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109
Voted
CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 2 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
99
Voted
DAGSTUHL
2003
15 years 3 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
71
Voted
COLT
2004
Springer
15 years 7 months ago
A Function Representation for Learning in Banach Spaces
Charles A. Micchelli, Massimiliano Pontil
ICML
2004
IEEE
16 years 2 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 6 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