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Algorithmic Learning Theory [[electronic resource] ] : 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings / / edited by Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann
| Algorithmic Learning Theory [[electronic resource] ] : 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings / / edited by Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (XIII, 421 p. 45 illus.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computer programming Mathematical logic Algorithms Computers Computer logic Artificial Intelligence Programming Techniques Mathematical Logic and Formal Languages Algorithm Analysis and Problem Complexity Computation by Abstract Devices Logics and Meanings of Programs |
| ISBN |
1-280-38945-1
9786613567376 3-642-16108-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- Towards General Algorithms for Grammatical Inference -- The Blessing and the Curse of the Multiplicative Updates -- Discovery of Abstract Concepts by a Robot -- Contrast Pattern Mining and Its Application for Building Robust Classifiers -- Optimal Online Prediction in Adversarial Environments -- Regular Contributions -- An Algorithm for Iterative Selection of Blocks of Features -- Bayesian Active Learning Using Arbitrary Binary Valued Queries -- Approximation Stability and Boosting -- A Spectral Approach for Probabilistic Grammatical Inference on Trees -- PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation -- Inferring Social Networks from Outbreaks -- Distribution-Dependent PAC-Bayes Priors -- PAC Learnability of a Concept Class under Non-atomic Measures: A Problem by Vidyasagar -- A PAC-Bayes Bound for Tailored Density Estimation -- Compressed Learning with Regular Concept -- A Lower Bound for Learning Distributions Generated by Probabilistic Automata -- Lower Bounds on Learning Random Structures with Statistical Queries -- Recursive Teaching Dimension, Learning Complexity, and Maximum Classes -- Toward a Classification of Finite Partial-Monitoring Games -- Switching Investments -- Prediction with Expert Advice under Discounted Loss -- A Regularization Approach to Metrical Task Systems -- Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations -- Learning without Coding -- Learning Figures with the Hausdorff Metric by Fractals -- Inductive Inference of Languages from Samplings -- Optimality Issues of Universal Greedy Agents with Static Priors -- Consistency of Feature Markov Processes -- Algorithms for Adversarial Bandit Problems with Multiple Plays -- Online Multiple Kernel Learning: Algorithms and Mistake Bounds -- An Identity for Kernel Ridge Regression. |
| Record Nr. | UNISA-996465982503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Algorithmic learning theory : 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010 ; proceedings / / Marcus Hutter ... [et al.] (eds.)
| Algorithmic learning theory : 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010 ; proceedings / / Marcus Hutter ... [et al.] (eds.) |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2010 |
| Descrizione fisica | 1 online resource (XIII, 421 p. 45 illus.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | HutterMarcus |
| Collana | Lecture notes in artificial intelligence |
| Soggetto topico |
Machine learning
Algorithms |
| ISBN |
1-280-38945-1
9786613567376 3-642-16108-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- Towards General Algorithms for Grammatical Inference -- The Blessing and the Curse of the Multiplicative Updates -- Discovery of Abstract Concepts by a Robot -- Contrast Pattern Mining and Its Application for Building Robust Classifiers -- Optimal Online Prediction in Adversarial Environments -- Regular Contributions -- An Algorithm for Iterative Selection of Blocks of Features -- Bayesian Active Learning Using Arbitrary Binary Valued Queries -- Approximation Stability and Boosting -- A Spectral Approach for Probabilistic Grammatical Inference on Trees -- PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation -- Inferring Social Networks from Outbreaks -- Distribution-Dependent PAC-Bayes Priors -- PAC Learnability of a Concept Class under Non-atomic Measures: A Problem by Vidyasagar -- A PAC-Bayes Bound for Tailored Density Estimation -- Compressed Learning with Regular Concept -- A Lower Bound for Learning Distributions Generated by Probabilistic Automata -- Lower Bounds on Learning Random Structures with Statistical Queries -- Recursive Teaching Dimension, Learning Complexity, and Maximum Classes -- Toward a Classification of Finite Partial-Monitoring Games -- Switching Investments -- Prediction with Expert Advice under Discounted Loss -- A Regularization Approach to Metrical Task Systems -- Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations -- Learning without Coding -- Learning Figures with the Hausdorff Metric by Fractals -- Inductive Inference of Languages from Samplings -- Optimality Issues of Universal Greedy Agents with Static Priors -- Consistency of Feature Markov Processes -- Algorithms for Adversarial Bandit Problems with Multiple Plays -- Online Multiple Kernel Learning: Algorithms and Mistake Bounds -- An Identity for Kernel Ridge Regression. |
| Record Nr. | UNINA-9910484805303321 |
| Berlin ; ; New York, : Springer, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Algorithmic learning theory : 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, proceedings / / Marcus Hutter, Rocco A. Servedio, Eiji Takimoto (Eds.)
