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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
JCDL
2006
ACM
71views Education» more  JCDL 2006»
16 years 22 days ago
Using controlled query generation to evaluate blind relevance feedback algorithms
Currently in document retrieval there are many algorithms each with different strengths and weakness. There is some difficulty, however, in evaluating the impact of the test quer...
Chris Jordan, Carolyn R. Watters, Qigang Gao
HYBRID
2001
Springer
15 years 11 months ago
Accurate Event Detection for Simulating Hybrid Systems
It has been observed that there are a variety of situations in which the most popular hybrid simulation methods can fail to properly detect the occurrence of discrete events. In th...
Joel M. Esposito, Vijay Kumar, George J. Pappas
COLT
1993
Springer
15 years 11 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
TIFS
2008
157views more  TIFS 2008»
15 years 6 months ago
Subspace Approximation of Face Recognition Algorithms: An Empirical Study
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
Pranab Mohanty, Sudeep Sarkar, Rangachar Kasturi, ...