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COLT
2008
Springer
13 years 10 months ago
Linear Algorithms for Online Multitask Classification
We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
Giovanni Cavallanti, Nicolò Cesa-Bianchi, C...
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 5 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
JMLR
2010
211views more  JMLR 2010»
13 years 3 months ago
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Bo Dai, Baogang Hu
ICML
2009
IEEE
14 years 9 months ago
Efficient learning algorithms for changing environments
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
Elad Hazan, C. Seshadhri
ICML
2009
IEEE
14 years 9 months ago
Learning instance specific distances using metric propagation
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou