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...
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...
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...
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...
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...
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...
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...
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...
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...
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...