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Discovery Science [[electronic resource] ] : 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings / / edited by Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski
Discovery Science [[electronic resource] ] : 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings / / edited by Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (xxii, 546 pages) : illustrations
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Computers
Optical data processing
Software engineering
Artificial Intelligence
Data Mining and Knowledge Discovery
Theory of Computation
Computer Imaging, Vision, Pattern Recognition and Graphics
Software Engineering/Programming and Operating Systems
ISBN 3-030-33778-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Advanced Machine Learning -- Applications -- Data and Knowledge Representation -- Feature Importance -- Interpretable Machine Learning -- Networks -- Pattern Discovery -- Time Series.
Record Nr. UNISA-996466304603316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Discovery Science : 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings / / edited by Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski
Discovery Science : 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings / / edited by Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (xxii, 546 pages) : illustrations
Disciplina 006.3
501
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Computers
Optical data processing
Software engineering
Artificial Intelligence
Data Mining and Knowledge Discovery
Theory of Computation
Computer Imaging, Vision, Pattern Recognition and Graphics
Software Engineering/Programming and Operating Systems
ISBN 3-030-33778-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Advanced Machine Learning -- Applications -- Data and Knowledge Representation -- Feature Importance -- Interpretable Machine Learning -- Networks -- Pattern Discovery -- Time Series.
Record Nr. UNINA-9910349271503321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Discovery Science [[electronic resource] ] : 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014, Proceedings / / edited by Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski
Discovery Science [[electronic resource] ] : 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014, Proceedings / / edited by Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXII, 364 p. 111 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Information storage and retrieval
Database management
Algorithms
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Storage and Retrieval
Database Management
Algorithm Analysis and Problem Complexity
ISBN 3-319-11812-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix Visualization -- Big Data Analysis of StockTwits to Predict Sentiments in the Stock Market -- Synthetic Sequence Generator for Recommender Systems – Memory Biased Random Walk on a Sequence Multilayer Network -- Predicting Sepsis Severity from Limited Temporal Observations -- Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining -- Antipattern Discovery in Ethiopian Bagana Songs -- Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project -- Multilayer Clustering: A Discovery Experiment on Country Level Trading Data -- Medical Document Mining Combining Image Exploration and Text Characterization -- Mining Cohesive Itemsets in Graphs -- Mining Rank Data -- Link Prediction on the Semantic MEDLINE Network: An Approach to Literature-Based Discovery -- Medical Image Retrieval Using Multimodal Data -- Fast Computation of the Tree Edit Distance between Unordered Trees Using IP Solvers -- Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency -- Incremental Learning with Social Media Data to Predict Near Real-Time Events -- Stacking Label Features for Learning Multilabel Rules -- Selective Forgetting for Incremental Matrix Factorization in Recommender Systems -- Providing Concise Database Covers Instantly by Recursive Tile Sampling -- Resampling-Based Framework for Estimating Node Centrality of Large Social Network -- Detecting Maximum k-Plex with Iterative Proper l-Plex Search -- Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data -- Failure Prediction – An Application in the Railway Industry -- Wind Power Forecasting Using Time Series Cluster Analysis -- Feature Selection in Hierarchical Feature Spaces -- Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology -- An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths -- Algorithm Selection on Data Streams -- Sparse Coding for Key Node Selection over Networks -- Variational Dependent Multi-output Gaussian Process Dynamical Systems.
