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» Algorithm Selection using Reinforcement Learning
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SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 8 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
JMLR
2010
187views more  JMLR 2010»
13 years 5 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 11 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
CORR
2008
Springer
173views Education» more  CORR 2008»
13 years 11 months ago
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
Fangwen Fu, Mihaela van der Schaar
JMLR
2010
206views more  JMLR 2010»
13 years 5 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...