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NIPS
2007
14 years 11 months ago
A general agnostic active learning algorithm
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni
ICML
2003
IEEE
15 years 11 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
75
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AAAI
2008
15 years 16 days ago
Fast Spectral Learning using Lanczos Eigenspace Projections
The core computational step in spectral learning
Sridhar Mahadevan
ILP
2007
Springer
15 years 4 months ago
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...
ECAI
2004
Springer
15 years 3 months ago
Improving Asynchronous Backtracking for Dealing with Complex Local Problems
Distributed constraint satisfaction, in its most general acceptation, involves a collection of agents solving local constraint satisfaction subproblems, and a communication protoco...
Arnold Maestre, Christian Bessière