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TIP
2008
128views more  TIP 2008»
15 years 7 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
SIGPRO
2010
73views more  SIGPRO 2010»
15 years 5 months ago
Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers
This article considers the application of the unscented transformation to approximate fixed-interval optimal smoothing of continuous-time non-linear stochastic systems. The propo...
Simo Särkkä
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 7 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
PPSC
1997
15 years 8 months ago
The Future Fast Fourier Transform?
It seems likely that improvements in arithmetic speed will continue to outpace advances in communication bandwidth. Furthermore, as more and more problems are working on huge datas...
Alan Edelman, Peter McCorquodale, Sivan Toledo
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
15 years 2 months ago
Aggregation-based model reduction of a Hidden Markov Model
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Kun Deng, Prashant G. Mehta, Sean P. Meyn