000			05044nam a22005055i 4500
001			978-3-540-72927-3
003			DE-He213
005			20160624102107.0
007			cr nn 008mamaa
008			100301s2007 gw | s |||| 0|eng d
020			_a9783540729273 _9978-3-540-72927-3
024	7		_a10.1007/978-3-540-72927-3 _2doi
050		4	_aQA75.5-76.95
072		7	_aUYZG _2bicssc
072		7	_aCOM037000 _2bisacsh
082	0	4	_a004.0151 _223
245	1	0	_aLearning Theory _h[electronic resource] : _b20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA; June 13-15, 2007. Proceedings / _cedited by Nader H. Bshouty, Claudio Gentile.
260		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007.
300			_aXII, 636 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Computer Science, _x0302-9743 ; _v4539
505	0		_aInvited 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	_aComputer science.
650		0	_aComputer software.
650		0	_aArtificial intelligence.
650	1	4	_aComputer Science.
650	2	4	_aComputation by Abstract Devices.
650	2	4	_aAlgorithm Analysis and Problem Complexity.
650	2	4	_aMathematical Logic and Formal Languages.
650	2	4	_aArtificial Intelligence (incl. Robotics).
700	1		_aBshouty, Nader H. _eeditor.
700	1		_aGentile, Claudio. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540729259
786			_dSpringer
830		0	_aLecture Notes in Computer Science, _x0302-9743 ; _v4539
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-540-72927-3
942			_2EBK7617 _cEBK
999			_c36911 _d36911