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» Odefy -- From discrete to continuous models
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NIPS
2007
15 years 1 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 3 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 4 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
16 years 1 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 11 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