| Algorithmic learning theory : 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, proceedings / / Marcus Hutter, Rocco A. Servedio, Eiji Takimoto (Eds.) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XI, 406 p.) |
| Disciplina | 005.1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer algorithms
Machine learning |
| ISBN | 3-540-75225-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- A Theory of Similarity Functions for Learning and Clustering -- Machine Learning in Ecosystem Informatics -- Challenge for Info-plosion -- A Hilbert Space Embedding for Distributions -- Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity -- Invited Papers -- Feasible Iteration of Feasible Learning Functionals -- Parallelism Increases Iterative Learning Power -- Prescribed Learning of R.E. Classes -- Learning in Friedberg Numberings -- Complexity Aspects of Learning -- Separating Models of Learning with Faulty Teachers -- Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations -- Parameterized Learnability of k-Juntas and Related Problems -- On Universal Transfer Learning -- Online Learning -- Tuning Bandit Algorithms in Stochastic Environments -- Following the Perturbed Leader to Gamble at Multi-armed Bandits -- Online Regression Competitive with Changing Predictors -- Unsupervised Learning -- Cluster Identification in Nearest-Neighbor Graphs -- Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in -- Language Learning -- Learning Efficiency of Very Simple Grammars from Positive Data -- Learning Rational Stochastic Tree Languages -- Query Learning -- One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples -- Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries -- Learning and Verifying Graphs Using Queries with a Focus on Edge Counting -- Exact Learning of Finite Unions of Graph Patterns from Queries -- Kernel-Based Learning -- Polynomial Summaries of Positive Semidefinite Kernels -- Learning Kernel Perceptrons on Noisy Data Using Random Projections -- Continuity of Performance Metrics for Thin Feature Maps -- Other Directions -- Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability -- Pseudometrics for State Aggregation in Average Reward Markov Decision Processes -- On Calibration Error of Randomized Forecasting Algorithms. |
| Record Nr. | UNISA-996465435103316 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Algorithmic learning theory : 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, proceedings / / Marcus Hutter, Rocco A. Servedio, Eiji Takimoto (Eds.)
| Algorithmic learning theory : 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, proceedings / / Marcus Hutter, Rocco A. Servedio, Eiji Takimoto (Eds.) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XI, 406 p.) |
| Disciplina | 005.1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer algorithms
Machine learning |
| ISBN | 3-540-75225-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- A Theory of Similarity Functions for Learning and Clustering -- Machine Learning in Ecosystem Informatics -- Challenge for Info-plosion -- A Hilbert Space Embedding for Distributions -- Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity -- Invited Papers -- Feasible Iteration of Feasible Learning Functionals -- Parallelism Increases Iterative Learning Power -- Prescribed Learning of R.E. Classes -- Learning in Friedberg Numberings -- Complexity Aspects of Learning -- Separating Models of Learning with Faulty Teachers -- Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations -- Parameterized Learnability of k-Juntas and Related Problems -- On Universal Transfer Learning -- Online Learning -- Tuning Bandit Algorithms in Stochastic Environments -- Following the Perturbed Leader to Gamble at Multi-armed Bandits -- Online Regression Competitive with Changing Predictors -- Unsupervised Learning -- Cluster Identification in Nearest-Neighbor Graphs -- Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in -- Language Learning -- Learning Efficiency of Very Simple Grammars from Positive Data -- Learning Rational Stochastic Tree Languages -- Query Learning -- One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples -- Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries -- Learning and Verifying Graphs Using Queries with a Focus on Edge Counting -- Exact Learning of Finite Unions of Graph Patterns from Queries -- Kernel-Based Learning -- Polynomial Summaries of Positive Semidefinite Kernels -- Learning Kernel Perceptrons on Noisy Data Using Random Projections -- Continuity of Performance Metrics for Thin Feature Maps -- Other Directions -- Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability -- Pseudometrics for State Aggregation in Average Reward Markov Decision Processes -- On Calibration Error of Randomized Forecasting Algorithms. |
| Record Nr. | UNINA-9910484808303321 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Recent Advances in Reinforcement Learning [[electronic resource] ] : 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised and Selected Papers / / edited by Scott Sanner, Marcus Hutter
| Recent Advances in Reinforcement Learning [[electronic resource] ] : 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised and Selected Papers / / edited by Scott Sanner, Marcus Hutter |
| Edizione | [1st ed. 2012.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
| Descrizione fisica | 1 online resource (XIII, 345 p. 98 illus.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Algorithms Application software Database management Mathematical statistics Artificial Intelligence Computation by Abstract Devices Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) Database Management Probability and Statistics in Computer Science |
| Soggetto genere / forma | Conference proceedings. |
| ISBN | 3-642-29946-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465571903316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||