Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then tra...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...
With the proliferation of camera phones, new information retrieval applications will emerge. The image of a scene captured by a camera phone can be a query to a remote server to i...
A steganalysis system based on 2-D Markov chain of thresholded prediction-error image is proposed in this paper. Image pixels are predicted with their neighboring pixels, and the ...