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» Evaluating algorithms that learn from data streams
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GRC
2008
IEEE
15 years 7 months ago
Neighborhood Smoothing Embedding for Noisy Manifold Learning
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Guisheng Chen, Junsong Yin, Deyi Li
ICML
2000
IEEE
16 years 7 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
CIDR
2011
290views Algorithms» more  CIDR 2011»
14 years 10 months ago
Towards a One Size Fits All Database Architecture
We propose a new type of database system coined OctopusDB. Our approach suggests a unified, one size fits all data processing architecture for OLTP, OLAP, streaming systems, and...
Jens Dittrich, Alekh Jindal
ICDM
2005
IEEE
133views Data Mining» more  ICDM 2005»
16 years 8 days ago
Summarization - Compressing Data into an Informative Representation
In this paper, we formulate the problem of summarization of a dataset of transactions with categorical attributes as an optimization problem involving two objective functions - co...
Varun Chandola, Vipin Kumar
NIPS
2003
15 years 8 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan