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ISAAC
2010
Springer
313views Algorithms» more  ISAAC 2010»
8 years 6 months ago
A Cache-Oblivious Implicit Dictionary with the Working Set Property
Abstract. In this paper we present an implicit dictionary with the working set property i.e. a dictionary supporting insert(e), delete(x) and predecessor(x) in O(log n) time and se...
Gerth Stølting Brodal, Casper Kejlberg-Rasm...
VC
2008
143views more  VC 2008»
8 years 8 months ago
A single-pass GPU ray casting framework for interactive out-of-core rendering of massive volumetric datasets
We present an adaptive out-of-core technique for rendering massive scalar volumes employing single pass GPU raycasting. The method is based on the decomposition of a volumetric dat...
Enrico Gobbetti, Fabio Marton, José Antonio...
ALGORITHMICA
2005
135views more  ALGORITHMICA 2005»
8 years 8 months ago
Queaps
A new priority queue structure, the queap, is introduced. The queap executes insertion in O(1) amortized time and extract-min in O(log(k+2)) amortized time if there are k items th...
John Iacono, Stefan Langerman
JMLR
2006
89views more  JMLR 2006»
8 years 8 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
ISLPED
2010
ACM
169views Hardware» more  ISLPED 2010»
8 years 8 months ago
TurboTag: lookup filtering to reduce coherence directory power
On-chip coherence directories of today's multi-core systems are not energy efficient. Coherence directories dissipate a significant fraction of their power on unnecessary loo...
Pejman Lotfi-Kamran, Michael Ferdman, Daniel Crisa...
AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
9 years 4 days ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
ANNPR
2006
Springer
9 years 4 days ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe
ICSE
2010
IEEE-ACM
9 years 12 days ago
Code bubbles: rethinking the user interface paradigm of integrated development environments
Today’s integrated development environments (IDEs) are hampered by their dependence on files and file-based editing. We propose a novel user interface that is based on collectio...
Andrew Bragdon, Steven P. Reiss, Robert C. Zelezni...
SIGMETRICS
2000
ACM
9 years 23 days ago
An analytical model of the working-set sizes in decision-support systems
This paper presents an analytical model to study how working sets scale with database size and other applications parameters in decision-support systems (DSS). The model uses appl...
Magnus Karlsson, Per Stenström
ICSE
2010
IEEE-ACM
9 years 1 months ago
A research demonstration of code bubbles
Today’s integrated development environments (IDEs) are hampered by their dependence on files and file-based editing. We propose a novel user interface that is based on collectio...
Andrew Bragdon, Steven P. Reiss, Robert C. Zelezni...
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