Download e-book for kindle: Advances in Machine Learning: First Asian Conference on by Thomas G. Dietterich (auth.), Zhi-Hua Zhou, Takashi Washio

By Thomas G. Dietterich (auth.), Zhi-Hua Zhou, Takashi Washio (eds.)

ISBN-10: 364205224X

ISBN-13: 9783642052248

The First Asian convention on desktop studying (ACML 2009) was once held at Nanjing, China in the course of November 2–4, 2009.This was once the ?rst variation of a sequence of annual meetings which objective to supply a number one overseas discussion board for researchers in computer studying and similar ?elds to percentage their new principles and study ?ndings. This 12 months we obtained 113 submissions from 18 international locations and areas in Asia, Australasia, Europe and North the USA. The submissions went via a r- orous double-blind reviewing technique. so much submissions acquired 4 stories, a number of submissions bought ?ve reports, whereas simply numerous submissions acquired 3 experiences. each one submission used to be dealt with through a space Chair who coordinated discussions between reviewers and made suggestion at the submission. this system Committee Chairs tested the stories and meta-reviews to extra warrantly the reliability and integrity of the reviewing procedure. Twenty-nine - pers have been chosen after this approach. to make sure that vital revisions required by means of reviewers have been integrated into the ?nal authorised papers, and to permit submissions which might have - tential after a cautious revision, this yr we introduced a “revision double-check” method. in brief, the above-mentioned 29 papers have been conditionally permitted, and the authors have been asked to include the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal model and the revision record of every conditionally permitted paper used to be tested by way of the world Chair and application Committee Chairs. Papers that didn't go the exam have been ?nally rejected.

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Additional info for Advances in Machine Learning: First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009. Proceedings

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Often, ensemble learning classifiers provide superior predictive performance and they are easier to scale and parallelize than single classifier methods. In [6] two new state-of-the-art bagging methods were presented: ASHT Bagging using trees of different sizes, and ADWIN Bagging using a change detector to decide when to discard underperforming ensemble members. This paper improves on ASHT Bagging by speeding up the time taken to adapt to changes in the distribution generating the stream. It improves on ADWIN Bagging by employing Hoeffding Adaptive Trees, trees that can adaptively learn from evolving data streams.

Springer, Heidelberg (2008) 30. : Transfer learning for collaborative filtering via a rating-matrix generative model. In: ICML, pp. 617–624 (2009) 31. : Estimating location using Wi-Fi. hk/˜qyang/ICDMDMC07/ 32. : The information bottleneck method. In: Proc. of the 37th Annual Allerton Conference on Communication, Control and Computing, pp. 368–377 33. : Cross-lingual text categorization. T. ) ECDL 2003. LNCS, vol. 2769, pp. 126–139. Springer, Heidelberg (2003) 34. : Bilingual topic aspect classification with a few training examples.

Forest trees for on-line data. In: SAC 2004: Proceedings of the 2004 ACM symposium on Applied computing, pp. 632–636. : Accurate decision trees for mining high-speed data streams. In: KDD 2003, August 2003, pp. : Adaptive Filtering and Change Detection. : Splice-2 comparative evaluation: Electricity pricing. : Mining time-changing data streams. In: KDD 2001, San Francisco, CA, pp. 97–106. : Pruning adaptive boosting. In: ICML 1997, pp. : Machine Learning. : Online bagging and boosting. In: Artificial Intelligence and Statistics 2001, pp.

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Advances in Machine Learning: First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009. Proceedings by Thomas G. Dietterich (auth.), Zhi-Hua Zhou, Takashi Washio (eds.)

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