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MM
2005
ACM
171views Multimedia» more  MM 2005»
14 years 3 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
CORR
2011
Springer
183views Education» more  CORR 2011»
13 years 1 months ago
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Foster J. Provost, Gary M. Weiss
ICASSP
2010
IEEE
13 years 10 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
GLVLSI
2005
IEEE
133views VLSI» more  GLVLSI 2005»
14 years 3 months ago
Generating decision regions in analog measurement spaces
We develop a neural network that learns to separate the nominal from the faulty instances of a circuit in a measurement space. We demonstrate that the required separation boundari...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris
AINA
2007
IEEE
13 years 9 months ago
Detecting Anomaly Node Behavior in Wireless Sensor Networks
Wireless sensor networks are usually deployed in a way “once deployed, never changed”. The actions of sensor nodes are either pre-scheduled inside chips or triggered to respon...
Qinghua Wang, Tingting Zhang