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Analysis of Experimental Algorithms [[electronic resource] ] : Special Event, SEA² 2019, Kalamata, Greece, June 24-29, 2019, Revised Selected Papers / / edited by Ilias Kotsireas, Panos Pardalos, Konstantinos E. Parsopoulos, Dimitris Souravlias, Arsenis Tsokas
| Analysis of Experimental Algorithms [[electronic resource] ] : Special Event, SEA² 2019, Kalamata, Greece, June 24-29, 2019, Revised Selected Papers / / edited by Ilias Kotsireas, Panos Pardalos, Konstantinos E. Parsopoulos, Dimitris Souravlias, Arsenis Tsokas |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 564 p. 462 illus., 125 illus. in color.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science—Mathematics Artificial intelligence—Data processing Artificial intelligence Computer graphics Mathematics of Computing Data Science Artificial Intelligence Computer Graphics |
| ISBN | 3-030-34029-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466423403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Analysis of Experimental Algorithms : Special Event, SEA² 2019, Kalamata, Greece, June 24-29, 2019, Revised Selected Papers / / edited by Ilias Kotsireas, Panos Pardalos, Konstantinos E. Parsopoulos, Dimitris Souravlias, Arsenis Tsokas
| Analysis of Experimental Algorithms : Special Event, SEA² 2019, Kalamata, Greece, June 24-29, 2019, Revised Selected Papers / / edited by Ilias Kotsireas, Panos Pardalos, Konstantinos E. Parsopoulos, Dimitris Souravlias, Arsenis Tsokas |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 564 p. 462 illus., 125 illus. in color.) |
| Disciplina |
005.1
005.13 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science—Mathematics Artificial intelligence—Data processing Artificial intelligence Computer graphics Mathematics of Computing Data Science Artificial Intelligence Computer Graphics |
| ISBN | 3-030-34029-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910357850303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Discrete Optimization and Operations Research [[electronic resource] ] : 9th International Conference, DOOR 2016, Vladivostok, Russia, September 19-23, 2016, Proceedings / / edited by Yury Kochetov, Michael Khachay, Vladimir Beresnev, Evgeni Nurminski, Panos Pardalos
| Discrete Optimization and Operations Research [[electronic resource] ] : 9th International Conference, DOOR 2016, Vladivostok, Russia, September 19-23, 2016, Proceedings / / edited by Yury Kochetov, Michael Khachay, Vladimir Beresnev, Evgeni Nurminski, Panos Pardalos |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXVI, 586 p. 58 illus.) |
| Disciplina | 519.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Numerical analysis Computer science—Mathematics Discrete mathematics Mathematical optimization Artificial intelligence Computer networks Numerical Analysis Discrete Mathematics in Computer Science Optimization Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-44914-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited talks -- discrete optimization -- scheduling problems -- facility location -- mathematical programming -- mathematical economics and games -- applications of operational research -- short communications. . |
| Record Nr. | UNISA-996465645303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Discrete Optimization and Operations Research : 9th International Conference, DOOR 2016, Vladivostok, Russia, September 19-23, 2016, Proceedings / / edited by Yury Kochetov, Michael Khachay, Vladimir Beresnev, Evgeni Nurminski, Panos Pardalos
| Discrete Optimization and Operations Research : 9th International Conference, DOOR 2016, Vladivostok, Russia, September 19-23, 2016, Proceedings / / edited by Yury Kochetov, Michael Khachay, Vladimir Beresnev, Evgeni Nurminski, Panos Pardalos |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXVI, 586 p. 58 illus.) |
| Disciplina | 519.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Numerical analysis Computer science—Mathematics Discrete mathematics Mathematical optimization Artificial intelligence Computer networks Numerical Analysis Discrete Mathematics in Computer Science Optimization Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-44914-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited talks -- discrete optimization -- scheduling problems -- facility location -- mathematical programming -- mathematical economics and games -- applications of operational research -- short communications. . |
| Record Nr. | UNINA-9910483363003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Retrieval : 9th Russian Summer School, RuSSIR 2015, Saint Petersburg, Russia, August 24-28, 2015, Revised Selected Papers / / edited by Pavel Braslavski, Ilya Markov, Panos Pardalos, Yana Volkovich, Dmitry I. Ignatov, Sergei Koltsov, Olessia Koltsova
| Information Retrieval : 9th Russian Summer School, RuSSIR 2015, Saint Petersburg, Russia, August 24-28, 2015, Revised Selected Papers / / edited by Pavel Braslavski, Ilya Markov, Panos Pardalos, Yana Volkovich, Dmitry I. Ignatov, Sergei Koltsov, Olessia Koltsova |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XX, 187 p. 40 illus.) |
| Disciplina | 025.04 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Information storage and retrieval
Data mining Natural language processing (Computer science) Artificial intelligence Application software Information Storage and Retrieval Data Mining and Knowledge Discovery Natural Language Processing (NLP) Artificial Intelligence Information Systems Applications (incl. Internet) |
| ISBN | 3-319-41718-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | IR and theory and models -- Social networks and graph analysis -- Crowdsourcing systems and social media -- Data structures, algorithms, and indexing -- Web search systems and Web mining -- Semantic Web and knowledge databases -- Natural language processing. |
| Record Nr. | UNINA-9910767514403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning and Intelligent Optimization [[electronic resource] ] : 13th International Conference, LION 13, Chania, Crete, Greece, May 27–31, 2019, Revised Selected Papers / / edited by Nikolaos F. Matsatsinis, Yannis Marinakis, Panos Pardalos
| Learning and Intelligent Optimization [[electronic resource] ] : 13th International Conference, LION 13, Chania, Crete, Greece, May 27–31, 2019, Revised Selected Papers / / edited by Nikolaos F. Matsatsinis, Yannis Marinakis, Panos Pardalos |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XIII, 400 p. 98 illus., 49 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Mathematics—Data processing
Algorithms Computer networks Computer systems Application software Data structures (Computer science) Information theory Computational Mathematics and Numerical Analysis Computer Communication Networks Computer System Implementation Computer and Information Systems Applications Data Structures and Information Theory |
| ISBN | 3-030-38629-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine learning -- Artificial Intelligence -- Machine learning approaches -- Bio-inspired optimization -- Optimization with randomized search heuristics -- Evolutionary algorithms -- Continuous optimization -- Mathematical optimization -- Routing and network design problems -- Supervised learning -- Unsupervised learning -- Reinforcement learning -- Planning and scheduling -- Distributed artificial intelligence -- Multi-agent systems -- Intelligent agents. |
| Record Nr. | UNISA-996418204103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Learning and Intelligent Optimization : 13th International Conference, LION 13, Chania, Crete, Greece, May 27–31, 2019, Revised Selected Papers / / edited by Nikolaos F. Matsatsinis, Yannis Marinakis, Panos Pardalos
| Learning and Intelligent Optimization : 13th International Conference, LION 13, Chania, Crete, Greece, May 27–31, 2019, Revised Selected Papers / / edited by Nikolaos F. Matsatsinis, Yannis Marinakis, Panos Pardalos |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XIII, 400 p. 98 illus., 49 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Mathematics—Data processing
Algorithms Computer networks Computer systems Application software Data structures (Computer science) Information theory Computational Mathematics and Numerical Analysis Computer Communication Networks Computer System Implementation Computer and Information Systems Applications Data Structures and Information Theory |
| ISBN | 3-030-38629-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine learning -- Artificial Intelligence -- Machine learning approaches -- Bio-inspired optimization -- Optimization with randomized search heuristics -- Evolutionary algorithms -- Continuous optimization -- Mathematical optimization -- Routing and network design problems -- Supervised learning -- Unsupervised learning -- Reinforcement learning -- Planning and scheduling -- Distributed artificial intelligence -- Multi-agent systems -- Intelligent agents. |
| Record Nr. | UNINA-9910481953803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning and Intelligent Optimization [[electronic resource] ] : 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos
| Learning and Intelligent Optimization [[electronic resource] ] : 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XV, 470 p. 120 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Numerical analysis Artificial intelligence Computer science—Mathematics Discrete mathematics Computer science Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Theory of Computation |
