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» Approximate Learning of Dynamic Models
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PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 9 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
118
Voted
DATE
2008
IEEE
122views Hardware» more  DATE 2008»
15 years 9 months ago
Simulation-Directed Invariant Mining for Software Verification
With the advance of SAT solvers, transforming a software program to a propositional formula has generated much interest for bounded model checking of software in recent years. How...
Xueqi Cheng, Michael S. Hsiao
IROS
2008
IEEE
161views Robotics» more  IROS 2008»
15 years 9 months ago
Segmenting acoustic signal with articulatory movement using Recurrent Neural Network for phoneme acquisition
— This paper proposes a computational model for phoneme acquisition by infants. Human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic ...
Hisashi Kanda, Tetsuya Ogata, Kazunori Komatani, H...
133
Voted
TVCG
2012
191views Hardware» more  TVCG 2012»
13 years 5 months ago
Live Speech Driven Head-and-Eye Motion Generators
—This paper describes a fully automated framework to generate realistic head motion, eye gaze, and eyelid motion simultaneously based on live (or recorded) speech input. Its cent...
Binh Huy Le, Xiaohan Ma, Zhigang Deng
135
Voted
HICSS
2005
IEEE
95views Biometrics» more  HICSS 2005»
15 years 8 months ago
Understanding the Effect of Risk Aversion on Risk
As we progress, society must intelligently address the following question: How much risk is acceptable? How we answer this question could have important consequences for the futur...
U. S. Bhatt, David E. Newman, Benjamin A. Carreras...