Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Fault-tolerant distributed real-time systems are presently facing a lot of new challenges. Although many techniques provide effective masking of node failures on the architectural...
In this paper, we propose a novel approach for understanding and analyzing the online handwritten chemical formulas. With the structural characteristics, semantic rules, and more ...
To develop effective learning algorithms for online cursive word recognition is still a challenge research issue. In this paper, we propose a probabilistic framework to model the ...
We study models that characterize pen trajectories of online handwritten characters in a fine manner. We propose radical based fine trajectory hidden Markov models (HMMs), which...