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JMLR
2008
230views more  JMLR 2008»
15 years 6 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
16 years 10 days ago
On Feature Selection through Clustering
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...
POPL
2008
ACM
16 years 7 months ago
From dirt to shovels: fully automatic tool generation from ad hoc data
An ad hoc data source is any semistructured data source for which useful data analysis and transformation tools are not readily available. Such data must be queried, transformed a...
Kathleen Fisher, David Walker, Kenny Qili Zhu, Pet...
PODS
2008
ACM
211views Database» more  PODS 2008»
16 years 6 months ago
The power of two min-hashes for similarity search among hierarchical data objects
In this study we propose sketching algorithms for computing similarities between hierarchical data. Specifically, we look at data objects that are represented using leaf-labeled t...
Sreenivas Gollapudi, Rina Panigrahy
STOC
2003
ACM
141views Algorithms» more  STOC 2003»
16 years 7 months ago
Better streaming algorithms for clustering problems
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy