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121
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ICML
2003
IEEE
16 years 1 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims
111
Voted
ICML
2001
IEEE
16 years 1 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICML
2000
IEEE
16 years 1 months ago
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
Daniel Nikovski, Illah R. Nourbakhsh
ASIACRYPT
2009
Springer
15 years 7 months ago
Attacking Power Generators Using Unravelled Linearization: When Do We Output Too Much?
We look at iterated power generators si = se i−1 mod N for a random seed s0 ∈ ZN that in each iteration output a certain amount of bits. We show that heuristically an output of...
Mathias Herrmann, Alexander May
95
Voted
GECCO
2009
Springer
15 years 7 months ago
An evolutionary approach to planning IEEE 802.16 networks
Efficient and effective deployment of IEEE 802.16 networks to service an area of users with certain traffic demands is an important network planning problem. We resort to an evol...
Ting Hu, Yuanzhu Peter Chen, Wolfgang Banzhaf, Rob...