Record Nr. UNISA-996199681803316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Discovery Science : 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014, Proceedings / / edited by Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski
Discovery Science : 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014, Proceedings / / edited by Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXII, 364 p. 111 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Information storage and retrieval
Database management
Algorithms
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Storage and Retrieval
Database Management
Algorithm Analysis and Problem Complexity
ISBN 3-319-11812-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix Visualization -- Big Data Analysis of StockTwits to Predict Sentiments in the Stock Market -- Synthetic Sequence Generator for Recommender Systems – Memory Biased Random Walk on a Sequence Multilayer Network -- Predicting Sepsis Severity from Limited Temporal Observations -- Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining -- Antipattern Discovery in Ethiopian Bagana Songs -- Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project -- Multilayer Clustering: A Discovery Experiment on Country Level Trading Data -- Medical Document Mining Combining Image Exploration and Text Characterization -- Mining Cohesive Itemsets in Graphs -- Mining Rank Data -- Link Prediction on the Semantic MEDLINE Network: An Approach to Literature-Based Discovery -- Medical Image Retrieval Using Multimodal Data -- Fast Computation of the Tree Edit Distance between Unordered Trees Using IP Solvers -- Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency -- Incremental Learning with Social Media Data to Predict Near Real-Time Events -- Stacking Label Features for Learning Multilabel Rules -- Selective Forgetting for Incremental Matrix Factorization in Recommender Systems -- Providing Concise Database Covers Instantly by Recursive Tile Sampling -- Resampling-Based Framework for Estimating Node Centrality of Large Social Network -- Detecting Maximum k-Plex with Iterative Proper l-Plex Search -- Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data -- Failure Prediction – An Application in the Railway Industry -- Wind Power Forecasting Using Time Series Cluster Analysis -- Feature Selection in Hierarchical Feature Spaces -- Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology -- An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths -- Algorithm Selection on Data Streams -- Sparse Coding for Key Node Selection over Networks -- Variational Dependent Multi-output Gaussian Process Dynamical Systems.
Record Nr. UNINA-9910485145703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XXXIII, 866 p. 213 illus.)
Disciplina 006.31
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71246-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Pattern and Sequence Mining -- BeatLex: Summarizing and Forecasting Time Series with Patterns -- Behavioral Constraint Template-Based Sequence Classification -- Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space -- Subjectively Interesting Connecting Trees -- Privacy and Security -- Malware Detection by Analysing Encrypted Network Traffic with Neural Networks -- PEM: Practical Differentially Private System for Large-Scale Cross-Institutional Data Mining -- Probabilistic Models and Methods -- Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources -- Bayesian Inference for Least Squares Temporal Difference Regularization -- Discovery of Causal Models that Contain Latent Variables through Bayesian Scoring of Independence Constraints -- Labeled DBN learning with community structure knowledge -- Multi-view Generative Adversarial Networks -- Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models -- PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning Approach -- Partial Device Fingerprints -- Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies -- Recommendation -- A Regularization Method with Inference of Trust and Distrust in Recommender Systems -- A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations -- Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation -- Regression -- Adaptive Skip-Train Structured Regression for Temporal Networks -- ALADIN: A New Approach for Drug-Target Interaction Prediction -- Co-Regularised Support Vector Regression -- Online Regression with Controlled Label Noise Rate -- Reinforcement Learning -- Generalized Inverse Reinforcement Learning with Linearly Solvable MDP -- Max K-armed bandit: On the ExtremeHunter algorithm and beyond -- Variational Thompson Sampling for Relational Recurrent Bandits -- Subgroup Discovery -- Explaining Deviating Subsets through Explanation Networks -- Flash points: Discovering exceptional pairwise behaviors in vote or rating data -- Time Series and Streams -- A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching -- Arbitrated Ensemble for Time Series Forecasting -- Cost Sensitive Time-series Classification -- Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams -- Efficient Temporal Kernels between Feature Sets for Time Series Classification -- Forecasting and Granger modelling with non-linear dynamical dependencies -- Learning TSK Fuzzy Rules from Data Streams -- Non-Parametric Online AUC Maximization -- On-line Dynamic Time Warping for Streaming Time Series -- PowerCast: Mining and Forecasting Power Grid Sequences -- UAPD: Predicting Urban Anomalies from Spatial-Temporal Data -- Transfer and Multi-Task Learning -- A Novel Rating Pattern Transfer Model for Improving Non-Overlapping Cross-Domain Collaborative Filtering -- Distributed Multi-task Learning for Sensor Network -- Learning task structure via sparsity grouped multitask learning -- Lifelong Learning with Gaussian Processes -- Personalized Tag Recommendation for Images Using Deep Transfer Learning -- Ranking based Multitask Learning of Scoring Functions -- Theoretical Analysis of Domain Adaptation with Optimal Transport -- TSP: Learning Task-Speci_c Pivots for Unsupervised Domain Adaptation -- Unsupervised and Semisupervised Learning -- k2-means for fast and accurate large scale clustering -- A Simple Exponential Family Framework for Zero-Shot Learning -- DeepCluster: A General Clustering Framework based on Deep Learning -- Multi-view Spectral Clustering on Conflicting Views -- Pivot-based Distributed K-Nearest Neighbor Mining.
