, Michele Lombardi, Pierre Schaus:
How efficient is a global constraint in practice? - A fair experimental framework. Constraints An Int. J. 23(1): 87-122 (2018) - [j15]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Scheduling-based power capping in high performance computing systems. Sustain. Comput. Informatics Syst. 19: 1-13 (2018) - [c46]Allegra De Filippo, Michele Lombardi, Michela Milano:
Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management. CPAIOR 2018: 100-116 - [c45]Andrea Galassi, Michele Lombardi, Paola Mello, Michela Milano:
Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study. CPAIOR 2018: 254-262 - [c44]Danuta Sorina Chisca, Michele Lombardi, Michela Milano, Barry O'Sullivan:
From Offline to Online Kidney Exchange Optimization. ICTAI 2018: 587-591 - [c43]Allegra De Filippo, Michele Lombardi, Michela Milano:
Methods for off-line/on-line optimization under uncertainty. IJCAI 2018: 1270-1276 - [c42]Michele Lombardi, Michela Milano:
Boosting Combinatorial Problem Modeling with Machine Learning. IJCAI 2018: 5472-5478 - [i3]Michele Lombardi, Michela Milano:
Boosting Combinatorial Problem Modeling with Machine Learning. CoRR abs/1807.05517 (2018) - [i2]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection using Autoencoders in High Performance Computing Systems. CoRR abs/1811.05269 (2018) - 2017
- [j14]Michele Lombardi, Michela Milano, Andrea Bartolini:
Empirical decision model learning. Artif. Intell. 244: 343-367 (2017) - [j13]Domenico Salvagnin, Michele Lombardi:
Introduction to the CPAIOR 2017 fast track issue. Constraints An Int. J. 22(4): 491-492 (2017) - [c41]Allegra De Filippo, Michele Lombardi, Michela Milano, Alberto Borghetti:
Robust Optimization for Virtual Power Plants. AI*IA 2017: 17-30 - [e2]Domenico Salvagnin, Michele Lombardi:
Integration of AI and OR Techniques in Constraint Programming - 14th International Conference, CPAIOR 2017, Padua, Italy, June 5-8, 2017, Proceedings. Lecture Notes in Computer Science 10335, Springer 2017, ISBN 978-3-319-59775-1 [contents] - [i1]Sascha Van Cauwelaert, Michele Lombardi, Pierre Schaus:
A Visual Web Tool to Perform What-If Analysis of Optimization Approaches. CoRR abs/1703.06042 (2017) - 2016
- [j12]Michele Lombardi, Stefano Gualandi:
A lagrangian propagator for artificial neural networks in constraint programming. Constraints An Int. J. 21(4): 435-462 (2016) - [j11]Thomas Bridi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
A Constraint Programming Scheduler for Heterogeneous High-Performance Computing Machines. IEEE Trans. Parallel Distributed Syst. 27(10): 2781-2794 (2016) - [c40]Thomas Bridi, Michele Lombardi, Andrea Bartolini, Luca Benini, Michela Milano:
DARDIS: Distributed And Randomized DIspatching and Scheduling. AI*IA 2016: 493-507 - [c39]Alessio Bonfietti, Alessandro Zanarini, Michele Lombardi, Michela Milano:
The Multirate Resource Constraint. CP 2016: 113-129 - [c38]Allegra De Filippo, Michele Lombardi, Michela Milano:
Non-linear Optimization of Business Models in the Electricity Market. CPAIOR 2016: 81-97 - [c37]Thomas Bridi, Michele Lombardi, Andrea Bartolini, Luca Benini, Michela Milano:
DARDIS: Distributed And Randomized DIspatching and Scheduling. ECAI 2016: 1598-1599 - [c36]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Predictive Modeling for Job Power Consumption in HPC Systems. ISC 2016: 181-199 - 2015
- [c35]Thomas Bridi, Michele Lombardi, Andrea Bartolini, Luca Benini, Michela Milano:
A CP Scheduler for High-Performance Computers. DC@AI*IA 2015: 37-42 - [c34]Michele Lombardi, Alessio Bonfietti, Michela Milano:
Deterministic Estimation of the Expected Makespan of a POS Under Duration Uncertainty. CP 2015: 279-294 - [c33]Andrea Borghesi, Francesca Collina, Michele Lombardi, Michela Milano, Luca Benini:
