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» Input Modeling Using Quantile Statistical Methods
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123
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BIBE
2010
IEEE
146views Bioinformatics» more  BIBE 2010»
15 years 3 months ago
Methods for Designing Reliable Probe Arrays
Recent advances in biosensing technologies have led to applications of biosensor probe arrays for rapid identification of biological agents such as drugs, gene expressions, protein...
Michele Lombardi, Luca Benini, Abhishek Garg, Giov...
137
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JSAC
2007
120views more  JSAC 2007»
15 years 2 months ago
On the Capacity of MIMO Wireless Channels with Dynamic CSIT
Abstract— Transmit channel side information (CSIT) can significantly increase MIMO wireless capacity. Due to delay in acquiring this information, however, the time-selective fad...
Mai Vu, Arogyaswami Paulraj
142
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ICMLA
2009
15 years 15 days ago
Learning Deep Neural Networks for High Dimensional Output Problems
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Benjamin Labbé, Romain Hérault, Cl&e...
136
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ACL
1998
15 years 4 months ago
Machine Translation with a Stochastic Grammatical Channel
We introduce a stochastic grammatical channel model for machine translation, that synthesizes several desirable characteristics of both statistical and grammatical machine transla...
Dekai Wu, Hongsing Wong
ECCV
1998
Springer
16 years 4 months ago
A Probabilistic Approach to Object Recognition Using Local Photometry and Global Geometry
Many object classes, including human faces, can be modeled as a set of characteristic parts arranged in a variable spatial con guration. We introduce a simpli ed model of a deforma...
Michael C. Burl, Markus Weber, Pietro Perona