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» On Multiple Linear Approximations
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ECAI
2008
Springer
15 years 5 months ago
Reinforcement Learning with the Use of Costly Features
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
Robby Goetschalckx, Scott Sanner, Kurt Driessens
UAI
2008
15 years 5 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
115
Voted
UAI
2001
15 years 5 months ago
A Clustering Approach to Solving Large Stochastic Matching Problems
In this work we focus on efficient heuristics for solving a class of stochastic planning problems that arise in a variety of business, investment, and industrial applications. The...
Milos Hauskrecht, Eli Upfal
WSCG
2004
95views more  WSCG 2004»
15 years 5 months ago
Wave Height Forecasting Using Cascade Correlation Neural Network
Forecasting of wave height is necessary in a large number of ocean coastal activities. Recently, neural networks are used for prediction and approximation of wave heights in sea a...
Hamidreza Rashidy Kanan, Karim Faez
GLOBECOM
2008
IEEE
15 years 4 months ago
Power Efficient Throughput Maximization in Multi-Hop Wireless Networks
Abstract-- We study the problem of total throughput maximization in arbitrary multi-hop wireless networks, with constraints on the total power usage (denoted by PETM), when nodes h...
Deepti Chafekar, V. S. Anil Kumar, Madhav V. Marat...