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JMLR
2010
103views more  JMLR 2010»
13 years 3 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ECCV
2010
Springer
14 years 16 days ago
Learning Artistic Lighting Template from Portrait Photographs
This paper presents a method for learning artistic portrait lighting template from a dataset of artistic and daily portrait photographs. The learned template can be used for (1) cl...
EMNLP
2011
12 years 8 months ago
Random Walk Inference and Learning in A Large Scale Knowledge Base
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Ni Lao, Tom M. Mitchell, William W. Cohen
ICPR
2006
IEEE
14 years 10 months ago
Robust Recursive Learning for Foreground Region Detection in Videos with Quasi-Stationary Backgrounds
Detecting regions of interest in video sequences is the most important task in many high level video processing applications. In this paper a robust technique based on recursive l...
Alireza Tavakkoli, George Bebis, Mircea Nicolescu
AAAI
2011
12 years 9 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos