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JMLR
2010
143views more  JMLR 2010»
13 years 7 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
AO
2006
97views more  AO 2006»
13 years 8 months ago
An ontological model of device function: industrial deployment and lessons learned
Functionality is one of the key concepts of knowledge about artifacts. Functional knowledge shows a part of designer's intention (so-called design rationale), and thus its sha...
Yoshinobu Kitamura, Yusuke Koji, Riichiro Mizoguch...
AIR
2006
152views more  AIR 2006»
13 years 8 months ago
Machine learning: a review of classification and combining techniques
Abstract Supervised classification is one of the tasks most frequently carried out by socalled Intelligent Systems. Thus, a large number of techniques have been developed based on ...
Sotiris B. Kotsiantis, Ioannis D. Zaharakis, Panay...
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
DCC
2008
IEEE
14 years 8 months ago
Object-Based Regions of Interest for Image Compression
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
Sunhyoung Han, Nuno Vasconcelos