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NIPS
2008
15 years 7 months ago
An Online Algorithm for Maximizing Submodular Functions
We present an algorithm for solving a broad class of online resource allocation . Our online algorithm can be applied in environments where abstract jobs arrive one at a time, and...
Matthew J. Streeter, Daniel Golovin
ACE
2003
115views Education» more  ACE 2003»
15 years 7 months ago
Impacting the Learning Experience
The availability of technology has seen the development of online asynchronous discussion boards for use in teaching and learning. This paper explores the use of this medium withi...
Sandra Barker
ICML
2005
IEEE
16 years 7 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
16 years 23 days ago
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
NIPS
1998
15 years 7 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller