1916 search results - page 189 / 384 » Reconfiguring a state machine |
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
Probabilistic modelling of text data in the bagof-words representation has been dominated by directed graphical models such as pLSI, LDA, NMF, and discrete PCA. Recently, state of...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...