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CVPR
2009
IEEE
14 years 2 months ago
Understanding videos, constructing plots learning a visually grounded storyline model from annotated videos
Analyzing videos of human activities involves not only recognizing actions (typically based on their appearances), but also determining the story/plot of the video. The storyline ...
Abhinav Gupta, Praveen Srinivasan, Jianbo Shi, Lar...
AMKM
2003
Springer
14 years 27 days ago
Discovering, Visualizing, and Sharing Knowledge through Personalized Learning Knowledge Maps
This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
JMLR
2010
139views more  JMLR 2010»
13 years 2 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
ICML
2004
IEEE
14 years 8 months ago
Learning to fly by combining reinforcement learning with behavioural cloning
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
Eduardo F. Morales, Claude Sammut
ICRA
2010
IEEE
147views Robotics» more  ICRA 2010»
13 years 6 months ago
Learning physically-instantiated game play through visual observation
Abstract— We present an integrated vision and robotic system that plays, and learns to play, simple physically-instantiated board games that are variants of TIC TAC TOE and HEXAP...
Andrei Barbu, Siddharth Narayanaswamy, Jeffrey Mar...