Sparse representation has been applied to visual tracking by finding the best candidate with minimal reconstruction error using target templates. However most sparse representati...
Standard Machine Learning approaches to text classification use the bag-of-words representation of documents to deceive the classification target function. Typical linguistic stru...
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinke...
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...