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» Bounds for Linear Multi-Task Learning
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JMLR
2006
134views more  JMLR 2006»
13 years 7 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz
JMLR
2010
147views more  JMLR 2010»
13 years 2 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
JMLR
2008
137views more  JMLR 2008»
13 years 7 months ago
Online Learning of Complex Prediction Problems Using Simultaneous Projections
We describe and analyze an algorithmic framework for online classification where each online trial consists of multiple prediction tasks that are tied together. We tackle the prob...
Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
13 years 5 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
CDC
2008
IEEE
149views Control Systems» more  CDC 2008»
13 years 9 months ago
Distributed computation under bit constraints
Abstract-- A network of nodes communicate via noisy channels. Each node has some real-valued initial measurement or message. The goal of each of the nodes is to acquire an estimate...
Ola Ayaso, Devavrat Shah, Munther A. Dahleh