We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...
Since health care on foods is drawing people's attention recently, a system that can record everyday meals easily is being awaited. In this paper, we propose an automatic foo...
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...