Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Hashing, which tries to learn similarity-preserving binary codes for data representation, has been widely used for efficient nearest neighbor search in massive databases due to i...
This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
This paper reports our experiments for TRECVID 2008 tasks: high level feature extraction, search and contentbased copy detection. For the high level feature extraction task, we use...
Duy-Dinh Le, Xiaomeng Wu, Shin'ichi Satoh, Sheetal...
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...