This paper presents a statistical model for textures that uses a non-negative decomposition on a set of local atoms learned from an exemplar. This model is described by the varianc...
The proportionate normalized least-mean squares (PNLMS) adaptation algorithm exploits the sparse nature of acoustic impulse responses and assigns adaptation gain proportional to t...
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
stractions are extensively used to understand and solve challenging computational problems in various scientific and engineering domains. They have particularly gained prominence...
This paper presents a framework for implicit deformable models and a pair of new algorithms for solving the nonlinear partial di erential equations that result from this framework...