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» On the Complexity of Ordinal Clustering
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ECAI
2004
Springer
14 years 2 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
DAWAK
2000
Springer
14 years 1 months ago
COFE: A Scalable Method for Feature Extraction from Complex Objects
Abstract. Feature Extraction, also known as Multidimensional Scaling, is a basic primitive associated with indexing, clustering, nearest neighbor searching and visualization. We co...
Gabriela Hristescu, Martin Farach-Colton
COLT
2008
Springer
13 years 10 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
ICDE
2012
IEEE
285views Database» more  ICDE 2012»
11 years 11 months ago
Multidimensional Analysis of Atypical Events in Cyber-Physical Data
— A Cyber-Physical System (CPS) integrates physical devices (e.g., sensors, cameras) with cyber (or informational) components to form a situation-integrated analytical system tha...
Lu An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Wen...
ICCD
2003
IEEE
111views Hardware» more  ICCD 2003»
14 years 5 months ago
Reducing Operand Transport Complexity of Superscalar Processors using Distributed Register Files
A critical problem in wide-issue superscalar processors is the limit on cycle time imposed by the central register file and operand bypass network. In this paper, a distributed re...
Santithorn Bunchua, D. Scott Wills, Linda M. Wills