We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
Abstract. The propose of this paper is to introduce a new regularization formulation for inverse problems in computer vision and image processing that allows one to reconstruct sec...
A simple and computationally lightweight video coder employing shape-adaptive, embedded intraframe coding and wavelet-domain conditional replenishment is proposed. Robustness to p...
In this paper, we show how two classical sparse recovery algorithms, Orthogonal Matching Pursuit and Basis Pursuit, can be naturally extended to recover block-sparse solutions for...