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» Fast algorithms for time series mining
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73
Voted
ADMA
2005
Springer
149views Data Mining» more  ADMA 2005»
15 years 3 months ago
A New Support Vector Machine for Data Mining
Abstract. This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algor...
Haoran Zhang, Xiaodong Wang, Changjiang Zhang, Xiu...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
14 years 11 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
15 years 10 months ago
TANGENT: a novel, 'Surprise me', recommendation algorithm
Most of recommender systems try to find items that are most relevant to the older choices of a given user. Here we focus on the "surprise me" query: A user may be bored ...
Kensuke Onuma, Hanghang Tong, Christos Faloutsos
66
Voted
KDD
2004
ACM
211views Data Mining» more  KDD 2004»
15 years 10 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
82
Voted
IFIP
1999
Springer
15 years 2 months ago
Frontier: A Fast Placement System for FPGAs
In this paper we describe Frontier, an FPGA placement system that uses design macro-blocks in conjuction with a series of placement algorithms to achieve highly-routable and high-...
Russell Tessier