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[null,"1.","Record Nr.",null,"UNINA9910271358603321"]
[null,null,"Autore",null,"Alpers, Edward A."]
[null,null,"Titolo",null,"The Indian Ocean in world history / Edward A. Alpers"]
[null,null,"Pubbl/distr/stampa",null,"Oxford : Oxford University press, c2014"]
[null,null,"ISBN",null,"978-0-19-533787-7"]
[null,null,"Descrizione fisica",null,"X, 172 p. : ill. ; 24 cm."]
[null,null,"Collana",null,"The new Oxford world history"]
[null,null,"Disciplina",null,"909.09824"]
[null,null,"Locazione",null,"FSPBC"]
[null,null,"Collocazione",null,"XIV E 4369"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNISA996465807203316"]
[null,null,"Titolo",null,"Learning Theory [[electronic resource] ] : 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / / edited by John Shawe-Taylor, Yoram Singer"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004"]
[null,null,"ISBN",null,"3-540-27819-2"]
[null,null,"Edizione",null,"[1st ed. 2004.]"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 654 p.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 3120"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Mathematical logic"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Computers"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Mathematical Logic and Formal Languages"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[{"$nulls":4},"Computation by Abstract Devices"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Economics and Game Theory -- Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions -- Graphical Economics -- Deterministic Calibration and Nash Equilibrium -- Reinforcement Learning for Average Reward Zero-Sum Games -- OnLine Learning -- Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability -- Minimizing Regret with Label Efficient Prediction -- Regret Bounds for Hierarchical Classification with Linear-Threshold Functions -- Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary -- Inductive Inference -- Learning Classes of Probabilistic Automata -- On the Learnability of E-pattern Languages over Small Alphabets -- Replacing Limit Learners with Equally Powerful One-Shot Query Learners -- Probabilistic Models -- Concentration Bounds for Unigrams Language Model -- Inferring Mixtures of Markov Chains -- Boolean Function Learning -- PExact = Exact Learning -- Learning a Hidden Graph Using O(log n) Queries Per Edge -- Toward Attribute Efficient Learning of Decision Lists and Parities -- Empirical Processes -- Learning Over Compact Metric Spaces "]
[{"$nulls":4},"-- A Function Representation for Learning in Banach Spaces -- Local Complexities for Empirical Risk Minimization -- Model Selection by Bootstrap Penalization for Classification -- MDL -- Convergence of Discrete MDL for Sequential Prediction -- On the Convergence of MDL Density Estimation -- Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification -- Generalisation I -- Learning Intersections of Halfspaces with a Margin -- A General Convergence Theorem for the Decomposition Method -- Generalisation II -- Oracle Bounds and Exact Algorithm for Dyadic Classification Trees -- An Improved VC Dimension Bound for Sparse Polynomials -- A New PAC Bound for Intersection-Closed Concept Classes -- Clustering and Distributed Learning -- A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering -- Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers -- Consistency in Models for Communication Constrained Distributed Learning -- On the Convergence of Spectral Clustering on Random Samples: The Normalized Case -- Boosting -- Performance Guarantees for Regularized Maximum Entropy Density Estimation -- Learning Monotonic Linear Functions -- Boosting Based on a Smooth Margin -- Kernels and Probabilities -- Bayesian Networks and Inner Product Spaces -- An Inequality for Nearly Log-Concave Distributions with Applications to Learning -- Bayes and Tukey Meet at the Center Point -- Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results -- Kernels and Kernel Matrices -- A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra -- Statistical Properties of Kernel Principal Component Analysis -- Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA -- Regularization and Semi-supervised Learning on Large Graphs -- Open Problems -- Perceptron-Like Performance for Intersections of Halfspaces -- The Optimal PAC Algorithm -- The Budgeted Multi-armed Bandit Problem."]