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Algorithmic Learning Theory [[electronic resource] ] : 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009, Proceedings / / edited by Ricard Gavaldà, Gabor Lugosi, Thomas Zeugmann, Sandra Zilles
Algorithmic Learning Theory [[electronic resource] ] : 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009, Proceedings / / edited by Ricard Gavaldà, Gabor Lugosi, Thomas Zeugmann, Sandra Zilles
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Descrizione fisica 1 online resource (XI, 399 p.)
Disciplina 006.3/1
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computer programming
Data mining
Natural language processing (Computer science)
Pattern recognition
Information storage and retrieval
Artificial Intelligence
Programming Techniques
Data Mining and Knowledge Discovery
Natural Language Processing (NLP)
Pattern Recognition
Information Storage and Retrieval
Soggetto genere / forma Kongress.
Porto (Portugal, 2009)
ISBN 3-642-04414-X
Classificazione DAT 708f
SS 4800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Papers -- The Two Faces of Active Learning -- Inference and Learning in Planning -- Mining Heterogeneous Information Networks by Exploring the Power of Links -- Learning and Domain Adaptation -- Learning on the Web -- Regular Contributions -- Prediction with Expert Evaluators’ Advice -- Pure Exploration in Multi-armed Bandits Problems -- The Follow Perturbed Leader Algorithm Protected from Unbounded One-Step Losses -- Computable Bayesian Compression for Uniformly Discretizable Statistical Models -- Calibration and Internal No-Regret with Random Signals -- St. Petersburg Portfolio Games -- Reconstructing Weighted Graphs with Minimal Query Complexity -- Learning Unknown Graphs -- Completing Networks Using Observed Data -- Average-Case Active Learning with Costs -- Canonical Horn Representations and Query Learning -- Learning Finite Automata Using Label Queries -- Characterizing Statistical Query Learning: Simplified Notions and Proofs -- An Algebraic Perspective on Boolean Function Learning -- Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm -- Complexity versus Agreement for Many Views -- Error-Correcting Tournaments -- Difficulties in Forcing Fairness of Polynomial Time Inductive Inference -- Learning Mildly Context-Sensitive Languages with Multidimensional Substitutability from Positive Data -- Uncountable Automatic Classes and Learning -- Iterative Learning from Texts and Counterexamples Using Additional Information -- Incremental Learning with Ordinal Bounded Example Memory -- Learning from Streams -- Smart PAC-Learners -- Approximation Algorithms for Tensor Clustering -- Agnostic Clustering.
Record Nr. UNISA-996465309803316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Algorithmic Learning Theory : 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009, Proceedings / / edited by Ricard Gavaldà, Gabor Lugosi, Thomas Zeugmann, Sandra Zilles
Algorithmic Learning Theory : 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009, Proceedings / / edited by Ricard Gavaldà, Gabor Lugosi, Thomas Zeugmann, Sandra Zilles
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Descrizione fisica 1 online resource (XI, 399 p.)
Disciplina 006.3/1
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computer programming
Data mining
Natural language processing (Computer science)
Pattern recognition
Information storage and retrieval
Artificial Intelligence
Programming Techniques
Data Mining and Knowledge Discovery
Natural Language Processing (NLP)
Pattern Recognition
Information Storage and Retrieval
Soggetto genere / forma Kongress.
Porto (Portugal, 2009)
ISBN 3-642-04414-X
Classificazione DAT 708f
SS 4800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Papers -- The Two Faces of Active Learning -- Inference and Learning in Planning -- Mining Heterogeneous Information Networks by Exploring the Power of Links -- Learning and Domain Adaptation -- Learning on the Web -- Regular Contributions -- Prediction with Expert Evaluators’ Advice -- Pure Exploration in Multi-armed Bandits Problems -- The Follow Perturbed Leader Algorithm Protected from Unbounded One-Step Losses -- Computable Bayesian Compression for Uniformly Discretizable Statistical Models -- Calibration and Internal No-Regret with Random Signals -- St. Petersburg Portfolio Games -- Reconstructing Weighted Graphs with Minimal Query Complexity -- Learning Unknown Graphs -- Completing Networks Using Observed Data -- Average-Case Active Learning with Costs -- Canonical Horn Representations and Query Learning -- Learning Finite Automata Using Label Queries -- Characterizing Statistical Query Learning: Simplified Notions and Proofs -- An Algebraic Perspective on Boolean Function Learning -- Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm -- Complexity versus Agreement for Many Views -- Error-Correcting Tournaments -- Difficulties in Forcing Fairness of Polynomial Time Inductive Inference -- Learning Mildly Context-Sensitive Languages with Multidimensional Substitutability from Positive Data -- Uncountable Automatic Classes and Learning -- Iterative Learning from Texts and Counterexamples Using Additional Information -- Incremental Learning with Ordinal Bounded Example Memory -- Learning from Streams -- Smart PAC-Learners -- Approximation Algorithms for Tensor Clustering -- Agnostic Clustering.
Record Nr. UNINA-9910483550403321
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Algorithmic Learning Theory [[electronic resource] ] : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings / / edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto
Algorithmic Learning Theory [[electronic resource] ] : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings / / edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto
Edizione [1st ed. 2003.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
Descrizione fisica 1 online resource (XII, 320 p.)
Disciplina 006.3/1
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computers
Algorithms
Mathematical logic
Natural language processing (Computer science)
Artificial Intelligence
Computation by Abstract Devices
Algorithm Analysis and Problem Complexity
Mathematical Logic and Formal Languages
Natural Language Processing (NLP)
ISBN 3-540-39624-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Papers -- Abduction and the Dualization Problem -- Signal Extraction and Knowledge Discovery Based on Statistical Modeling -- Association Computation for Information Access -- Efficient Data Representations That Preserve Information -- Can Learning in the Limit Be Done Efficiently? -- Inductive Inference -- Intrinsic Complexity of Uniform Learning -- On Ordinal VC-Dimension and Some Notions of Complexity -- Learning of Erasing Primitive Formal Systems from Positive Examples -- Changing the Inference Type – Keeping the Hypothesis Space -- Learning and Information Extraction -- Robust Inference of Relevant Attributes -- Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables -- Learning with Queries -- On the Learnability of Erasing Pattern Languages in the Query Model -- Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries -- Learning with Non-linear Optimization -- Kernel Trick Embedded Gaussian Mixture Model -- Efficiently Learning the Metric with Side-Information -- Learning Continuous Latent Variable Models with Bregman Divergences -- A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation -- Learning from Random Examples -- On the Complexity of Training a Single Perceptron with Programmable Synaptic Delays -- Learning a Subclass of Regular Patterns in Polynomial Time -- Identification with Probability One of Stochastic Deterministic Linear Languages -- Online Prediction -- Criterion of Calibration for Transductive Confidence Machine with Limited Feedback -- Well-Calibrated Predictions from Online Compression Models -- Transductive Confidence Machine Is Universal -- On the Existence and Convergence of Computable Universal Priors.
Record Nr. UNISA-996465796603316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Algorithmic Learning Theory : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings / / edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto
Algorithmic Learning Theory : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings / / edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto
Edizione [1st ed. 2003.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
Descrizione fisica 1 online resource (XII, 320 p.)
Disciplina 006.3/1
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computers
Algorithms
Mathematical logic
Natural language processing (Computer science)
Artificial Intelligence
Computation by Abstract Devices
Algorithm Analysis and Problem Complexity
Mathematical Logic and Formal Languages
Natural Language Processing (NLP)
ISBN 3-540-39624-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Papers -- Abduction and the Dualization Problem -- Signal Extraction and Knowledge Discovery Based on Statistical Modeling -- Association Computation for Information Access -- Efficient Data Representations That Preserve Information -- Can Learning in the Limit Be Done Efficiently? -- Inductive Inference -- Intrinsic Complexity of Uniform Learning -- On Ordinal VC-Dimension and Some Notions of Complexity -- Learning of Erasing Primitive Formal Systems from Positive Examples -- Changing the Inference Type – Keeping the Hypothesis Space -- Learning and Information Extraction -- Robust Inference of Relevant Attributes -- Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables -- Learning with Queries -- On the Learnability of Erasing Pattern Languages in the Query Model -- Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries -- Learning with Non-linear Optimization -- Kernel Trick Embedded Gaussian Mixture Model -- Efficiently Learning the Metric with Side-Information -- Learning Continuous Latent Variable Models with Bregman Divergences -- A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation -- Learning from Random Examples -- On the Complexity of Training a Single Perceptron with Programmable Synaptic Delays -- Learning a Subclass of Regular Patterns in Polynomial Time -- Identification with Probability One of Stochastic Deterministic Linear Languages -- Online Prediction -- Criterion of Calibration for Transductive Confidence Machine with Limited Feedback -- Well-Calibrated Predictions from Online Compression Models -- Transductive Confidence Machine Is Universal -- On the Existence and Convergence of Computable Universal Priors.
