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ICCV
2003
IEEE
16 years 5 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann
ICIP
2009
IEEE
16 years 4 months ago
Detection Of Forgery In Paintings Using Supervised Learning
This paper examines whether machine learning and image analysis tools can be used to assist art experts in the authentication of unknown or disputed paintings. Recent work on this...
ICML
2009
IEEE
16 years 3 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
ICML
2004
IEEE
16 years 3 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ICML
2004
IEEE
16 years 3 months ago
Learning random walk models for inducing word dependency distributions
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...