Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
— Determining the optimal topology of a graph is pertinent to many domains, as graphs can be used to model a variety of systems. Evolutionary algorithms constitute a popular opti...
We describe a novel method for authenticating multicast packets that is robust against packet loss. Our main focus is to minimize the size of the communication overhead required t...
Jung Min Park, Edwin K. P. Chong, Howard Jay Siege...
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
This paper presents a sparse representation of 2D planar shape through the composition of warping functions, termed formlets, localized in scale and space. Each formlet subjects t...