Record Nr. UNISA-996465751903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (LXIII, 852 p. 245 illus.)
Disciplina 006.31
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71249-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Anomaly Detection -- Concentration Free Outlier Detection -- Efficient top rank optimization with gradient boosting for supervised anomaly detection -- Robust, Deep and Inductive Anomaly Detection -- Sentiment Informed Cyberbullying Detection in Social Media -- zooRank: Ranking Suspicious Activities in Time-Evolving Tensors -- Computer Vision -- Alternative Semantic Representations for Zero-Shot Human Action Recognition -- Early Active Learning with Pairwise Constraint for Person Re-identification -- Guiding InfoGAN with Semi-Supervision -- Scatteract: Automated extraction of data from scatter plots -- Unsupervised Diverse Colorization via Generative Adversarial Networks -- Ensembles and Meta Learning -- Dynamic Ensemble Selection with Probabilistic Classifier Chains -- Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks -- Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks -- Feature Selection and Extraction -- Deep Discrete Hashing with Self-supervised Labels -- Including multi-feature interactions and redundancy for feature ranking in mixed datasets -- Non-redundant Spectral Dimensionality Reduction -- Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-links -- SetExpan: Corpus-based Set Expansion via Context Feature Selection and Rank Ensemble -- Kernel Methods -- Bayesian Nonlinear Support Vector Machines for Big Data -- Entropic Trace Estimation for Log Determinants -- Fair Kernel Learning -- GaKCo: a Fast Gapped k-mer string Kernel using Counting -- Graph Enhanced Memory Networks for Sentiment Analysis -- Kernel Sequential Monte Carlo -- Learning Lukasiewicz Logic Fragments by Quadratic Programming -- Nystrom sketching -- Learning and Optimization -- Crossprop: learning representations by stochastic meta-gradient descent in neural networks -- Distributed Stochastic Optimization of the Regularized Risk via Saddle-point Problem -- Speeding up Hyper-parameter Optimization by Extrapolation of Learning Curves using Previous Builds -- Matrix and Tensor Factorization -- Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation -- Content-Based Social Recommendation with Poisson Matrix Factorization -- C-SALT: Mining Class-Speci_c ALTerations in Boolean Matrix Factorization -- Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition -- Structurally Regularized Non-negative Tensor Factorization for Spatio-temporal Pattern Discoveries -- Networks and Graphs -- Attributed Graph Clustering with Unimodal Normalized Cut -- K-clique-graphs for Dense Subgraph Discovery -- Learning and Scaling Directed Networks via Graph Embedding -- Local Lanczos Spectral Approximation for Membership Identification -- Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms -- Survival Factorization for Topical Cascades on Diffusion Networks -- The network-untangling problem: From interactions to activity timelines.-TransT: Type-based Multiple Embedding Representations for Knowledge Graph Completion -- Neural Networks and Deep Learning -- A network Architecture for Multi-multi Instance Learning -- CON-S2V: A Generic Framework for Incorporating Extra-Sentential Context into Sen2Vec -- Deep Over-sampling Framework for Classifying Imbalanced Data -- FCNNs: Fourier Convolutional Neural Networks -- Joint User Modeling across Aligned Heterogeneous Sites using Neural Networks -- Sequence Generation with Target Attention -- Wikipedia Vandal Early Detection: from User Behavior to User Embedding. .
