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ICASSP
2011
IEEE
12 years 11 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
ICIP
2003
IEEE
14 years 9 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...
MVA
1990
114views Computer Vision» more  MVA 1990»
13 years 8 months ago
Radar Image Processing for Locating Underground Linear Objects
This paper presents an image processing method for locating underground linear objects using ground-probing radar data. One of the problems when using groundprobing radars is how ...
Toru Kaneko
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
13 years 11 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
CORR
2012
Springer
220views Education» more  CORR 2012»
12 years 3 months ago
A Bijective String Sorting Transform
Given a string of characters, the Burrows-Wheeler Transform rearranges the characters in it so as to produce another string of the same length which is more amenable to compressio...
Joseph Yossi Gil, David Allen Scott