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» Evaluating algorithms that learn from data streams
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ICMLA
2010
15 years 2 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
ICML
2007
IEEE
16 years 5 months ago
Non-isometric manifold learning: analysis and an algorithm
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
Piotr Dollár, Serge J. Belongie, Vincent Ra...
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 2 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
CVPR
1999
IEEE
16 years 6 months ago
Integrating Shape from Shading and Range Data Using Neural Networks
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
EDBT
2009
ACM
136views Database» more  EDBT 2009»
15 years 11 months ago
Rule-based multi-query optimization
Data stream management systems usually have to process many long-running queries that are active at the same time. Multiple queries can be evaluated more efficiently together tha...
Mingsheng Hong, Mirek Riedewald, Christoph Koch, J...