Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
We propose a novel approach for improving level set seg-
mentation methods by embedding the potential functions
from a discriminatively trained conditional random field
(CRF) in...
Dana Cobzas (University of Alberta), Mark Schmidt ...
We address corpus building situations, where complete annotations to the whole corpus is time consuming and unrealistic. Thus, annotation is done only on crucial part of sentences...
Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hirok...
DRAM is facing severe scalability challenges in sub-45nm technology nodes due to precise charge placement and sensing hurdles in deep-submicron geometries. Resistive memories, suc...
Engin Ipek, Jeremy Condit, Edmund B. Nightingale, ...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...