Advances in Machine Learning (Record no. 182864)
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| fixed length control field | 06230nam a22006495i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-642-05224-8 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423125909.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100301s2009 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783642052248 |
| -- | 978-3-642-05224-8 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-642-05224-8 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA76.9.D343 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UNF |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQE |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM021030 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UNF |
| Source | thema |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQE |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.312 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Advances in Machine Learning |
| Medium | [electronic resource] : |
| Remainder of title | First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009. Proceedings / |
| Statement of responsibility, etc | edited by Zhi-Hua Zhou, Takashi Washio. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2009. |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg : |
| -- | Imprint: Springer, |
| -- | 2009. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XV, 413 p. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Artificial Intelligence, |
| International Standard Serial Number | 2945-9141 ; |
| Volume number/sequential designation | 5828 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Keynote and Invited Talks -- Machine Learning and Ecosystem Informatics: Challenges and Opportunities -- Density Ratio Estimation: A New Versatile Tool for Machine Learning -- Transfer Learning beyond Text Classification -- Regular Papers -- Improving Adaptive Bagging Methods for Evolving Data Streams -- A Hierarchical Face Recognition Algorithm -- Estimating Likelihoods for Topic Models -- Conditional Density Estimation with Class Probability Estimators -- Linear Time Model Selection for Mixture of Heterogeneous Components -- Max-margin Multiple-Instance Learning via Semidefinite Programming -- A Reformulation of Support Vector Machines for General Confidence Functions -- Robust Discriminant Analysis Based on Nonparametric Maximum Entropy -- Context-Aware Online Commercial Intention Detection -- Feature Selection via Maximizing Neighborhood Soft Margin -- Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix -- Community Detection on Weighted Networks: A Variational Bayesian Method -- Averaged Naive Bayes Trees: A New Extension of AODE -- Automatic Choice of Control Measurements -- Coupled Metric Learning for Face Recognition with Degraded Images -- Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model -- On Compressibility and Acceleration of Orthogonal NMF for POMDP Compression -- Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes -- Query Selection via Weighted Entropy in Graph-Based Semi-supervised Classification -- Learning Algorithms for Domain Adaptation -- Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble -- Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis -- Privacy-Preserving Evaluation of Generalization Error and Its Applicationto Model and Attribute Selection -- Coping with Distribution Change in the Same Domain Using Similarity-Based Instance Weighting -- Monte-Carlo Tree Search in Poker Using Expected Reward Distributions -- Injecting Structured Data to Generative Topic Model in Enterprise Settings -- Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer vision. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Image processing |
| General subdivision | Digital techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Pattern recognition systems. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Vision. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Models of Computation. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Automated Pattern Recognition. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Zhou, Zhi-Hua. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Washio, Takashi. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783642052231 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783642052255 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Artificial Intelligence, |
| -- | 2945-9141 ; |
| Volume number/sequential designation | 5828 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-642-05224-8">https://doi.org/10.1007/978-3-642-05224-8</a> |
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| -- | ZDB-2-LNC |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
No items available.