Power Capping in High Performance Computing Systems. CP 2015: 524-540 - [c32]Alessio Bonfietti, Michele Lombardi, Michela Milano:
Embedding Decision Trees and Random Forests in Constraint Programming. CPAIOR 2015: 74-90 - [c31]Sascha Van Cauwelaert, Michele Lombardi, Pierre Schaus:
Understanding the Potential of Propagators. CPAIOR 2015: 427-436 - [c30]Andrea Borghesi, Christian Conficoni, Michele Lombardi, Andrea Bartolini:
MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot! HPCS 2015: 88-95 - 2014
- [j10]Alessio Bonfietti, Michele Lombardi, Luca Benini, Michela Milano:
CROSS cyclic resource-constrained scheduling solver. Artif. Intell. 206: 25-52 (2014) - [j9]Michela Milano, Michele Lombardi:
Strategic decision making on complex systems. Constraints An Int. J. 19(2): 174-185 (2014) - [c29]Andrea Bartolini, Andrea Borghesi, Thomas Bridi, Michele Lombardi, Michela Milano:
Proactive Workload Dispatching on the EURORA Supercomputer. CP 2014: 765-780 - [c28]Alessio Bonfietti, Michele Lombardi, Michela Milano:
Disregarding Duration Uncertainty in Partial Order Schedules? Yes, We Can! CPAIOR 2014: 210-225 - [c27]Michele Lombardi, Pierre Schaus:
Cost Impact Guided LNS. CPAIOR 2014: 293-300 - 2013
- [j8]Alessio Bonfietti, Michele Lombardi, Michela Milano, Luca Benini:
Maximum-throughput mapping of SDFGs on multi-core SoC platforms. J. Parallel Distributed Comput. 73(10): 1337-1350 (2013) - [j7]Michele Lombardi, Michela Milano, Luca Benini:
Robust Scheduling of Task Graphs under Execution Time Uncertainty. IEEE Trans. Computers 62(1): 98-111 (2013) - [c26]Alessio Bonfietti, Michele Lombardi, Michela Milano:
De-Cycling Cyclic Scheduling Problems. ICAPS 2013 - [c25]Michele Lombardi, Michela Milano:
A Min-Flow Algorithm for Minimal Critical Set Detection in Resource Constrained Project Scheduling. ICAPS 2013 - [c24]Stefano Gualandi, Michele Lombardi:
A Simple and Effective Decomposition for the Multidimensional Binpacking Constraint. CP 2013: 356-364 - [c23]Michele Lombardi, Stefano Gualandi:
A New Propagator for Two-Layer Neural Networks in Empirical Model Learning. CP 2013: 448-463 - 2012
- [j6]Michele Lombardi, Michela Milano:
A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling. Artif. Intell. 182-183: 58-67 (2012) - [j5]Michele Lombardi, Michela Milano:
Optimal methods for resource allocation and scheduling: a cross-disciplinary survey. Constraints An Int. J. 17(1): 51-85 (2012) - [c22]Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Optimization and Controlled Systems: A Case Study on Thermal Aware Workload Dispatching. AAAI 2012 - [c21]Alessio Bonfietti, Michele Lombardi:
The Weighted Average Constraint. CP 2012: 191-206 - [c20]Alessio Bonfietti, Michele Lombardi, Luca Benini, Michela Milano:
Global Cyclic Cumulative Constraint. CPAIOR 2012: 81-96 - [e1]Paolo Liberatore, Michele Lombardi, Floriano Scioscia:
Proceedings of the Doctoral Consortium of the 12th Symposium of the Italian Association for Artificial Intelligence, Rome, Italy, June 15, 2012. CEUR Workshop Proceedings 926, CEUR-WS.org 2012 [contents] - 2011
- [j4]Luca Benini, Michele Lombardi, Michela Milano, Martino Ruggiero:
Optimal resource allocation and scheduling for the CELL BE platform. Ann. Oper. Res. 184(1): 51-77 (2011) - [j3]Michele Lombardi, Michela Milano, Andrea Roli, Alessandro Zanarini:
Deriving Information from Sampling and Diving. Fundam. Informaticae 107(2-3): 267-287 (2011) - [c19]Alessio Franceschelli, Paolo Burgio, Giuseppe Tagliavini, Andrea Marongiu, Martino Ruggiero, Michele Lombardi, Alessio Bonfietti, Michela Milano, Luca Benini:
