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ICASSP
2011
IEEE
13 years 3 months ago
Incoherent color frames for compressive demosaicing
In this paper, we explore the notion of using frames to project sensed colors within their inherently 3D space onto a larger number of color basis vectors. In particular, we devel...
Abdolreza Abdolhosseini Moghadam, Mohammad Aghagol...
ICASSP
2011
IEEE
13 years 4 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
ICASSP
2011
IEEE
13 years 4 months ago
Discriminative training for Bayesian sensing hidden Markov models
We describe feature space and model space discriminative training for a new class of acoustic models called Bayesian sensing hidden Markov models (BS-HMMs). In BS-HMMs, speech dat...
George Saon, Jen-Tzung Chien
TNN
2010
176views Management» more  TNN 2010»
13 years 7 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
TKDE
2008
126views more  TKDE 2008»
14 years 10 days ago
The Discrete Basis Problem
Matrix decomposition methods represent a data matrix as a product of two smaller matrices: one containing basis vectors that represent meaningful concepts in the data, and another ...
Pauli Miettinen, Taneli Mielikäinen, Aristide...
IVC
2008
117views more  IVC 2008»
14 years 12 days ago
Direct type-specific conic fitting and eigenvalue bias correction
A new method to fit specific types of conics to scattered data points is introduced. Direct, specific fitting of ellipses and hyperbolae is achieved by imposing a quadratic constr...
Matthew Harker, Paul O'Leary, Paul J. Zsombor-Murr...
ESANN
2006
14 years 1 months ago
Efficient Forward Regression with Marginal Likelihood
We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new bas...
Ping Sun, Xin Yao
ICA
2007
Springer
14 years 2 months ago
Bayesian Estimation of Overcomplete Independent Feature Subspaces for Natural Images
In this paper, we propose a Bayesian estimation approach to extend independent subspace analysis (ISA) for an overcomplete representation without imposing the orthogonal constraint...
Libo Ma, Liqing Zhang
ANTS
2010
Springer
262views Algorithms» more  ANTS 2010»
14 years 4 months ago
Short Bases of Lattices over Number Fields
Lattices over number elds arise from a variety of sources in algorithmic algebra and more recently cryptography. Similar to the classical case of Z-lattices, the choice of a nice,...
Claus Fieker, Damien Stehlé
ETS
2006
IEEE
119views Hardware» more  ETS 2006»
14 years 6 months ago
On-Chip Test Generation Using Linear Subspaces
A central problem in built-in self test (BIST) is how to efficiently generate a small set of test vectors that detect all targeted faults. We propose a novel solution that uses l...
Ramashis Das, Igor L. Markov, John P. Hayes