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NC
2006
132views Neural Networks» more  NC 2006»
15 years 6 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu
MANSCI
2007
100views more  MANSCI 2007»
15 years 6 months ago
Dynamic Assortment with Demand Learning for Seasonal Consumer Goods
Companies such as Zara and World Co. have recently implemented novel product development processes and supply chain architectures enabling them to make more product design and ass...
Felipe Caro, Jérémie Gallien
TSMC
2002
105views more  TSMC 2002»
15 years 6 months ago
On the use of learning automata in the control of broadcast networks: a methodology
Due to its fixed assignment nature, the well-known time division multiple access (TDMA) protocol suffers from poor performance when the offered traffic is bursty. In this paper, an...
Georgios I. Papadimitriou, Mohammad S. Obaidat, An...
BMVC
2010
15 years 4 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
15 years 4 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König