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DSAA 2018 : 2018 IEEE 5th International Conference on Data Science and Advanced Analytics : proceedings : 1-4 October 2018, Turin, Italy / / edited by Francesco Bonchi [and five others] ; sponsored by IEEE Computer Society
| DSAA 2018 : 2018 IEEE 5th International Conference on Data Science and Advanced Analytics : proceedings : 1-4 October 2018, Turin, Italy / / edited by Francesco Bonchi [and five others] ; sponsored by IEEE Computer Society |
| Pubbl/distr/stampa | Los Alamitos, California : , : IEEE Computer Society, , 2018 |
| Descrizione fisica | 1 online resource (698 pages) |
| Disciplina | 005.74 |
| Soggetto topico |
Database management
Data mining |
| ISBN | 1-5386-5090-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910309946303321 |
| Los Alamitos, California : , : IEEE Computer Society, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
DSAA 2018 : 2018 IEEE 5th International Conference on Data Science and Advanced Analytics : proceedings : 1-4 October 2018, Turin, Italy / / edited by Francesco Bonchi [and five others] ; sponsored by IEEE Computer Society
| DSAA 2018 : 2018 IEEE 5th International Conference on Data Science and Advanced Analytics : proceedings : 1-4 October 2018, Turin, Italy / / edited by Francesco Bonchi [and five others] ; sponsored by IEEE Computer Society |
| Pubbl/distr/stampa | Los Alamitos, California : , : IEEE Computer Society, , 2018 |
| Descrizione fisica | 1 online resource (698 pages) |
| Disciplina | 005.74 |
| Soggetto topico |
Database management
Data mining |
| ISBN | 1-5386-5090-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996575608803316 |
| Los Alamitos, California : , : IEEE Computer Society, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Knowledge Discovery in Inductive Databases [[electronic resource] ] : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut
| Knowledge Discovery in Inductive Databases [[electronic resource] ] : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (VIII, 252 p.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data structures (Computer science)
Database management Artificial intelligence Data Structures and Information Theory Database Management Artificial Intelligence |
| ISBN | 3-540-33293-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Data Mining in Inductive Databases -- Mining Databases and Data Streams with Query Languages and Rules -- Contributed Papers -- Memory-Aware Frequent k-Itemset Mining -- Constraint-Based Mining of Fault-Tolerant Patterns from Boolean Data -- Experiment Databases: A Novel Methodology for Experimental Research -- Quick Inclusion-Exclusion -- Towards Mining Frequent Queries in Star Schemes -- Inductive Databases in the Relational Model: The Data as the Bridge -- Transaction Databases, Frequent Itemsets, and Their Condensed Representations -- Multi-class Correlated Pattern Mining -- Shaping SQL-Based Frequent Pattern Mining Algorithms -- Exploiting Virtual Patterns for Automatically Pruning the Search Space -- Constraint Based Induction of Multi-objective Regression Trees -- Learning Predictive Clustering Rules. |
| Record Nr. | UNISA-996466100803316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Knowledge Discovery in Inductive Databases : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut
| Knowledge Discovery in Inductive Databases : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (VIII, 252 p.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data structures (Computer science)
Database management Artificial intelligence Data Structures and Information Theory Database Management Artificial Intelligence |
| ISBN | 3-540-33293-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Data Mining in Inductive Databases -- Mining Databases and Data Streams with Query Languages and Rules -- Contributed Papers -- Memory-Aware Frequent k-Itemset Mining -- Constraint-Based Mining of Fault-Tolerant Patterns from Boolean Data -- Experiment Databases: A Novel Methodology for Experimental Research -- Quick Inclusion-Exclusion -- Towards Mining Frequent Queries in Star Schemes -- Inductive Databases in the Relational Model: The Data as the Bridge -- Transaction Databases, Frequent Itemsets, and Their Condensed Representations -- Multi-class Correlated Pattern Mining -- Shaping SQL-Based Frequent Pattern Mining Algorithms -- Exploiting Virtual Patterns for Automatically Pruning the Search Space -- Constraint Based Induction of Multi-objective Regression Trees -- Learning Predictive Clustering Rules. |
| Record Nr. | UNINA-9910484571103321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXX, 866 p. 463 illus., 192 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Optical data processing Application software Computers Data protection Artificial Intelligence Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Computing Milieux Security |
