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» Generalization Improvement in Multi-Objective Learning
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BMCBI
2008
153views more  BMCBI 2008»
13 years 5 months ago
Improved general regression network for protein domain boundary prediction
Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary ...
Paul D. Yoo, Abdur R. Sikder, Bing Bing Zhou, Albe...
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 4 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
ATAL
2009
Springer
14 years 9 days ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone
NIPS
2007
13 years 7 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
IJCAI
2001
13 years 7 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz