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NIPS
2008
15 years 8 months ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton
ICML
2009
IEEE
16 years 7 months ago
Discovering options from example trajectories
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...
ICML
2006
IEEE
16 years 7 months ago
Estimating relatedness via data compression
We show that it is possible to use data compression on independently obtained hypotheses from various tasks to algorithmically provide guarantees that the tasks are sufficiently r...
Brendan Juba
ICML
2005
IEEE
16 years 7 months ago
A theoretical analysis of Model-Based Interval Estimation
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...
Alexander L. Strehl, Michael L. Littman
ICML
2005
IEEE
16 years 7 months ago
Large margin non-linear embedding
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
Alexander Zien, Joaquin Quiñonero Candela