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ICML
2007
IEEE
14 years 10 months ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu
CF
2006
ACM
14 years 3 months ago
Memory efficient parallel matrix multiplication operation for irregular problems
Regular distributions for storing dense matrices on parallel systems are not always used in practice. In many scientific applicati RUMMA) [1] to handle irregularly distributed mat...
Manojkumar Krishnan, Jarek Nieplocha
ICML
2006
IEEE
14 years 10 months ago
Totally corrective boosting algorithms that maximize the margin
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
Gunnar Rätsch, Jun Liao, Manfred K. Warmuth
NSPW
2003
ACM
14 years 3 months ago
Public key distribution through "cryptoIDs"
In this paper, we argue that person-to-person key distribution is best accomplished with a key-centric approach, instead of PKI: users should distribute public key fingerprints in...
Trevor Perrin
ISCAPDCS
2001
13 years 11 months ago
AMOS-SDDS: A Scalable Distributed Data Manager for Windows Multicomputers
Known parallel DBMS offer at present only static partitioning schemes. Adding a storage node is then a cumbersome operation that typically requires the manual data redistribution....
Yakham Ndiaye, Aly Wane Diene, Witold Litwin, Tore...