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» Odefy -- From discrete to continuous models
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NIPS
2007
14 years 11 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
REX
1991
15 years 1 months ago
From Timed to Hybrid Systems
We propose a framework for the formal speci cation and veri cation of timed and hybrid systems. For timed systems we propose a speci cation language that refers to time only throug...
Oded Maler, Zohar Manna, Amir Pnueli
FM
1999
Springer
161views Formal Methods» more  FM 1999»
15 years 1 months ago
Combining Theorem Proving and Continuous Models in Synchronous Design
Support for system speci cation in terms of modelling and simulation environments has become a common practice in safety-critical applications. Also, a current trend is the automat...
Simin Nadjm-Tehrani, Ove Åkerlund
CVPR
1999
IEEE
15 years 11 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
JMLR
2006
124views more  JMLR 2006»
14 years 9 months ago
Policy Gradient in Continuous Time
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Rémi Munos