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MCS
2009
Springer
14 years 3 months ago
Selective Ensemble under Regularization Framework
An ensemble is generated by training multiple component learners for a same task and then combining them for predictions. It is known that when lots of trained learners are availab...
Nan Li, Zhi-Hua Zhou
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
14 years 3 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
ICTAI
2007
IEEE
14 years 3 months ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas
FPGA
2010
ACM
182views FPGA» more  FPGA 2010»
13 years 6 months ago
A comprehensive approach to modeling, characterizing and optimizing for metastability in FPGAs
Metastability is a phenomenon that can cause system failures in digital circuits. It may occur whenever signals are being transmitted across asynchronous or unrelated clock domain...
Doris Chen, Deshanand Singh, Jeffrey Chromczak, Da...
ACL
2012
11 years 11 months ago
Discriminative Pronunciation Modeling: A Large-Margin, Feature-Rich Approach
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...
Hao Tang, Joseph Keshet, Karen Livescu