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ICML
2000
IEEE
16 years 7 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
16 years 7 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»
16 years 7 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
16 years 6 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
16 years 1 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. ...