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JMLR
2012
13 years 9 months ago
Randomized Optimum Models for Structured Prediction
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
NIPS
1996
15 years 8 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
194
Voted
CGF
1998
86views more  CGF 1998»
15 years 6 months ago
Subdivision Schemes for Thin Plate Splines
Thin plate splines are a well known entity of geometric design. They are defined as the minimizer of a variational problem whose differential operators approximate a simple notio...
Henrik Weimer, Joe D. Warren
ICML
2008
IEEE
16 years 7 months ago
Reinforcement learning in the presence of rare events
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
Jordan Frank, Shie Mannor, Doina Precup
SODA
2010
ACM
208views Algorithms» more  SODA 2010»
16 years 4 months ago
Correlation Robust Stochastic Optimization
We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation be...
Shipra Agrawal, Yichuan Ding, Amin Saberi, Yinyu Y...