Learning Theory (Record no. 36911)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05044nam a22005055i 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783540729273 |
| -- | 978-3-540-72927-3 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.0151 |
| 245 10 - TITLE STATEMENT | |
| Title | Learning Theory |
| Sub Title | 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA; June 13-15, 2007. Proceedings / |
| Statement of responsibility, etc | edited by Nader H. Bshouty, Claudio Gentile. |
| 260 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Berlin, Heidelberg : |
| Name of publisher | Springer Berlin Heidelberg, |
| Year of publication | 2007. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XII, 636 p. |
| Other physical details | online resource. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Computer Science, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Invited Presentations -- Property Testing: A Learning Theory Perspective -- Spectral Algorithms for Learning and Clustering -- Unsupervised, Semisupervised and Active Learning I -- Minimax Bounds for Active Learning -- Stability of k-Means Clustering -- Margin Based Active Learning -- Unsupervised, Semisupervised and Active Learning II -- Learning Large-Alphabet and Analog Circuits with Value Injection Queries -- Teaching Dimension and the Complexity of Active Learning -- Multi-view Regression Via Canonical Correlation Analysis -- Statistical Learning Theory -- Aggregation by Exponential Weighting and Sharp Oracle Inequalities -- Occam’s Hammer -- Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector -- Suboptimality of Penalized Empirical Risk Minimization in Classification -- Transductive Rademacher Complexity and Its Applications -- Inductive Inference -- U-Shaped, Iterative, and Iterative-with-Counter Learning -- Mind Change Optimal Learning of Bayes Net Structure -- Learning Correction Grammars -- Mitotic Classes -- Online and Reinforcement Learning I -- Regret to the Best vs. Regret to the Average -- Strategies for Prediction Under Imperfect Monitoring -- Bounded Parameter Markov Decision Processes with Average Reward Criterion -- Online and Reinforcement Learning II -- On-Line Estimation with the Multivariate Gaussian Distribution -- Generalised Entropy and Asymptotic Complexities of Languages -- Q-Learning with Linear Function Approximation -- Regularized Learning, Kernel Methods, SVM -- How Good Is a Kernel When Used as a Similarity Measure? -- Gaps in Support Vector Optimization -- Learning Languages with Rational Kernels -- Generalized SMO-Style Decomposition Algorithms -- Learning Algorithms and Limitations on Learning -- Learning Nested Halfspaces and Uphill Decision Trees -- An Efficient Re-scaled Perceptron Algorithm for Conic Systems -- A Lower Bound for Agnostically Learning Disjunctions -- Sketching Information Divergences -- Competing with Stationary Prediction Strategies -- Online and Reinforcement Learning III -- Improved Rates for the Stochastic Continuum-Armed Bandit Problem -- Learning Permutations with Exponential Weights -- Online and Reinforcement Learning IV -- Multitask Learning with Expert Advice -- Online Learning with Prior Knowledge -- Dimensionality Reduction -- Nonlinear Estimators and Tail Bounds for Dimension Reduction in l 1 Using Cauchy Random Projections -- Sparse Density Estimation with ?1 Penalties -- ?1 Regularization in Infinite Dimensional Feature Spaces -- Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking -- Other Approaches -- Observational Learning in Random Networks -- The Loss Rank Principle for Model Selection -- Robust Reductions from Ranking to Classification -- Open Problems -- Rademacher Margin Complexity -- Open Problems in Efficient Semi-supervised PAC Learning -- Resource-Bounded Information Gathering for Correlation Clustering -- Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation? -- When Is There a Free Matrix Lunch?. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Computer software. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Computation by Abstract Devices. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Algorithm Analysis and Problem Complexity. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Mathematical Logic and Formal Languages. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial Intelligence (incl. Robotics). |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Bshouty, Nader H. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Gentile, Claudio. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-540-72927-3 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | E-BOOKS |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg, |
| -- | 2007. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 0302-9743 ; |
| Withdrawn status | Lost status | Damaged status | Not for loan | Current library | Accession Number | Uniform Resource Identifier | Koha item type |
|---|---|---|---|---|---|---|---|
| IMSc Library | EBK7617 | http://dx.doi.org/10.1007/978-3-540-72927-3 | E-BOOKS |