Record Nr. UNISA-996465761003316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III / / edited by Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Žitnik, Michelangelo Ceci, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III / / edited by Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Žitnik, Michelangelo Ceci, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XXXV, 448 p. 144 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71273-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Applied Data Science track -- A Novel Framework for Online Sales Burst Prediction -- Analyzing Granger causality in climate data with time series classification methods -- Automatic Detection and Recognition of Individuals in Patterned Species -- Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting -- CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining -- DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters -- Disjoint-Support Factors and Seasonality Estimation in E-Commerce -- Event Detection and Summarization using Phrase Networks: PhraseNet -- Generalising Random Forest Parameter Optimisation to Include Stability and Cost -- Have It Both Ways - from A/B Testing to A&B Testing with Exceptional Model Mining -- Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays -- Modeling the Temporal Nature of Human Behavior for Demographics Prediction -- MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings -- Optimal client recommendation for market makers in illiquid financial products -- Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center -- Probabilistic Inference of Twitter Users' Age based on What They Follow -- Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects -- RSSI Based Supervised Learning for Uncooperative Direction-Finding -- Sequential Keystroke Behavioral Biometrics for User Identification via Multi-view Deep Learning -- Session-Based Fraud Detection in Online E-Commerce Transactions Using Recurrent Neural Networks -- SINAS: Suspect Investigation Using Offenders' Activity Space -- Stance Classification of Tweets using Skip Char NGrams -- Structural Semantic Models for Automatic Analysis of Urban Areas -- Taking it for a Test Drive: A Hybrid Spatio-temporal Model for Wildlife Poaching Prediction Evaluated through a Controlled Field Test -- Unsupervised signature extraction from forensic logs -- Urban Water Flow and Water Level Prediction based on Deep Learning -- Using Machine Learning for Labour Market Intelligence -- Nectar track -- Activity-Driven Influence Maximization in Social Networks -- An AI Planning System for Data Cleaning -- Comparing hypotheses on sequential behavior: A Bayesian approach and its applications -- Data-driven Approaches for Smart Parking -- Image representation, annotation and retrieval with predictive clustering trees -- Music Generation Using Bayesian Networks -- Phenotype Inference from Text and Genomic Data -- Process-based Modeling and Design of Dynamical Systems -- QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees -- Recent Advances in Kernel-Based Graph Classification -- Demo track -- ASK-the-Expert: Active learning based knowledge discovery using the expert -- Delve: A Data set Retrieval and Document Analysis System -- Framework for Exploring and Understanding Multivariate Correlations -- Lit@EVE: Explainable Recommendation based on Wikipedia Concept Vectors -- Monitoring Physical Activity and Mental Stress using Wrist-worn Device and a Smartphone -- Tetrahedron: Barycentric Measure Visualizer -- TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting -- TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory -- TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks -- WHODID: Web-based interface for Human-assisted factory Operations in fault Detection, Identification and Diagnosis.
Record Nr. UNISA-996465759903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III / / edited by Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Žitnik, Michelangelo Ceci, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III / / edited by Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Žitnik, Michelangelo Ceci, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XXXV, 448 p. 144 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71273-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Applied Data Science track -- A Novel Framework for Online Sales Burst Prediction -- Analyzing Granger causality in climate data with time series classification methods -- Automatic Detection and Recognition of Individuals in Patterned Species -- Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting -- CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining -- DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters -- Disjoint-Support Factors and Seasonality Estimation in E-Commerce -- Event Detection and Summarization using Phrase Networks: PhraseNet -- Generalising Random Forest Parameter Optimisation to Include Stability and Cost -- Have It Both Ways - from A/B Testing to A&B Testing with Exceptional Model Mining -- Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays -- Modeling the Temporal Nature of Human Behavior for Demographics Prediction -- MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings -- Optimal client recommendation for market makers in illiquid financial products -- Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center -- Probabilistic Inference of Twitter Users' Age based on What They Follow -- Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects -- RSSI Based Supervised Learning for Uncooperative Direction-Finding -- Sequential Keystroke Behavioral Biometrics for User Identification via Multi-view Deep Learning -- Session-Based Fraud Detection in Online E-Commerce Transactions Using Recurrent Neural Networks -- SINAS: Suspect Investigation Using Offenders' Activity Space -- Stance Classification of Tweets using Skip Char NGrams -- Structural Semantic Models for Automatic Analysis of Urban Areas -- Taking it for a Test Drive: A Hybrid Spatio-temporal Model for Wildlife Poaching Prediction Evaluated through a Controlled Field Test -- Unsupervised signature extraction from forensic logs -- Urban Water Flow and Water Level Prediction based on Deep Learning -- Using Machine Learning for Labour Market Intelligence -- Nectar track -- Activity-Driven Influence Maximization in Social Networks -- An AI Planning System for Data Cleaning -- Comparing hypotheses on sequential behavior: A Bayesian approach and its applications -- Data-driven Approaches for Smart Parking -- Image representation, annotation and retrieval with predictive clustering trees -- Music Generation Using Bayesian Networks -- Phenotype Inference from Text and Genomic Data -- Process-based Modeling and Design of Dynamical Systems -- QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees -- Recent Advances in Kernel-Based Graph Classification -- Demo track -- ASK-the-Expert: Active learning based knowledge discovery using the expert -- Delve: A Data set Retrieval and Document Analysis System -- Framework for Exploring and Understanding Multivariate Correlations -- Lit@EVE: Explainable Recommendation based on Wikipedia Concept Vectors -- Monitoring Physical Activity and Mental Stress using Wrist-worn Device and a Smartphone -- Tetrahedron: Barycentric Measure Visualizer -- TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting -- TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory -- TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks -- WHODID: Web-based interface for Human-assisted factory Operations in fault Detection, Identification and Diagnosis.
Record Nr. UNINA-9910484668103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XXXIII, 866 p. 213 illus.)
Disciplina 006.31
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71246-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Pattern and Sequence Mining -- BeatLex: Summarizing and Forecasting Time Series with Patterns -- Behavioral Constraint Template-Based Sequence Classification -- Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space -- Subjectively Interesting Connecting Trees -- Privacy and Security -- Malware Detection by Analysing Encrypted Network Traffic with Neural Networks -- PEM: Practical Differentially Private System for Large-Scale Cross-Institutional Data Mining -- Probabilistic Models and Methods -- Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources -- Bayesian Inference for Least Squares Temporal Difference Regularization -- Discovery of Causal Models that Contain Latent Variables through Bayesian Scoring of Independence Constraints -- Labeled DBN learning with community structure knowledge -- Multi-view Generative Adversarial Networks -- Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models -- PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning Approach -- Partial Device Fingerprints -- Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies -- Recommendation -- A Regularization Method with Inference of Trust and Distrust in Recommender Systems -- A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations -- Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation -- Regression -- Adaptive Skip-Train Structured Regression for Temporal Networks -- ALADIN: A New Approach for Drug-Target Interaction Prediction -- Co-Regularised Support Vector Regression -- Online Regression with Controlled Label Noise Rate -- Reinforcement Learning -- Generalized Inverse Reinforcement Learning with Linearly Solvable MDP -- Max K-armed bandit: On the ExtremeHunter algorithm and beyond -- Variational Thompson Sampling for Relational Recurrent Bandits -- Subgroup Discovery -- Explaining Deviating Subsets through Explanation Networks -- Flash points: Discovering exceptional pairwise behaviors in vote or rating data -- Time Series and Streams -- A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching -- Arbitrated Ensemble for Time Series Forecasting -- Cost Sensitive Time-series Classification -- Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams -- Efficient Temporal Kernels between Feature Sets for Time Series Classification -- Forecasting and Granger modelling with non-linear dynamical dependencies -- Learning TSK Fuzzy Rules from Data Streams -- Non-Parametric Online AUC Maximization -- On-line Dynamic Time Warping for Streaming Time Series -- PowerCast: Mining and Forecasting Power Grid Sequences -- UAPD: Predicting Urban Anomalies from Spatial-Temporal Data -- Transfer and Multi-Task Learning -- A Novel Rating Pattern Transfer Model for Improving Non-Overlapping Cross-Domain Collaborative Filtering -- Distributed Multi-task Learning for Sensor Network -- Learning task structure via sparsity grouped multitask learning -- Lifelong Learning with Gaussian Processes -- Personalized Tag Recommendation for Images Using Deep Transfer Learning -- Ranking based Multitask Learning of Scoring Functions -- Theoretical Analysis of Domain Adaptation with Optimal Transport -- TSP: Learning Task-Speci_c Pivots for Unsupervised Domain Adaptation -- Unsupervised and Semisupervised Learning -- k2-means for fast and accurate large scale clustering -- A Simple Exponential Family Framework for Zero-Shot Learning -- DeepCluster: A General Clustering Framework based on Deep Learning -- Multi-view Spectral Clustering on Conflicting Views -- Pivot-based Distributed K-Nearest Neighbor Mining.
