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IJCNN
2006
IEEE
13 years 10 months ago
Preparing More Effective Liquid State Machines Using Hebbian Learning
—In Liquid State Machines, separation is a critical attribute of the liquid—which is traditionally not trained. The effects of using Hebbian learning in the liquid to improve s...
David Norton, Dan Ventura
IWANN
2005
Springer
13 years 10 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
ICAC
2006
IEEE
13 years 10 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...
NIPS
1997
13 years 6 months ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell
CHI
2010
ACM
13 years 11 months ago
Interactive optimization for steering machine classification
Interest has been growing within HCI on the use of machine learning and reasoning in applications to classify such hidden states as user intentions, based on observations. HCI res...
Ashish Kapoor, Bongshin Lee, Desney S. Tan, Eric H...