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ICML
2010
IEEE
15 years 3 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
IROS
2009
IEEE
154views Robotics» more  IROS 2009»
15 years 11 months ago
Consideration on robotic giant-swing motion generated by reinforcement learning
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
Masayuki Hara, Naoto Kawabe, Naoki Sakai, Jian Hua...
PAMI
2008
179views more  PAMI 2008»
15 years 4 months ago
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
A dynamic texture is a spatio-temporal generative model for video, which represents video sequences as observations from a linear dynamical system. This work introduces the mixtur...
Antoni B. Chan, Nuno Vasconcelos
MLDM
2009
Springer
15 years 11 months ago
Dynamic Score Combination: A Supervised and Unsupervised Score Combination Method
In two-class score-based problems the combination of scores from an ensemble of experts is generally used to obtain distributions for positive and negative patterns that exhibit a ...
Roberto Tronci, Giorgio Giacinto, Fabio Roli
DIGRA
2005
Springer
15 years 10 months ago
Realistic Agent Movement in Dynamic Game Environments
One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core...
Ross Graham, Hugh McCabe, Stephen Sheridan