机器学习： ECML 2006 /会议录/Machine learning--ECML 2006

This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held in Berlin, Germany in September 2006, jointly with PKDD 2006.
　　The 46 revised full papers and 36 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 564 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available.
The scope of LNAI spans the whole range of artificial intelligence and intelli- gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes.
proceedings (published in time for the respective conference)；
post-proceedings (consisting of thoroughly revised final full papers)；
research monographs (which may be based on PhD work).

Invited Talks
On Temporal Evolution in Data Streams
The hlture of CiteSeer: CiteSeerx
Learning to Have Fun
Winning the DARPA Grand Challenge
Challenges of Urban Sensing
Long Papers
Learning in One-Shot
Strategic Form Games
A Selective Sainpling Strategy for Label Ranking
Combinatorial Markov Random Fields
Learning Stochastic Tree Edit Distance
Pertinent Background Knowledge for Learning Protein Grammars
Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies
Sequence Discrimination Using Phase-Type Distributions
Languages as Hyperplanes: Grammatical Inference with String Kernels
Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning
Fisher Kernels for Relational Data
Evaluating Misclassifications in hnbalanced Data
Improving Control-Knowledge Acquisition for Planning by Active Learning
PAC-Learning of Markov Models with Hidden State
A Discriminative Approach for the Retrieval of Images from Text Queries
TildeCRF: Conditional Random Fields for Logical Sequences
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Bayesian Learning of Markov Network Structure
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
……
Short Papers
Author Index