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» Practical Preference Relations for Large Data Sets
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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 5 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 5 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
IEEEPACT
2002
IEEE
15 years 10 months ago
Using the Compiler to Improve Cache Replacement Decisions
Memory performance is increasingly determining microprocessor performance and technology trends are exacerbating this problem. Most architectures use set-associative caches with L...
Zhenlin Wang, Kathryn S. McKinley, Arnold L. Rosen...
POPL
2010
ACM
16 years 2 months ago
Nominal System T
This paper introduces a new recursion principle for inductive data modulo -equivalence of bound names. It makes use of Oderskystyle local names when recursing over bound names. It...
Andrew M. Pitts
SIGCOMM
1999
ACM
15 years 9 months ago
On Estimating End-to-End Network Path Properties
The more information about current network conditions available to a transport protocol, the more efficiently it can use the network to transfer its data. In networks such as the...
Mark Allman, Vern Paxson