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ICML
2007
IEEE
16 years 4 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
ICML
2003
IEEE
16 years 4 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
113
Voted
ICML
2003
IEEE
16 years 4 months ago
Online Ranking/Collaborative Filtering Using the Perceptron Algorithm
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Edward F. Harrington
ICIP
2008
IEEE
16 years 5 months ago
Emotional valence categorization using holistic image features
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
123
Voted
ICML
2007
IEEE
16 years 4 months ago
On the relation between multi-instance learning and semi-supervised learning
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
Zhi-Hua Zhou, Jun-Ming Xu