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ICML
2000
IEEE
15 years 10 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
ICML
2000
IEEE
15 years 10 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
SIGMOD
2002
ACM
120views Database» more  SIGMOD 2002»
15 years 10 months ago
Exploiting statistics on query expressions for optimization
Statistics play an important role in influencing the plans produced by a query optimizer. Traditionally, optimizers use statistics built over base tables and assume independence b...
Nicolas Bruno, Surajit Chaudhuri
DCC
2007
IEEE
15 years 9 months ago
Lifting of divisible designs
The aim of this paper is to present a construction of t-divisible designs for t > 3, because such divisible designs seem to be missing in the literature. To this end, tools suc...
Andrea Blunck, Hans Havlicek, Corrado Zanella
DSN
2007
IEEE
15 years 4 months ago
Architecture-Level Soft Error Analysis: Examining the Limits of Common Assumptions
This paper concerns the validity of a widely used method for estimating the architecture-level mean time to failure (MTTF) due to soft errors. The method first calculates the fai...
Xiaodong Li, Sarita V. Adve, Pradip Bose, Jude A. ...