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CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 6 months ago
Near-Optimal Bayesian Active Learning with Noisy Observations
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Daniel Golovin, Andreas Krause, Debajyoti Ray
DAGSTUHL
2003
15 years 7 months ago
The Need to Adapt and Its Implications for Embodiment
We present the hypothesis that an important factor for the choice of a particular embodiment for a natural or artificial agent is the effect of the embodiment on the agent’s ab...
Lukas Lichtensteiger
COLT
2004
Springer
15 years 11 months ago
A Function Representation for Learning in Banach Spaces
Charles A. Micchelli, Massimiliano Pontil
ICML
2004
IEEE
16 years 6 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
COLT
1994
Springer
15 years 10 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby