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» Stochastic methods for l1 regularized loss minimization
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JMLR
2008
95views more  JMLR 2008»
15 years 11 days ago
Learning Similarity with Operator-valued Large-margin Classifiers
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Andreas Maurer
ICML
2008
IEEE
16 years 1 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
14 years 10 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
109
Voted
IWDC
2005
Springer
112views Communications» more  IWDC 2005»
15 years 5 months ago
Stochastic Rate-Control for Real-Time Video Transmission over Heterogeneous Network
In this paper, we propose a stochastic rate control method to provide seamless video streaming for vertical handoff between WLAN and 3G cellular network. In the proposed method, w...
Jae-Woong Yun, Hye-Soo Kim, Jae-Won Kim, Youn-Seon...
115
Voted
DAGM
2005
Springer
15 years 6 months ago
Regularization on Discrete Spaces
Abstract. We consider the classification problem on a finite set of objects. Some of them are labeled, and the task is to predict the labels of the remaining unlabeled ones. Such...
Dengyong Zhou, Bernhard Schölkopf