01169nam0-22003251i-450 99000187064040332120190529131438.0000187064FED01000187064(Aleph)000187064FED0100018706420021010d1975----km-y0itay50------baitaCombined zeeman effects on the 35Cl and 14N nuclear quadrupole resonances in a single crystal of N,N'- dideuterated para-chloroanilineR. Ambrosetti, Arturo Colligiani, P. Grigolini.Pisa...1975.p. 249-26824 cmEstr. da: Proceedings of the second international Symposium on NQR spectroscopy, 1975Chimica fisica541Ambrosetti,Roberto358543Colligiani,ArturoGrigolini,P.ITUNINARICAUNIMARCLG99000187064040332160 OP. 146/63FAGBCFAGBCCombined zeeman effects on the 35Cl and 14N nuclear quadrupole resonances in a single crystal of N,N'- dideuterated para-chloroaniline401128UNINAING0101602nam 2200433 a 450 991070013100332120120329125347.0(CKB)5470000002407659(OCoLC)781950698(EXLCZ)99547000000240765920120329d2011 ua 0engurcn|||||||||txtrdacontentcrdamediacrrdacarrierUpper Colorado River Basin Climate Effects Network[electronic resource] /[Jayne Belnap and Donald Campbell][Reston, Va.] :U.S. Dept. of the Interior, U.S. Geological Survey,[2011]1 online resource (2 unnumbered pages) color illustrations, color mapFact sheet ;2010-3092Title from title screen (viewed on Mar. 29, 2012)."January 2011."Ecosystem managementColorado River Watershed (Colo.-Mexico)Applied ecologyColorado River Watershed (Colo.-Mexico)Nature conservationColorado River Watershed (Colo.-Mexico)Climatic changesColorado River Watershed (Colo.-Mexico)Ecosystem managementApplied ecologyNature conservationClimatic changesBelnap Jayne1952-282943Campbell Donald H1387882Geological Survey (U.S.)GPOGPOBOOK9910700131003321Upper Colorado River Basin Climate Effects Network3445809UNINA06245nam 22007695 450 991076755260332120251226195624.01-280-94078-697866109407833-540-72927-510.1007/978-3-540-72927-3(CKB)1000000000478525(EBL)3061502(SSID)ssj0000190640(PQKBManifestationID)11199414(PQKBTitleCode)TC0000190640(PQKBWorkID)10180718(PQKB)10646709(DE-He213)978-3-540-72927-3(MiAaPQ)EBC3061502(MiAaPQ)EBC6413326(PPN)12316284X(BIP)14225938(EXLCZ)99100000000047852520100301d2007 u| 0engur|n|---|||||txtccrLearning Theory 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007, Proceedings /edited by Nader Bshouty, Claudio Gentile1st ed. 2007.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2007.1 online resource (644 p.)Lecture Notes in Artificial Intelligence,2945-9141 ;4539Description based upon print version of record.3-540-72925-9 Includes bibliographical references and index.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 UphillDecision 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?.This book constitutes the refereed proceedings of the 20th Annual Conference on Learning Theory, COLT 2007, held in San Diego, CA, USA in June 2007. The 41 revised full papers presented together with 5 articles on open problems and 2 invited lectures were carefully reviewed and selected from a total of 92 submissions. The papers cover a wide range of topics and are organized in topical sections on unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, other approaches, and open problems.Lecture Notes in Artificial Intelligence,2945-9141 ;4539Artificial intelligenceComputer scienceAlgorithmsMachine theoryArtificial IntelligenceTheory of ComputationAlgorithmsFormal Languages and Automata TheoryArtificial intelligence.Computer science.Algorithms.Machine theory.Artificial Intelligence.Theory of Computation.Algorithms.Formal Languages and Automata Theory.006.31Bshouty Nader H.Gentile ClaudioMiAaPQMiAaPQMiAaPQBOOK9910767552603321Learning Theory772233UNINA