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213
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ICONIP
2007
15 years 9 months ago
Principal Component Analysis for Sparse High-Dimensional Data
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
Tapani Raiko, Alexander Ilin, Juha Karhunen
204
Voted
ALENEX
2003
144views Algorithms» more  ALENEX 2003»
15 years 8 months ago
Cache-Conscious Sorting of Large Sets of Strings with Dynamic Tries
Ongoing changes in computer performance are affecting the efficiency of string sorting algorithms. The size of main memory in typical computers continues to grow, but memory acce...
Ranjan Sinha, Justin Zobel
NIPS
2004
15 years 8 months ago
Non-Local Manifold Tangent Learning
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
Yoshua Bengio, Martin Monperrus
197
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ICML
2010
IEEE
15 years 8 months ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
Nader H. Bshouty, Philip M. Long
205
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CORR
2010
Springer
85views Education» more  CORR 2010»
15 years 7 months ago
A control-theoretical methodology for the scheduling problem
This paper presents a novel methodology to develop scheduling algorithms. The scheduling problem is phrased as a control problem, and control-theoretical techniques are used to de...
Carlo A. Furia, Alberto Leva, Martina Maggio, Paol...