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ICRA
2005
IEEE
176views Robotics» more  ICRA 2005»
15 years 3 months ago
Auto-supervised learning in the Bayesian Programming Framework
Domestic and real world robotics requires continuous learning of new skills and behaviors to interact with humans. Auto-supervised learning, a compromise between supervised and co...
Pierre Dangauthier, Pierre Bessière, Anne S...
CIKM
2011
Springer
13 years 9 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
15 years 6 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
ICCV
2011
IEEE
13 years 9 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
ISSTA
2006
ACM
15 years 3 months ago
A regression tests selection technique for aspect-oriented programs
As the Aspect-Oriented Software Development gains popularity, there is growing interest as developing for existing object-oriented software aspects to address the crosscutting pro...
Guoqing Xu