Record Nr. UNINA-9910144028803321
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
ECML PKDD 2018 Workshops [[electronic resource] ] : Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings / / edited by Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
ECML PKDD 2018 Workshops [[electronic resource] ] : Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings / / edited by Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (X, 257 p. 92 illus., 59 illus. in color.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computer security
Optical data processing
Computer communication systems
Artificial Intelligence
Systems and Data Security
Image Processing and Computer Vision
Computer Communication Networks
ISBN 3-030-13453-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Label Sanitization against Label Flipping Poisoning Attacks -- Limitations of the Lipschitz constant as a Defense Against Adversarial Examples -- Understanding Adversarial Space through the Lens of Attribution -- Detecting Potential Local Adversarial Examples for Human-Interpretable Defense -- Smart Cities with Deep Edges -- Computational Model for Urban Growth Using Socioeconomic Latent Parameters -- Object Geolocation from Crowdsourced Street Level Imagery -- Extending Support Vector Regression to Constraint Optimization: Application to the Reduction of Potentially Avoidable Hospitalizations -- SALER: a Data Science Solution to Detect and Prevent Corruption in Public Administration -- MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities -- Designing Data-Driven Solutions to Societal Problems: Challenges and Approaches -- Host based Intrusion Detection System with Combined CNN/RNN Model -- Cyber Attacks against the PC Learning Algorithm -- Neural Networks in an Adversarial Setting and Ill-Conditioned Weight Space -- Pseudo-Random Number Generation using Generative Adversarial Networks -- Context Delegation for Context-Based Access Control -- An Information Retrieval System For CBRNe Incidents -- A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support -- Event relevancy pruning in support of energy-efficient sequential pattern mining -- How to Measure Energy Consumption in Machine Learning Algorithms.
Record Nr. UNISA-996466447703316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
ECML PKDD 2018 Workshops : Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings / / edited by Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
ECML PKDD 2018 Workshops : Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings / / edited by Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (X, 257 p. 92 illus., 59 illus. in color.)
Disciplina 006.3
006.31
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Computer security
Optical data processing
Computer communication systems
Artificial Intelligence
Systems and Data Security
Image Processing and Computer Vision
Computer Communication Networks
ISBN 3-030-13453-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Label Sanitization against Label Flipping Poisoning Attacks -- Limitations of the Lipschitz constant as a Defense Against Adversarial Examples -- Understanding Adversarial Space through the Lens of Attribution -- Detecting Potential Local Adversarial Examples for Human-Interpretable Defense -- Smart Cities with Deep Edges -- Computational Model for Urban Growth Using Socioeconomic Latent Parameters -- Object Geolocation from Crowdsourced Street Level Imagery -- Extending Support Vector Regression to Constraint Optimization: Application to the Reduction of Potentially Avoidable Hospitalizations -- SALER: a Data Science Solution to Detect and Prevent Corruption in Public Administration -- MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities -- Designing Data-Driven Solutions to Societal Problems: Challenges and Approaches -- Host based Intrusion Detection System with Combined CNN/RNN Model -- Cyber Attacks against the PC Learning Algorithm -- Neural Networks in an Adversarial Setting and Ill-Conditioned Weight Space -- Pseudo-Random Number Generation using Generative Adversarial Networks -- Context Delegation for Context-Based Access Control -- An Information Retrieval System For CBRNe Incidents -- A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support -- Event relevancy pruning in support of energy-efficient sequential pattern mining -- How to Measure Energy Consumption in Machine Learning Algorithms.
Record Nr. UNINA-9910337576703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui