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DIS
2009
Springer
16 years 1 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
ICML
2007
IEEE
16 years 7 months ago
Approximate maximum margin algorithms with rules controlled by the number of mistakes
We present a family of incremental Perceptron-like algorithms (PLAs) with margin in which both the "effective" learning rate, defined as the ratio of the learning rate t...
Petroula Tsampouka, John Shawe-Taylor
JMLR
2010
147views more  JMLR 2010»
15 years 1 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
OSDI
2008
ACM
16 years 7 months ago
An Internet Protocol Address Clustering Algorithm
We pose partitioning a b-bit Internet Protocol (IP) address space as a supervised learning task. Given (IP, property) labeled training data, we develop an IP-specific clustering a...
Robert Beverly, Karen R. Sollins