We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Multi-party communication complexity involves distributed computation of a function over inputs held by multiple distributed players. A key focus of distributed computing research...
Binbin Chen, Haifeng Yu, Yuda Zhao, Phillip B. Gib...
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
A fundamental problem in distributed computation is the distributed evaluation of functions. The goal is to determine the value of a function over a set of distributed inputs, in ...
— The problem of accurate 6-DoF pose estimation of 3D objects based on their shape has so far been solved only for specific object geometries. Edge-based recognition and trackin...