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» A random walk approach to sampling hidden databases
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ICDAR
2003
IEEE
15 years 2 months ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...
TIT
1998
79views more  TIT 1998»
14 years 9 months ago
Capacity of Two-Layer Feedforward Neural Networks with Binary Weights
— The lower and upper bounds for the information capacity of two-layer feedforward neural networks with binary interconnections, integer thresholds for the hidden units, and zero...
Chuanyi Ji, Demetri Psaltis
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
15 years 10 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
PODS
2009
ACM
112views Database» more  PODS 2009»
15 years 10 months ago
Optimal sampling from sliding windows
APPEARED IN ACM PODS-2009. A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are disc...
Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniol...
VLDB
2000
ACM
155views Database» more  VLDB 2000»
15 years 1 months ago
ICICLES: Self-Tuning Samples for Approximate Query Answering
Approximate query answering systems provide very fast alternatives to OLAP systems when applications are tolerant to small errors in query answers. Current sampling-based approach...
Venkatesh Ganti, Mong-Li Lee, Raghu Ramakrishnan