Record Nr. UNINA-9910484496703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I / / edited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (LXIII, 852 p. 245 illus.)
Disciplina 006.31
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Optical data processing
Application software
Computer security
Computers
Data Mining and Knowledge Discovery
Artificial Intelligence
Image Processing and Computer Vision
Information Systems Applications (incl. Internet)
Systems and Data Security
Computing Milieux
ISBN 3-319-71249-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Anomaly Detection -- Concentration Free Outlier Detection -- Efficient top rank optimization with gradient boosting for supervised anomaly detection -- Robust, Deep and Inductive Anomaly Detection -- Sentiment Informed Cyberbullying Detection in Social Media -- zooRank: Ranking Suspicious Activities in Time-Evolving Tensors -- Computer Vision -- Alternative Semantic Representations for Zero-Shot Human Action Recognition -- Early Active Learning with Pairwise Constraint for Person Re-identification -- Guiding InfoGAN with Semi-Supervision -- Scatteract: Automated extraction of data from scatter plots -- Unsupervised Diverse Colorization via Generative Adversarial Networks -- Ensembles and Meta Learning -- Dynamic Ensemble Selection with Probabilistic Classifier Chains -- Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks -- Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks -- Feature Selection and Extraction -- Deep Discrete Hashing with Self-supervised Labels -- Including multi-feature interactions and redundancy for feature ranking in mixed datasets -- Non-redundant Spectral Dimensionality Reduction -- Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-links -- SetExpan: Corpus-based Set Expansion via Context Feature Selection and Rank Ensemble -- Kernel Methods -- Bayesian Nonlinear Support Vector Machines for Big Data -- Entropic Trace Estimation for Log Determinants -- Fair Kernel Learning -- GaKCo: a Fast Gapped k-mer string Kernel using Counting -- Graph Enhanced Memory Networks for Sentiment Analysis -- Kernel Sequential Monte Carlo -- Learning Lukasiewicz Logic Fragments by Quadratic Programming -- Nystrom sketching -- Learning and Optimization -- Crossprop: learning representations by stochastic meta-gradient descent in neural networks -- Distributed Stochastic Optimization of the Regularized Risk via Saddle-point Problem -- Speeding up Hyper-parameter Optimization by Extrapolation of Learning Curves using Previous Builds -- Matrix and Tensor Factorization -- Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation -- Content-Based Social Recommendation with Poisson Matrix Factorization -- C-SALT: Mining Class-Speci_c ALTerations in Boolean Matrix Factorization -- Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition -- Structurally Regularized Non-negative Tensor Factorization for Spatio-temporal Pattern Discoveries -- Networks and Graphs -- Attributed Graph Clustering with Unimodal Normalized Cut -- K-clique-graphs for Dense Subgraph Discovery -- Learning and Scaling Directed Networks via Graph Embedding -- Local Lanczos Spectral Approximation for Membership Identification -- Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms -- Survival Factorization for Topical Cascades on Diffusion Networks -- The network-untangling problem: From interactions to activity timelines.-TransT: Type-based Multiple Embedding Representations for Knowledge Graph Completion -- Neural Networks and Deep Learning -- A network Architecture for Multi-multi Instance Learning -- CON-S2V: A Generic Framework for Incorporating Extra-Sentential Context into Sen2Vec -- Deep Over-sampling Framework for Classifying Imbalanced Data -- FCNNs: Fourier Convolutional Neural Networks -- Joint User Modeling across Aligned Heterogeneous Sites using Neural Networks -- Sequence Generation with Target Attention -- Wikipedia Vandal Early Detection: from User Behavior to User Embedding. .
Record Nr. UNINA-9910484496603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui