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ICML
2008
IEEE
16 years 20 days ago
Sequence kernels for predicting protein essentiality
The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing therapeutic drugs. This work d...
Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 8 days ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ICCV
2009
IEEE
16 years 4 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
ICML
1998
IEEE
16 years 20 days ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...
ICIP
2007
IEEE
16 years 1 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen