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SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
14 years 13 days ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
ICDAR
2011
IEEE
12 years 10 months ago
Symbol Spotting in Line Drawings through Graph Paths Hashing
—In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can ...
Anjan Dutta, Josep Lladós, Umapada Pal
RTCSA
2000
IEEE
14 years 3 months ago
Task attribute assignment of fixed priority scheduled tasks to reenact off-line schedules
A number of industrial applications advocate the use of time-triggered approaches for reasons of predictability, distribution, and particular constraints such as jitter or end-to-...
Radu Dobrin, Yusuf Özdemir, Gerhard Fohler
COR
2007
106views more  COR 2007»
13 years 10 months ago
On a stochastic sequencing and scheduling problem
We present a framework for solving multistage pure 0–1 programs for a widely used sequencing and scheduling problem with uncertainty in the objective function coefficients, the...
Antonio Alonso-Ayuso, Laureano F. Escudero, M. Ter...
CIKM
2011
Springer
12 years 11 months ago
MTopS: scalable processing of continuous top-k multi-query workloads
A continuous top-k query retrieves the k most preferred objects in a data stream according to a given preference function. These queries are important for a broad spectrum of appl...
Avani Shastri, Di Yang, Elke A. Rundensteiner, Mat...