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» Online Learning of Non-stationary Sequences
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ICML
2003
IEEE
14 years 8 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
ICCV
2011
IEEE
12 years 7 months ago
Learning Universal Multi-view Age Estimator by Video Contexts
Most existing techniques for analyzing face images assume that the faces are at near-frontal poses. Generalizing to non-frontal faces is often difficult, due to a dearth of groun...
Zheng Song, Bingbing Ni, Dong Guo, Terence Sim, Sh...
ICANN
2005
Springer
14 years 27 days ago
A Neural Network Model for Inter-problem Adaptive Online Time Allocation
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Matteo Gagliolo, Jürgen Schmidhuber
ICML
2006
IEEE
14 years 8 months ago
Online decoding of Markov models under latency constraints
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
Mukund Narasimhan, Paul A. Viola, Michael Shilman
NIPS
1998
13 years 8 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller