| Nome |
# |
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The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm, file e1dcb335-dc12-7715-e053-1705fe0a6cc9
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395
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A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems, file e1dcb338-4109-7715-e053-1705fe0a6cc9
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384
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Anomaly Detection and Anticipation in High Performance Computing Systems, file e1dcb339-f191-7715-e053-1705fe0a6cc9
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199
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Towards a Novel HMI Paradigm Based on Mixed EEG and Indoor Localization Platforms, file e1dcb332-d711-7715-e053-1705fe0a6cc9
|
182
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Power capping in high performance computing systems, file e1dcb335-6ab8-7715-e053-1705fe0a6cc9
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130
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Combining learning and optimization for transprecision computing, file e1dcb335-b9e8-7715-e053-1705fe0a6cc9
|
106
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Scheduling-based power capping in high performance computing systems, file e1dcb338-7556-7715-e053-1705fe0a6cc9
|
104
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Empirical decision model learning, file e1dcb338-45bc-7715-e053-1705fe0a6cc9
|
103
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Integrated Offline and Online Decision Making under Uncertainty, file e1dcb336-abd9-7715-e053-1705fe0a6cc9
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94
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An Analysis of Regularized Approaches for Constrained Machine Learning, file e1dcb338-85d9-7715-e053-1705fe0a6cc9
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81
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A Constraint Programming Scheduler for Heterogeneous High-Performance Computing Machines, file e1dcb338-7e5c-7715-e053-1705fe0a6cc9
|
68
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Merging Observed and Self-Reported Behaviour in Agent-Based Simulation: A Case Study on Photovoltaic Adoption, file e1dcb333-2a31-7715-e053-1705fe0a6cc9
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67
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The blind men and the elephant: Integrated offline/online optimization under uncertainty, file bf2ed99e-31cb-40bc-8fcc-6a966ce66c6e
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53
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User-aware electricity price optimization for the competitive market, file e1dcb330-3cff-7715-e053-1705fe0a6cc9
|
45
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Constraint Programming Links with Math Programming, file e1dcb32c-07b4-7715-e053-1705fe0a6cc9
|
39
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Teaching the old dog new tricks: Supervised learning with constraints, file e1dcb336-ee2c-7715-e053-1705fe0a6cc9
|
33
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Hybrid offline/online optimization under uncertainty, file e1dcb337-a806-7715-e053-1705fe0a6cc9
|
24
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Optimal Methods for resource allocation and scheduling: a cross-disciplinary survey, file e1dcb32c-29da-7715-e053-1705fe0a6cc9
|
21
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Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem, file 978e5e1f-f12c-4cdd-bb43-1980549789fb
|
13
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Sliced Neighborhood Search, file e1dcb32c-29e2-7715-e053-1705fe0a6cc9
|
13
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Injective Domain Knowledge in Neural Networks for Transprecision Computing, file f49651ef-a949-4525-bef2-4ba8f3158a10
|
13
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Injecting domain knowledge in neural networks: A controlled experiment on a constrained problem, file 59718676-d78d-4b55-b17b-9993022cd8d2
|
11
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Integrating Operations Research in Constraint Programming, file e1dcb32b-c8cb-7715-e053-1705fe0a6cc9
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11
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Frequency Assignment in High Performance Computing Systems, file e1dcb333-8b91-7715-e053-1705fe0a6cc9
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11
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Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem, file e1dcb338-8aab-7715-e053-1705fe0a6cc9
|
11
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HADA: An automated tool for hardware dimensioning of AI applications, file de7b7d60-1965-4524-ac7e-a6ceb4ddec3d
|
8
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Sustainable biomass power plant location in the Italian Emilia-Romagna Region, file e1dcb32c-07bd-7715-e053-1705fe0a6cc9
|
8
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Towards a Novel HMI Paradigm Based on Mixed EEG and Indoor Localization Platforms, file e1dcb330-1197-7715-e053-1705fe0a6cc9
|
8
|
|
The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm, file e1dcb331-8207-7715-e053-1705fe0a6cc9
|
7
|
|
A Constraint based approach to cyclic RCPSP, file e1dcb32c-07ae-7715-e053-1705fe0a6cc9
|
6
|
|
An Application of Fuzzy Logic to Strategic Environmental Assessment, file e1dcb32c-29e5-7715-e053-1705fe0a6cc9
|
6
|
|
Neuron Constraints to Model Complex Real-World Problems, file e1dcb32c-29eb-7715-e053-1705fe0a6cc9
|
6
|
|
Do You Like Dancing Robots? AI Can Tell You Why, file dfac2549-80f8-48e5-b429-12f5820e2455
|
5
|
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Improving CP-based Local Branching via Sliced Neighborhood Search, file e1dcb32c-07bb-7715-e053-1705fe0a6cc9
|
5
|
|
Global Cyclic Cumulative Constraint, file e1dcb32c-29d2-7715-e053-1705fe0a6cc9
|
5
|
|
Power capping in high performance computing systems, file e1dcb32d-e464-7715-e053-1705fe0a6cc9
|
4
|
|
Solving Mathematical Puzzles: A Challenging Competition for AI, file e1dcb330-491f-7715-e053-1705fe0a6cc9
|
4
|
|
A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling, file e1dcb32c-29d4-7715-e053-1705fe0a6cc9
|
3
|
|
Informed Deep Learning for Epidemics Forecasting, file 3fb70986-3160-403b-9131-88924d0f017b
|
2
|
|
Methods for off-line/on-line optimization under uncertainty, file e1dcb331-9fa2-7715-e053-1705fe0a6cc9
|
2
|
|
Boosting combinatorial problem modeling with machine learning, file e1dcb331-9fa3-7715-e053-1705fe0a6cc9
|
2
|
|
Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management, file e1dcb331-a496-7715-e053-1705fe0a6cc9
|
2
|
|
Anomaly Detection Using Autoencoders in High Performance Computing Systems, file e1dcb332-e716-7715-e053-1705fe0a6cc9
|
2
|
|
Teaching the Old Dog New Tricks: Supervised Learning with Constraints, file e1dcb339-13e0-7715-e053-1705fe0a6cc9
|
2
|
|
HADA: An automated tool for hardware dimensioning of AI applications, file 1e9c0537-3d6a-4dbb-8b0a-dc7e8b291a61
|
1
|
|
MPOpt-Cell: a high-performance data-flow programming environment for the CELL BE processor, file e1dcb32c-3e7a-7715-e053-1705fe0a6cc9
|
1
|
|
Embedding Decision Trees and Random Forests in Constraint Programming, file e1dcb32e-27d5-7715-e053-1705fe0a6cc9
|
1
|
|
null, file e1dcb331-1542-7715-e053-1705fe0a6cc9
|
1
|
|
From Offline to Online Kidney Exchange Optimization, file e1dcb331-9fa1-7715-e053-1705fe0a6cc9
|
1
|
|
How to Tame Your Anticipatory Algorithm, file e1dcb334-308f-7715-e053-1705fe0a6cc9
|
1
|
|
Combining learning and optimization for transprecision computing, file e1dcb335-ecf0-7715-e053-1705fe0a6cc9
|
1
|
|
Empirical decision model learning, file e1dcb338-7833-7715-e053-1705fe0a6cc9
|
1
|
|
Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem, file fedce2ba-a576-499e-b8e8-fb7ab85f7459
|
1
|
| Totale |
2.307 |