Algorithmic Learning Theory(算法学习理论/会议录)

Algorithmic Learning Theory(算法学习理论/会议录) - 图书城

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作者:
Shai Ben David 著
ISBN:
9783540233565 , 3540233563
出版社:
出版日期:
2004-12-1
定价:
723.20
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内容提要:
This book constitutes the refereed proceedings of the 15th International Conference on Algorithmic Learning Theory, ALT 2004, held in Padova, Italy in October 2004.
The 29 revised full papers presented together with 5 invited papers and 3 tutorial summaries were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on inductive inference, PAC learning and boosting, statistical supervised learning, online sequence learning, approximate optimization algorithms, logic based learning, and query and reinforcement learning.
目录:
INVITED PAPERS
 String Pattern Discovery
 Applications of Regularized Least Squares to Classification Problems .
 Probabilistic Inductive Logic Programming
 Hidden Markov Modelling Techniques for Haplotype Analysis
 Learning, Logic, and Probability: A Unified View
 REGULAR CONTRIBUTIONS
Inductive Inference
 Learning Languages from Positive Data and Negative Counterexamples
 Inductive Inference of Term Rewriting Systems from Positive Data
 On the Data Consumption Benefits of Accepting Increased Uncertainty
 Comparison of Query Learning and Gold-Style Learning in Dependence of the Hypothesis Space
PAC Learning and Boosting
 Learning r-of-k Functions by Boosting
 Boosting Based on Divide and Merge
 Learning Boolean Functions in AC0 on Attribute and Classification Noise
Statistical Supervised Learning
 Decision Trees: More Theoretical Justification for Practical Algorithms
 Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data
 Complexity of Pattern Classes and Lipschitz Property
Statistical Analysis of Unlabeled Data
 On Kernels, Margins, and Low-Dimensional Mappings
 Estimation of the Data Region Using Extreme-Value Distributions
 Maximum Entropy Principle in Non-ordered Setting
 Universal Convergence of Semimeasures on Individual Random Sequences
Online Sequence Prediction
 A Criterion for the Existence of Predictive Complexity for Binary Games
 Full Information Game with Gains and Losses
 Prediction with Expert Advice by Following the Perturbed Leader for General Weights
 On the Convergence Speed of MDL Predictions for Bernoulli Sequences
Aooroximate Optimzation Algorthms
Logic Based Learning
Query and Reinforcement Learning
TUTORIAL PAPERS
Author Index
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