| ISBN | 3-030-10928-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Graphs -- Temporally Evolving Community Detection and Prediction in Content-Centric Networks -- Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies -- Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery -- Dynamic hierarchies in temporal directed networks -- Risk-Averse Matchings over Uncertain Graph Databases -- Discovering Urban Travel Demands through Dynamic Zone Correlation in Location-Based Social Networks -- Social-Affiliation Networks: Patterns and the SOAR Model -- ONE-M: Modeling the Co-evolution of Opinions and Network Connections -- Think before You Discard: Accurate Triangle Counting in Graph Streams with Deletions -- Semi-Supervised Blockmodelling with Pairwise Guidance -- Kernel Methods -- Large-scale Nonlinear Variable Selection via Kernel Random Features -- Fast and Provably Effective Multi-view Classification with Landmark-based SVM -- Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent -- Learning Paradigms -- Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds -- Deep Learning Architecture Search by Neuro-Cell-based Evolution with Function-Preserving Mutations -- VC-Dimension Based Generalization Bounds for Relational Learning -- Robust Super-Level Set Estimation using Gaussian Processes -- Robust Super-Level Set Estimation using Gaussian Processes -- Scalable Nonlinear AUC Maximization Methods -- Matrix and Tensor Analysis -- Lambert Matrix Factorization -- Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition -- MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds -- Block CUR: Decomposing Matrices using Groups of Columns -- Online and Active Learning -- SpectralLeader: Online Spectral Learning for Single Topic Models -- Online Learning of Weighted Relational Rules for Complex Event Recognition -- Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees -- Online Feature Selection by Adaptive Sub-gradient Methods -- Frame-based Optimal Design -- Hierarchical Active Learning with Proportion Feedback on Regions -- Pattern and Sequence Mining -- An Efficient Algorithm for Computing Entropic Measures of Feature Subsets -- Anytime Subgroup Discovery in Numerical Domains with Guarantees -- Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics -- Mining Periodic Patterns with a MDL Criterion -- Revisiting Conditional Functional Dependency Discovery: Splitting the “C" from the “FD" -- Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint -- Mining Tree Patterns with Partially Injective Homomorphisms -- Probabilistic Models and Statistical Methods -- Variational Bayes for Mixture Models with Censored Data -- Exploration Enhanced Expected Improvement for Bayesian Optimization -- A Left-to-right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis -- Causal Inference on Multivariate and Mixed-Type Data -- Recommender Systems -- POLAR: Attention-based CNN for One-shot Personalized Article Recommendation -- Learning Multi-granularity Dynamic Network Representations for Social Recommendation -- GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-based Social Networks -- Personalized Thread Recommendation for MOOC Discussion Forums -- Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation -- Transfer Learning -- Feature Selection for Unsupervised Domain Adaptation using Optimal Transport -- Towards more Reliable Transfer Learning -- Differentially Private Hypothesis Transfer Learning -- Information-theoretic Transfer Learning framework for Bayesian Optimisation -- A Unified Framework for Domain Adaptation using Metric Learning on Manifolds. |
| Record Nr. | UNISA-996466463803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 740 p. 451 illus., 159 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Optical data processing Application software Computers Data protection Artificial Intelligence Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Computing Milieux Security |
| ISBN | 3-030-10925-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adversarial Learning -- Image Anomaly Detection with Generative Adversarial Networks -- Image-to-Markup Generation via Paired Adversarial Learning -- Toward an Understanding of Adversarial Examples in Clinical Trials -- ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector -- Anomaly and Outlier Detection -- GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid -- Incorporating Privileged Information to Unsupervised Anomaly Detection -- L1-Depth Revisited: A Robust Angle-based Outlier Factor in High-dimensional Space -- Beyond Outlier Detection: LookOut for Pictorial Explanation -- Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier Features -- Group Anomaly Detection using Deep Generative Models -- Applications -- A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements -- Face-Cap: Image Captioning using Facial Expression Analysis -- Pedestrian Trajectory Prediction with Structured Memory Hierarchies -- Classification -- Multiple Instance Learning with Bag-level Randomized Trees -- One-class Quantification -- Deep F-Measure Maximization in Multi-Label Classification: A Comparative Study -- Ordinal Label Proportions -- AWX: An Integrated Approach to Hierarchical-Multilabel Classification -- Clustering and Unsupervised Learning -- Clustering in the Presence of Concept Drift -- Time Warp Invariant Dictionary Learning for Time Series Clustering -- How Your Supporters and Opponents Define Your Interestingness -- Deep Learning -- Efficient Decentralized Deep Learning by Dynamic Model Averaging -- Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems -- Towards Efficient Forward Propagation on Resource-Constrained Systems -- Auxiliary Guided Autoregressive Variational Autoencoders -- Cooperative Multi-Agent Policy Gradient -- Parametric t-Distributed Stochastic Exemplar-centered Embedding -- Joint autoencoders: a flexible meta-learning framework -- Privacy Preserving Synthetic Data Release Using Deep Learning -- On Finer Control of Information Flow in LSTMs -- MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes -- Ontology alignment based on word embedding and random forest classification -- Domain Adaption in One-Shot Learning -- Ensemble Methods -- Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure -- Modular Dimensionality Reduction -- Constructive Aggregation and its Application to Forecasting with Dynamic Ensembles -- MetaBags: Bagged Meta-Decision Trees for Regression -- Evaluation -- Visualizing the Feature Importance for Black Box Models -- Efficient estimation of AUC in a sliding window -- Controlling and visualizing the precision-recall tradeoff for external performance indices -- Evaluation Procedures for Forecasting with Spatio-Temporal Data -- A Blended Metric for Multi-label Optimisation and Evaluation. |
| Record Nr. | UNISA-996466463503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXX, 866 p. 463 illus., 192 illus. in color.) |
| Disciplina |
006.3
006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Optical data processing Application software Computers Data protection Artificial Intelligence Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Computing Milieux Security |
| ISBN | 3-030-10928-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Graphs -- Temporally Evolving Community Detection and Prediction in Content-Centric Networks -- Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies -- Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery -- Dynamic hierarchies in temporal directed networks -- Risk-Averse Matchings over Uncertain Graph Databases -- Discovering Urban Travel Demands through Dynamic Zone Correlation in Location-Based Social Networks -- Social-Affiliation Networks: Patterns and the SOAR Model -- ONE-M: Modeling the Co-evolution of Opinions and Network Connections -- Think before You Discard: Accurate Triangle Counting in Graph Streams with Deletions -- Semi-Supervised Blockmodelling with Pairwise Guidance -- Kernel Methods -- Large-scale Nonlinear Variable Selection via Kernel Random Features -- Fast and Provably Effective Multi-view Classification with Landmark-based SVM -- Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent -- Learning Paradigms -- Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds -- Deep Learning Architecture Search by Neuro-Cell-based Evolution with Function-Preserving Mutations -- VC-Dimension Based Generalization Bounds for Relational Learning -- Robust Super-Level Set Estimation using Gaussian Processes -- Robust Super-Level Set Estimation using Gaussian Processes -- Scalable Nonlinear AUC Maximization Methods -- Matrix and Tensor Analysis -- Lambert Matrix Factorization -- Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition -- MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds -- Block CUR: Decomposing Matrices using Groups of Columns -- Online and Active Learning -- SpectralLeader: Online Spectral Learning for Single Topic Models -- Online Learning of Weighted Relational Rules for Complex Event Recognition -- Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees -- Online Feature Selection by Adaptive Sub-gradient Methods -- Frame-based Optimal Design -- Hierarchical Active Learning with Proportion Feedback on Regions -- Pattern and Sequence Mining -- An Efficient Algorithm for Computing Entropic Measures of Feature Subsets -- Anytime Subgroup Discovery in Numerical Domains with Guarantees -- Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics -- Mining Periodic Patterns with a MDL Criterion -- Revisiting Conditional Functional Dependency Discovery: Splitting the “C" from the “FD" -- Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint -- Mining Tree Patterns with Partially Injective Homomorphisms -- Probabilistic Models and Statistical Methods -- Variational Bayes for Mixture Models with Censored Data -- Exploration Enhanced Expected Improvement for Bayesian Optimization -- A Left-to-right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis -- Causal Inference on Multivariate and Mixed-Type Data -- Recommender Systems -- POLAR: Attention-based CNN for One-shot Personalized Article Recommendation -- Learning Multi-granularity Dynamic Network Representations for Social Recommendation -- GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-based Social Networks -- Personalized Thread Recommendation for MOOC Discussion Forums -- Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation -- Transfer Learning -- Feature Selection for Unsupervised Domain Adaptation using Optimal Transport -- Towards more Reliable Transfer Learning -- Differentially Private Hypothesis Transfer Learning -- Information-theoretic Transfer Learning framework for Bayesian Optimisation -- A Unified Framework for Domain Adaptation using Metric Learning on Manifolds. |
| Record Nr. | UNINA-9910337584103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I / / edited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 740 p. 451 illus., 159 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Optical data processing Application software Computers Data protection Artificial Intelligence Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Computing Milieux Security |
| ISBN | 3-030-10925-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adversarial Learning -- Image Anomaly Detection with Generative Adversarial Networks -- Image-to-Markup Generation via Paired Adversarial Learning -- Toward an Understanding of Adversarial Examples in Clinical Trials -- ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector -- Anomaly and Outlier Detection -- GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid -- Incorporating Privileged Information to Unsupervised Anomaly Detection -- L1-Depth Revisited: A Robust Angle-based Outlier Factor in High-dimensional Space -- Beyond Outlier Detection: LookOut for Pictorial Explanation -- Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier Features -- Group Anomaly Detection using Deep Generative Models -- Applications -- A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements -- Face-Cap: Image Captioning using Facial Expression Analysis -- Pedestrian Trajectory Prediction with Structured Memory Hierarchies -- Classification -- Multiple Instance Learning with Bag-level Randomized Trees -- One-class Quantification -- Deep F-Measure Maximization in Multi-Label Classification: A Comparative Study -- Ordinal Label Proportions -- AWX: An Integrated Approach to Hierarchical-Multilabel Classification -- Clustering and Unsupervised Learning -- Clustering in the Presence of Concept Drift -- Time Warp Invariant Dictionary Learning for Time Series Clustering -- How Your Supporters and Opponents Define Your Interestingness -- Deep Learning -- Efficient Decentralized Deep Learning by Dynamic Model Averaging -- Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems -- Towards Efficient Forward Propagation on Resource-Constrained Systems -- Auxiliary Guided Autoregressive Variational Autoencoders -- Cooperative Multi-Agent Policy Gradient -- Parametric t-Distributed Stochastic Exemplar-centered Embedding -- Joint autoencoders: a flexible meta-learning framework -- Privacy Preserving Synthetic Data Release Using Deep Learning -- On Finer Control of Information Flow in LSTMs -- MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes -- Ontology alignment based on word embedding and random forest classification -- Domain Adaption in One-Shot Learning -- Ensemble Methods -- Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure -- Modular Dimensionality Reduction -- Constructive Aggregation and its Application to Forecasting with Dynamic Ensembles -- MetaBags: Bagged Meta-Decision Trees for Regression -- Evaluation -- Visualizing the Feature Importance for Black Box Models -- Efficient estimation of AUC in a sliding window -- Controlling and visualizing the precision-recall tradeoff for external performance indices -- Evaluation Procedures for Forecasting with Spatio-Temporal Data -- A Blended Metric for Multi-label Optimisation and Evaluation. |
| Record Nr. | UNINA-9910337583903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 345 p. 122 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-23461-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996200360203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 345 p. 122 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-23461-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483879403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
