The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
Abstract--This work studies the near-optimality versus the complexity of distributed configuration management for wireless networks. We first develop a global probabilistic graphic...
As a well known fixed-point iteration algorithm for kernel
density mode-seeking, Mean-Shift has attracted wide attention
in pattern recognition field. To date, Mean-Shift algorit...
Appropriate rate control plays a very important role in encoding motion pictures under the constant bit-rate. One of the requirements for rate control is minimizing temporal fluct...
Atsushi Matsumura, Sei Naito, Ryoichi Kawada, Atsu...
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...