MPOpt-Cell: a high-performance data-flow programming environment for the CELL BE processor. Conf. Computing Frontiers 2011: 11 - [c18]Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Neuron Constraints to Model Complex Real-World Problems. CP 2011: 115-129 - [c17]Alessio Bonfietti, Michele Lombardi, Luca Benini, Michela Milano:
A Constraint Based Approach to Cyclic RCPSP. CP 2011: 130-144 - [c16]Michele Lombardi, Alessio Bonfietti, Michela Milano, Luca Benini:
Precedence Constraint Posting for Cyclic Scheduling Problems. CPAIOR 2011: 137-153 - 2010
- [b1]Michele Lombardi:
Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments. University of Bologna, Italy, 2010 - [j2]Michele Lombardi, Michela Milano:
Allocation and scheduling of Conditional Task Graphs. Artif. Intell. 174(7-8): 500-529 (2010) - [j1]Michele Lombardi, Michela Milano, Martino Ruggiero, Luca Benini:
Stochastic allocation and scheduling for conditional task graphs in multi-processor systems-on-chip. J. Sched. 13(4): 315-345 (2010) - [c15]Fabio Parisini, Michele Lombardi, Michela Milano:
Discrepancy-Based Sliced Neighborhood Search. AIMSA 2010: 91-100 - [c14]Michele Lombardi, Luca Benini, Abhishek Garg, Giovanni De Micheli:
Methods for Designing Reliable Probe Arrays. BIBE 2010: 306-307 - [c13]Michele Lombardi, Michela Milano:
Constraint Based Scheduling to Deal with Uncertain Durations and Self-Timed Execution. CP 2010: 383-397 - [c12]Alessio Bonfietti, Luca Benini, Michele Lombardi, Michela Milano:
An efficient and complete approach for throughput-maximal SDF allocation and scheduling on multi-core platforms. DATE 2010: 897-902
2000 – 2009
- 2009
- [c11]Michele Lombardi, Michela Milano, Andrea Roli, Alessandro Zanarini:
Deriving Information from Sampling and Diving. AI*IA 2009: 82-91 - [c10]Michele Lombardi, Michela Milano:
A Precedence Constraint Posting Approach for the RCPSP with Time Lags and Variable Durations. CP 2009: 569-583 - [c9]Alessio Bonfietti, Michele Lombardi, Michela Milano, Luca Benini:
Throughput Constraint for Synchronous Data Flow Graphs. CPAIOR 2009: 26-40 - [c8]Michele Lombardi, Michela Milano, Luca Benini:
Robust non-preemptive hard real-time scheduling for clustered multicore platforms. DATE 2009: 803-808 - 2008
- [c7]Luca Benini, Michele Lombardi, Michela Milano, Martino Ruggiero:
A Constraint Programming Approach for Allocation and Scheduling on the CELL Broadband Engine. CP 2008: 21-35 - [c6]Luca Benini, Michele Lombardi, Marco Mantovani, Michela Milano, Martino Ruggiero:
Multi-stage Benders Decomposition for Optimizing Multicore Architectures. CPAIOR 2008: 36-50 - [c5]Martino Ruggiero, Michele Lombardi, Michela Milano, Luca Benini:
Cellflow: A Parallel Application Development Environment with Run-Time Support for the Cell BE Processor. DSD 2008: 645-650 - 2007
- [c4]Willem Jan van Hoeve, Carla P. Gomes, Bart Selman, Michele Lombardi:
Optimal Multi-Agent Scheduling with Constraint Programming. AAAI 2007: 1813-1818 - [c3]Michele Lombardi, Michela Milano:
Scheduling Conditional Task Graphs. CP 2007: 468-482 - [c2]Emiliano Dolif, Michele Lombardi, Martino Ruggiero, Michela Milano, Luca Benini:
Communication-aware stochastic allocation and scheduling framework for conditional task graphs in multi-processor systems-on-chip. EMSOFT 2007: 47-56 - 2006
- [c1]Michele Lombardi, Michela Milano:
Stochastic Allocation and Scheduling for Conditional Task Graphs in MPSoCs. CP 2006: 299-313
Coauthor Index
[c58] [c57] [c56] [c55] [c54] [c53] [i9] [i8] [i7] [i6] [i5] [j17] [c52] [c51] [c50] [c49] [c48] [c47] [j15] [c46] [c45] [c44] [c43] [c42] [i3] [i2] [j14] [c41] [j11] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [j10] [j9] [c29] [c28] [j8] [j7] [c26] [c25] [j6] [j5] [c22] [c20] [j4] [j3] [c19] [c18] [c17] [c16] [j2] [j1] [c15] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c3] [c2] [c1]
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