Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing th...
Mert R. Sabuncu, B. T. Thomas Yeo, Koen Van Leem...
Executing large number of independent tasks or tasks that perform minimal inter-task communication in parallel is a common requirement in many domains. In this paper, we present o...
Xiaohong Qiu, Jaliya Ekanayake, Scott Beason, Thil...
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
We present a scheme for generating new valid inequalities for mixed integer programs by taking pairwise combinations of existing valid inequalities. Our scheme is related to mixed...
Abstract: A novel self-organizing algorithm for conformational sampling is introduced, in which precomputed conformations of rigid fragments are used as templates to enforce the de...