| ISBN | 3-642-44973-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence -- Intelligent optimization for the minimum labelling spanning tree problem -- A Constraint Satisfaction Approach to Tractable Theory Induction -- Features for Exploiting Black-Box Optimization Problem Structure -- MOCA-I: Discovering Rules and Guiding Decision Maker in the Context of Partial Classification in Large and Imbalanced Datasets -- Sharing Information in Parallel Search with Search Space Partitioning -- Fast Computation of the Multi-points Expected Improvement with Applications in Batch Selection -- R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection -- A Heuristic Algorithm for the Set Multicover Problem with Generalized Upper Bound Constraints -- A genetic algorithm approach for the multidimensional two-way number partitioning problem -- Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search -- Multi-objective optimization for relevant sub-graph extraction -- PROGRESS: Progressive Reinforcement-Learning-Based Surrogate Selection -- Neutrality in the Graph Coloring Problem -- Kernel multi label vector optimization (kMLVO) - A unified multi-label classification formalism -- Robust Benchmark Set Selection for Boolean Constraint Solvers -- Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction -- A Fast and Adaptive Local Search Algorithm for Multi-Objective Optimization -- An Analysis of Hall-of-Fame Strategies in Competitive Coevolutionary Algorithms for Self-Learning in RTS Games -- Resources Optimization in (Video) Games: a Novel Approach to Teach Applied Mathematics -- CMF: a combinatorial tool to find composite motifs -- Hill-climbing Behaviour on Quantized NK-landscapes -- Neighbourhood Specification for Game Strategy Evolution in a Spatial Iterated Prisoners Dilemma Game -- A Study on the Specification of a Scalarizing Function in MOEA/D for Many-Objective Knapsack Problems -- Portfolio with Block Branching for Parallel SAT Solvers -- Parameter Setting with Dynamic Island Models -- A simulated annealing algorithm for the vehicle routing problem with time windows and synchronization constraints -- Solution of the maximum k-balanced subgraph problem -- Racing with a Fixed Budget and a Self-Adaptive Significance Level -- An efficient best response heuristic for a non-preemptive strictly periodic scheduling problem -- Finding an evolutionary solution to the game of Mastermind with good scaling behaviour -- A Fast Local Search Approach For Multiobjective problems -- Generating Customized Landscapes in Permutation-based Combinatorial Optimization Problems -- Multiobjective Evolution of Mixed Nash Equilibria -- Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop problem -- From Grammars to Parameters: Automatic Iterated Greedy Design for the Permutation Flow-shop Problem with Weighted Tardiness -- Architecture for Monitoring Learning Processes using Video Games -- Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning -- Evolutionary FSM-Based Agents for Playing Super Mario Game -- Identifying Key Algorithm Parameters and Instance Features using Forward Selection -- Using Racing to Automatically Configure Algorithms for Scaling Performance -- Algorithm Selection for the Graph Coloring Problem -- Batched Mode Hyper-heuristics -- Tuning algorithms for tackling large instances: An experimental protocol -- Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case Study in Quadratic Assignment Problem -- Practically Desirable Solutions Search on Multi-Objective Optimization -- Oversized Populations and Cooperative Selection: Dealing with Massive Resources in Parallel Infrastructures -- Effects of Population Size on Selection and Scalability in Evolutionary Many-objective Optimization -- A novel feature selection method for classification using a fuzzy criterion. |
| Record Nr. | UNISA-996465649703316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Learning and Intelligent Optimization : 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos
| Learning and Intelligent Optimization : 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XV, 470 p. 120 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Numerical analysis Artificial intelligence Computer science—Mathematics Discrete mathematics Computer science Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Theory of Computation |
| ISBN | 3-642-44973-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence -- Intelligent optimization for the minimum labelling spanning tree problem -- A Constraint Satisfaction Approach to Tractable Theory Induction -- Features for Exploiting Black-Box Optimization Problem Structure -- MOCA-I: Discovering Rules and Guiding Decision Maker in the Context of Partial Classification in Large and Imbalanced Datasets -- Sharing Information in Parallel Search with Search Space Partitioning -- Fast Computation of the Multi-points Expected Improvement with Applications in Batch Selection -- R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection -- A Heuristic Algorithm for the Set Multicover Problem with Generalized Upper Bound Constraints -- A genetic algorithm approach for the multidimensional two-way number partitioning problem -- Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search -- Multi-objective optimization for relevant sub-graph extraction -- PROGRESS: Progressive Reinforcement-Learning-Based Surrogate Selection -- Neutrality in the Graph Coloring Problem -- Kernel multi label vector optimization (kMLVO) - A unified multi-label classification formalism -- Robust Benchmark Set Selection for Boolean Constraint Solvers -- Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction -- A Fast and Adaptive Local Search Algorithm for Multi-Objective Optimization -- An Analysis of Hall-of-Fame Strategies in Competitive Coevolutionary Algorithms for Self-Learning in RTS Games -- Resources Optimization in (Video) Games: a Novel Approach to Teach Applied Mathematics -- CMF: a combinatorial tool to find composite motifs -- Hill-climbing Behaviour on Quantized NK-landscapes -- Neighbourhood Specification for Game Strategy Evolution in a Spatial Iterated Prisoners Dilemma Game -- A Study on the Specification of a Scalarizing Function in MOEA/D for Many-Objective Knapsack Problems -- Portfolio with Block Branching for Parallel SAT Solvers -- Parameter Setting with Dynamic Island Models -- A simulated annealing algorithm for the vehicle routing problem with time windows and synchronization constraints -- Solution of the maximum k-balanced subgraph problem -- Racing with a Fixed Budget and a Self-Adaptive Significance Level -- An efficient best response heuristic for a non-preemptive strictly periodic scheduling problem -- Finding an evolutionary solution to the game of Mastermind with good scaling behaviour -- A Fast Local Search Approach For Multiobjective problems -- Generating Customized Landscapes in Permutation-based Combinatorial Optimization Problems -- Multiobjective Evolution of Mixed Nash Equilibria -- Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop problem -- From Grammars to Parameters: Automatic Iterated Greedy Design for the Permutation Flow-shop Problem with Weighted Tardiness -- Architecture for Monitoring Learning Processes using Video Games -- Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning -- Evolutionary FSM-Based Agents for Playing Super Mario Game -- Identifying Key Algorithm Parameters and Instance Features using Forward Selection -- Using Racing to Automatically Configure Algorithms for Scaling Performance -- Algorithm Selection for the Graph Coloring Problem -- Batched Mode Hyper-heuristics -- Tuning algorithms for tackling large instances: An experimental protocol -- Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case Study in Quadratic Assignment Problem -- Practically Desirable Solutions Search on Multi-Objective Optimization -- Oversized Populations and Cooperative Selection: Dealing with Massive Resources in Parallel Infrastructures -- Effects of Population Size on Selection and Scalability in Evolutionary Many-objective Optimization -- A novel feature selection method for classification using a fuzzy criterion. |
| Record Nr. | UNINA-9910483941803321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Big Data [[electronic resource] ] : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
| Machine Learning, Optimization, and Big Data [[electronic resource] ] : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXI, 600 p. 154 illus.) |
| Disciplina | 006.31 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Application software
Artificial intelligence Algorithms Data mining Computer science—Mathematics Computer organization Information Systems Applications (incl. Internet) Artificial Intelligence Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery Mathematics of Computing Computer Systems Organization and Communication Networks |
| ISBN | 3-319-72926-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Cellular Networks -- 2.2 Modeling Approach -- 2.3 Framework Overview -- 3 Model Representation Format -- 4 From Reading to Model -- 4.1 Simple Interaction Translation -- 4.2 Translation of Translocation Interaction -- 4.3 Translation of Complexes -- 4.4 Translation of Nested Interactions -- 4.5 Translation of Direct and Indirect Interactions -- 4.6 Translation from Table Reading Output -- 5 Matching Reading and Modeling -- 5.1 Protein Families -- 5.2 Cell Type -- 5.3 Cellular Location -- 5.4 Contradicting Interaction Type -- 5.5 Negative Information -- 6 Case Study -- 7 Conclusion -- References -- Improving Support Vector Machines Performance Using Local Search -- 1 Introduction -- 2 Support Vector Machines -- 3 Iterated Local Search -- 4 Our ILS Method for SVM Parameters Tuning -- 5 Experimental Analysis -- 6 Conclusions and Future Research -- References -- Projective Approximation Based Quasi-Newton Methods -- 1 Introduction -- 2 Preliminaries -- 2.1 Notation Remarks -- 2.2 Quadratic Response Surface Methodology -- 2.3 Quasi-Newton Optimization Methods -- 3 Algorithm Descriptions -- 4 Theoretical Ground -- 5 Modelling -- 6 Conclusion -- A Proofs -- References -- Intra-feature Random Forest Clustering -- Abstract -- 1 Introduction -- 2 The Algorithm -- 3 Performance Evaluation -- 4 Conclusions -- References -- Dolphin Pod Optimization -- 1 Introduction -- 2 Dolphin Pod Optimization -- 3 DPO Setting Parameters -- 4 Performance Metrics -- 5 Numerical Results -- 5.1 Analytical Benchmark Functions -- 5.2 Hull-Form SBD Optimization Problem -- 6 Conclusions and Future Work -- References -- Contraction Clustering (RASTER) -- 1 Introduction -- 2 Problem Description.
