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» Using Learning for Approximation in Stochastic Processes
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NLPRS
2001
Springer
13 years 12 months ago
A New Prosodic Phrasing Model for Chinese TTS Systems
This paper proposes a new prosodic phrasing model for Chinese text-tospeech systems. First, in contrast to the commonly used CART techniques, we propose a new inductive learning a...
Weijun Chen, Fuzong Lin, Jianmin Li, Bo Zhang
CVPR
2005
IEEE
14 years 9 months ago
Learning a Similarity Metric Discriminatively, with Application to Face Verification
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...
Sumit Chopra, Raia Hadsell, Yann LeCun
CVPR
2007
IEEE
14 years 9 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
WCNC
2010
IEEE
13 years 11 months ago
Optimal Tradeoff Between Transmission Rate and Packet Duration in Wireless Ad Hoc Networks
—This paper considers the tradeoff between bursty and continuous transmissions in wireless ad hoc networks. In our network model, packets belonging to specific transmitters arri...
Jon E. Corneliussen, Mariam Kaynia, Geir E. &Oslas...
EGH
2010
Springer
13 years 5 months ago
Hardware implementation of micropolygon rasterization with motion and defocus blur
Current GPUs rasterize micropolygons (polygons approximately one pixel in size) inefficiently. Additionally, they do not natively support triangle rasterization with jittered samp...
J. S. Brunhaver, Kayvon Fatahalian, Pat Hanrahan