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ICCV
2005
IEEE
14 years 1 months ago
Learning Models for Predicting Recognition Performance
This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Rong Wang, Bir Bhanu
VLDB
2004
ACM
121views Database» more  VLDB 2004»
14 years 26 days ago
An Automatic Data Grabber for Large Web Sites
We demonstrate a system to automatically grab data from data intensive web sites. The system first infers a model that describes at the intensional level the web site as a collec...
Valter Crescenzi, Giansalvatore Mecca, Paolo Meria...
UAI
2008
13 years 9 months ago
Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
Max Welling, Yee Whye Teh, Bert Kappen
EMNLP
2007
13 years 9 months ago
Online Large-Margin Training for Statistical Machine Translation
We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of p...
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki ...
ISCA
1993
IEEE
115views Hardware» more  ISCA 1993»
13 years 11 months ago
Parity Logging Overcoming the Small Write Problem in Redundant Disk Arrays
Parity encoded redundant disk arrays provide highly reliable, cost effective secondary storage with high performance for read accesses and large write accesses. Their performance ...
Daniel Stodolsky, Garth A. Gibson, Mark Holland