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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
16 years 1 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
JMLR
2006
116views more  JMLR 2006»
15 years 7 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
ICASSP
2011
IEEE
14 years 10 months ago
Integrating binaural cues and blind source separation method for separating reverberant speech mixtures
This paper presents a new method for reverberant speech separation, based on the combination of binaural cues and blind source separation (BSS) for the automatic classification o...
Atiyeh Alinaghi, Wenwu Wang, Philip J. B. Jackson
STOC
2009
ACM
102views Algorithms» more  STOC 2009»
16 years 7 months ago
Multiple intents re-ranking
One of the most fundamental problems in web search is how to re-rank result web pages based on user logs. Most traditional models for re-ranking assume each query has a single int...
Yossi Azar, Iftah Gamzu, Xiaoxin Yin
185
Voted
ICML
2010
IEEE
15 years 8 months ago
Multi-Class Pegasos on a Budget
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Zhuang Wang, Koby Crammer, Slobodan Vucetic