2.1 The Clustering Problem -- 2.2 Motivating Use Case -- 2.3 Limitations of Common Clustering Methods -- 3 RASTER -- 3.1 High-Level Description -- 3.2 Tiles and RASTER Clusters -- 3.3 The Algorithm -- 3.4 Parallel RASTER -- 3.5 Generalizing to Higher Dimensions -- 3.6 Minimum Cluster Size in Disadvantageous Grid Layouts -- 4 Results -- 4.1 Ideal Data -- 4.2 Sample Datasets -- 4.3 Empirical Runtime -- 5 Related Work -- 6 Future Work -- References -- Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic Optimization Algorithms -- 1 Introduction -- 2 Related Work -- 3 Deep Statistical Comparison -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 First Experiment -- 4.3 Second Experiment -- 5 Conclusion -- References -- On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis -- 1 Introduction -- 1.1 A Nash Equilibrium Approach to Metabolic Pathways -- 1.2 Element Mass Balances and Charge Balancing -- 2 Explicitly Incorporating Enzyme-Substrate Reactions -- 2.1 Enzyme-Substrate Reactions -- 2.2 An Example of Binding and Unbinding Reactions -- 2.3 Multiple Minima from Protein Docking -- 2.4 A Multi-scale Methodology for Including Enzyme-Substrate Reactions -- 2.5 Enzyme Activity -- 3 Numerical Results -- 4 Conclusions -- References -- A Comparative Study on Term Weighting Schemes for Text Classification -- 1 Introduction -- 2 Text Classification -- 3 Classifiers -- 4 Results and Discussion -- 4.1 Experiments -- 4.2 Evaluation -- 4.3 Results -- 5 Conclusion -- References -- Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces -- 1 Introduction -- 2 Greedy Algorithms -- 3 Primal Convergence Results -- 4 Duality Gap and Convergence Result -- 5 Conclusion -- References -- Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization. 1 Introduction -- 2 Dimensionality Reduction Methods -- 2.1 General Definitions and Assumptions -- 2.2 Principal Component Analysis -- 2.3 Kernel Principal Component Analysis -- 2.4 Local Principal Component Analysis -- 2.5 Deep Autoencoders -- 3 Shape Modification of a Destroyer Hull -- 4 Numerical Results -- 4.1 Evaluation Metrics -- 4.2 Evaluation of Design-Space Dimensionality Reduction Capabilities -- 5 Conclusions and Future Work -- References -- A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner's Dilemma -- 1 Introduction -- 2 Differential Evolution: A Short Overview -- 3 Prisoner's Dilemma -- 3.1 Iterated PD and Benchmark Strategies -- 4 DE Develops IPD Strategies -- 4.1 The DE Approach with Memory -- 5 IPD Experiments -- 6 Conclusions -- References -- Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Training Set Creation -- 3.2 Classification -- 3.3 Dataset Pruning -- 4 Results -- 4.1 Test Set -- 4.2 Accuracy -- 5 Conclusion -- References -- Forecasting Natural Gas Flows in Large Networks -- 1 Introduction -- 1.1 Literature Review -- 1.2 The Data Set -- 1.3 Input Features -- 1.4 The Network -- 1.5 Evaluation -- 2 Recurrent Neural Network (RNN) with Design of Experiments (DOE) and Simulated Annealing -- 2.1 The Experiment -- 2.2 Optimal Design with Simulated Annealing -- 3 Recurrent Neural Network (RNN) with Genetic Algorithm (GA) -- 4 Conclusion -- References -- A Differential Evolution Algorithm to Semivectorial Bilevel Problems -- Abstract -- 1 Introduction -- 2 The SVBLP: Optimistic vs. Pessimistic Approaches -- 3 Optimistic and Pessimistic Frontiers -- 4 A Differential Evolution Algorithm for the SVBLP -- 5 Computational Experiment -- 6 Conclusions -- Acknowledgment -- References. Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces -- 1 Introduction -- 2 Related Work on Transfer Learning in BCI -- 2.1 Ensembles -- 2.2 ELGI -- 3 Methodology -- 3.1 P300 Speller Paradigm -- 3.2 Dataset Recordings -- 3.3 Prefiltering -- 3.4 Classifier -- 3.5 Conditions -- 3.6 Compared Algorithms -- 4 Evolved ELGI Ensemble -- 5 Results -- 6 Discussion and Conclusion -- References -- Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm with Local Linesearch -- 1 Introduction -- 2 Optimization Problem Formulation -- 3 Performance Metrics -- 4 Hybrid Global/Local Deterministic Algorithm -- 4.1 MODPSO -- 4.2 DFMO -- 4.3 MODHA -- 4.4 Algorithm Parameters and Setup -- 5 Numerical Results -- 5.1 Analytical Benchmark Problems -- 5.2 High-Speed Catamaran Optimization -- 6 Conclusions and Future Work -- References -- Artificial Bee Colony Optimization to Reallocate Personnel to Tasks Improving Workplace Safety -- 1 Introduction -- 2 Multi-objective Optimization -- 2.1 Non-dominated Sorting Bee Colony Optimization -- 3 Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) -- 4 Worker's Risk Perception and Caution -- 5 Problem Formulation -- 5.1 Objectives -- 5.2 Problem Formulation -- 6 Experiments and Discussion -- 6.1 Dataset -- 6.2 Setup of the Parameters -- 6.3 Optimization Results -- 7 Conclusion -- References -- Multi-objective Genetic Algorithm for Interior Lighting Design -- 1 Introduction -- 2 The Inverse Lighting Problem -- 2.1 Blender as Direct Engine -- 3 Multi-objective Optimization -- 3.1 Previous Related Works -- 3.2 NSGA-II -- 3.3 Fitness Evaluation and Constraint Handling -- 4 The Proposed Strategy -- 5 Results -- 5.1 Art Gallery -- 5.2 Office -- 6 Conclusions -- References. An Elementary Approach to the Problem of Column Selection in a Rectangular Matrix -- 1 Introduction -- 1.1 Historical Background -- 1.2 Our Contribution -- 2 Proof of Theorem 1.5 -- 2.1 Suitable Choice of the Extracted Vectors -- 2.2 Controlling the Individual Eigenvalues -- 2.3 Controlling the Greatest Eigenvalue -- 2.4 Two Simple Examples -- 3 Computational Considerations -- 3.1 A Simple Algorithm -- 3.2 Scalability vs Accuracy -- 3.3 Extracting Representative Images from a Dataset -- 4 Conclusion -- References -- A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S3VMs -- 1 Introduction and Related Work -- 1.1 The Semi-supervised Scenario -- 1.2 Continuous vs Combinatorial Approach -- 2 Lagrangian S3VM -- 2.1 Dealing with Hyper-parameters -- 2.2 Balance Constraint as a Guide -- 2.3 Inductive vs Transductive S3VMs -- 2.4 Method Details -- 3 Experiments -- 3.1 Algorithms -- 3.2 Datasets -- 3.3 Model Selection -- 3.4 Experimental Results -- 3.5 Technical Details -- 4 Conclusion and Remarks -- References -- A Heuristic Based on Fuzzy Inference Systems for Multiobjective IMRT Treatment Planning -- Abstract -- 1 Introduction -- 2 Brief Review of the Literature -- 3 Multiobjective Optimization Problem -- 4 Heuristic Procedure Based on FIS -- 5 Illustration of the Application of the Procedure -- 6 Conclusions -- Acknowledgments -- References -- Data-Driven Machine Learning Approach for Predicting Missing Values in Large Data Sets: A Comparison ... -- Abstract -- 1 Introduction -- 2 Related Work -- 3 System Design -- 3.1 Data Source and Data Preparation -- 3.2 Methods for Imputation of Missing Values -- 4 Performance Measurements and Results -- 4.1 Algorithms Tuning -- 4.2 Evaluation Measures -- 4.3 Results and Considerations -- 5 Proposed Imputation Approach -- 6 Conclusions -- References. Mineral: Multi-modal Network Representation Learning. |
| Record Nr. | UNISA-996465494703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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