The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who coordinated discussions among reviewers and made recommendation on the submission. The Program Committee Chairs examined the reviews and meta-reviews to further guarantee the reliability and integrity of the reviewing process. Twenty-nine - pers were selected after this process. To ensure that important revisions required by reviewers were incorporated into the ?nal accepted papers, and to allow submissions which would have - tential after a careful revision, this year we launched a “revision double-check” process. In short, the above-mentioned 29 papers were conditionally accepted, and the authors were requested to incorporate the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal version and the revision list of each conditionally accepted paper was examined by the Area Chair and Program Committee Chairs. Papers that failed to pass the examination were ?nally rejected.
Author(s): Thomas G. Dietterich (auth.), Zhi-Hua Zhou, Takashi Washio (eds.)
Series: Lecture Notes in Computer Science 5828 : Lecture Notes in Artificial Intelligence
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2009
Language: English
Pages: 413
Tags: Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Computer Imaging, Vision, Pattern Recognition and Graphics; Models and Principles; Image Processing and Computer Vision; Pattern Recognition
Front Matter....Pages -
Machine Learning and Ecosystem Informatics: Challenges and Opportunities....Pages 1-5
Density Ratio Estimation: A New Versatile Tool for Machine Learning....Pages 6-9
Transfer Learning beyond Text Classification....Pages 10-22
Improving Adaptive Bagging Methods for Evolving Data Streams....Pages 23-37
A Hierarchical Face Recognition Algorithm....Pages 38-50
Estimating Likelihoods for Topic Models....Pages 51-64
Conditional Density Estimation with Class Probability Estimators....Pages 65-81
Linear Time Model Selection for Mixture of Heterogeneous Components....Pages 82-97
Max-margin Multiple-Instance Learning via Semidefinite Programming....Pages 98-108
A Reformulation of Support Vector Machines for General Confidence Functions....Pages 109-119
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy....Pages 120-134
Context-Aware Online Commercial Intention Detection....Pages 135-149
Feature Selection via Maximizing Neighborhood Soft Margin....Pages 150-161
Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix....Pages 162-175
Community Detection on Weighted Networks: A Variational Bayesian Method....Pages 176-190
Averaged Naive Bayes Trees: A New Extension of AODE....Pages 191-205
Automatic Choice of Control Measurements....Pages 206-219
Coupled Metric Learning for Face Recognition with Degraded Images....Pages 220-233
Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model....Pages 234-247
On Compressibility and Acceleration of Orthogonal NMF for POMDP Compression....Pages 248-262
Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes....Pages 263-277
Query Selection via Weighted Entropy in Graph-Based Semi-supervised Classification....Pages 278-292
Learning Algorithms for Domain Adaptation....Pages 293-307
Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble....Pages 308-321
Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis....Pages 322-337
Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection....Pages 338-353
Coping with Distribution Change in the Same Domain Using Similarity-Based Instance Weighting....Pages 354-366
Monte-Carlo Tree Search in Poker Using Expected Reward Distributions....Pages 367-381
Injecting Structured Data to Generative Topic Model in Enterprise Settings....Pages 382-395
Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction....Pages 396-411
Back Matter....Pages -
