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NIPS
2008
15 years 1 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
BMCBI
2004
114views more  BMCBI 2004»
14 years 11 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
ICMCS
2006
IEEE
177views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Mixed Type Audio Classification with Support Vector Machine
Content-based classification of audio data is an important problem for various applications such as overall analysis of audio-visual streams, boundary detection of video story se...
Lei Chen 0002, Sule Gündüz, M. Tamer &Ou...
JITECH
2010
160views more  JITECH 2010»
14 years 6 months ago
Social software for business process modeling
Formal models of business processes are used for a variety of purposes. But where the elicitation of the characteristics of a business process usually takes place in a collaborati...
Agnes Koschmider, Minseok Song, Hajo A. Reijers
ICCV
2011
IEEE
13 years 11 months ago
DTAM: Dense Tracking and Mapping in Real-Time
DTAM is a system for real-time camera tracking and reconstruction which relies not on feature extraction but dense, every pixel methods. As a single hand-held RGB camera flies ov...
Richard A. Newcombe, Steven Lovegrove, Andrew J. D...