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» Self-Randomized Exponentiation Algorithms
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105
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ICML
2007
IEEE
16 years 3 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
89
Voted
ICML
2006
IEEE
16 years 3 months ago
Data association for topic intensity tracking
We present a unified model of what was traditionally viewed as two separate tasks: data association and intensity tracking of multiple topics over time. In the data association pa...
Andreas Krause, Jure Leskovec, Carlos Guestrin
134
Voted
ICML
2005
IEEE
16 years 3 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
116
Voted
WWW
2009
ACM
16 years 3 months ago
Spatio-temporal models for estimating click-through rate
We propose novel spatio-temporal models to estimate clickthrough rates in the context of content recommendation. We track article CTR at a fixed location over time through a dynam...
Deepak Agarwal, Bee-Chung Chen, Pradheep Elango
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
16 years 3 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...