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JMLR
2010
143views more  JMLR 2010»
15 years 1 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»
15 years 3 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»
15 years 3 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»
16 years 10 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
16 years 2 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