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020 _a9783540352969
_9978-3-540-35296-9
024 7 _a10.1007/11776420
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aLearning Theory
_h[electronic resource] :
_b19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings /
_cedited by Hans Ulrich Simon, Gábor Lugosi.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXII, 660 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 Artificial Intelligence,
_x2945-9141 ;
_v4005
505 0 _aInvited Presentations -- Random Multivariate Search Trees -- On Learning and Logic -- Predictions as Statements and Decisions -- Clustering, Un-, and Semisupervised Learning -- A Sober Look at Clustering Stability -- PAC Learning Axis-Aligned Mixtures of Gaussians with No Separation Assumption -- Stable Transductive Learning -- Uniform Convergence of Adaptive Graph-Based Regularization -- Statistical Learning Theory -- The Rademacher Complexity of Linear Transformation Classes -- Function Classes That Approximate the Bayes Risk -- Functional Classification with Margin Conditions -- Significance and Recovery of Block Structures in Binary Matrices with Noise -- Regularized Learning and Kernel Methods -- Maximum Entropy Distribution Estimation with Generalized Regularization -- Unifying Divergence Minimization and Statistical Inference Via Convex Duality -- Mercer's Theorem, Feature Maps, and Smoothing -- Learning Bounds for Support Vector Machines with Learned Kernels -- Query Learning and Teaching -- On Optimal Learning Algorithms for Multiplicity Automata -- Exact Learning Composed Classes with a Small Number of Mistakes -- DNF Are Teachable in the Average Case -- Teaching Randomized Learners -- Inductive Inference -- Memory-Limited U-Shaped Learning -- On Learning Languages from Positive Data and a Limited Number of Short Counterexamples -- Learning Rational Stochastic Languages -- Parent Assignment Is Hard for the MDL, AIC, and NML Costs -- Learning Algorithms and Limitations on Learning -- Uniform-Distribution Learnability of Noisy Linear Threshold Functions with Restricted Focus of Attention -- Discriminative Learning Can Succeed Where Generative Learning Fails -- Improved Lower Bounds for Learning Intersections of Halfspaces -- Efficient Learning Algorithms Yield Circuit Lower Bounds -- OnlineAggregation -- Optimal Oracle Inequality for Aggregation of Classifiers Under Low Noise Condition -- Aggregation and Sparsity Via ?1 Penalized Least Squares -- A Randomized Online Learning Algorithm for Better Variance Control -- Online Prediction and Reinforcement Learning I -- Online Learning with Variable Stage Duration -- Online Learning Meets Optimization in the Dual -- Online Tracking of Linear Subspaces -- Online Multitask Learning -- Online Prediction and Reinforcement Learning II -- The Shortest Path Problem Under Partial Monitoring -- Tracking the Best Hyperplane with a Simple Budget Perceptron -- Logarithmic Regret Algorithms for Online Convex Optimization -- Online Variance Minimization -- Online Prediction and Reinforcement Learning III -- Online Learning with Constraints -- Continuous Experts and the Binning Algorithm -- Competing with Wild Prediction Rules -- Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path -- Other Approaches -- Ranking with a P-Norm Push -- Subset Ranking Using Regression -- Active Sampling for Multiple Output Identification -- Improving Random Projections Using Marginal Information -- Open Problems -- Efficient Algorithms for General Active Learning -- Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints.
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer science.
_99832
650 0 _aAlgorithms.
_93390
650 0 _aMachine theory.
_9153247
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aTheory of Computation.
_9153248
650 2 4 _aAlgorithms.
_93390
650 2 4 _aFormal Languages and Automata Theory.
_9153249
700 1 _aSimon, Hans Ulrich.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9153250
700 1 _aLugosi, Gábor.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9153251
710 2 _aSpringerLink (Online service)
_9153252
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540352945
776 0 8 _iPrinted edition:
_z9783540825562
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v4005
_9153253
856 4 0 _uhttps://doi.org/10.1007/11776420
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