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CVPR
2001
IEEE
14 years 9 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
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
BMCBI
2006
119views more  BMCBI 2006»
13 years 7 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 7 months ago
On-board analysis of uncalibrated data for a spacecraft at mars
Analyzing data on-board a spacecraft as it is collected enables several advanced spacecraft capabilities, such as prioritizing observations to make the best use of limited bandwid...
Benyang Tang, Kiri Wagstaff, Rebecca Castañ...
CDC
2008
IEEE
149views Control Systems» more  CDC 2008»
13 years 9 months ago
Distributed computation under bit constraints
Abstract-- A network of nodes communicate via noisy channels. Each node has some real-valued initial measurement or message. The goal of each of the nodes is to acquire an estimate...
Ola Ayaso, Devavrat Shah, Munther A. Dahleh