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NIPS
2008
14 years 11 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
76
Voted
BMCBI
2004
114views more  BMCBI 2004»
14 years 9 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 3 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...
105
Voted
JITECH
2010
160views more  JITECH 2010»
14 years 4 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 9 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...