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ISITA
2010
13 years 7 months ago
Approximating discrete probability distributions with causal dependence trees
Abstract--Chow and Liu considered the problem of approximating discrete joint distributions with dependence tree distributions where the goodness of the approximations were measure...
Christopher J. Quinn, Todd P. Coleman, Negar Kiyav...
ICML
2004
IEEE
14 years 10 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
ICDCS
2008
IEEE
14 years 3 months ago
Enabling Accurate Node Control in Randomized Duty Cycling Networks
— In this paper, we propose a novel duty cycling algorithm for large-scale dense wireless sensor networks. The proposed algorithm is based on a social behavior of nodes in the se...
Kang-Won Lee, Vasileios Pappas, Asser N. Tantawi
IROS
2007
IEEE
123views Robotics» more  IROS 2007»
14 years 3 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura
FOCS
1998
IEEE
14 years 1 months ago
The Shortest Vector in a Lattice is Hard to Approximate to Within Some Constant
We show that approximating the shortest vector problem (in any p norm) to within any constant factor less than p 2 is hard for NP under reverse unfaithful random reductions with i...
Daniele Micciancio