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NECO
2007
115views more  NECO 2007»
14 years 9 months ago
Training Recurrent Networks by Evolino
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Jürgen Schmidhuber, Daan Wierstra, Matteo Gag...
SC
2009
ACM
15 years 4 months ago
Scalable computing with parallel tasks
Recent and future parallel clusters and supercomputers use SMPs and multi-core processors as basic nodes, providing a huge amount of parallel resources. These systems often have h...
Jörg Dümmler, Thomas Rauber, Gudula R&uu...
PPDP
1999
Springer
15 years 2 months ago
C--: A Portable Assembly Language that Supports Garbage Collection
For a compiler writer, generating good machine code for a variety of platforms is hard work. One might try to reuse a retargetable code generator, but code generators are complex a...
Simon L. Peyton Jones, Norman Ramsey, Fermin Reig
JMLR
2006
156views more  JMLR 2006»
14 years 9 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICML
1989
IEEE
15 years 1 months ago
Uncertainty Based Selection of Learning Experiences
The training experiences needed by a learning system may be selected by either an external agent or the system itself. We show that knowledge of the current state of the learner&#...
Paul D. Scott, Shaul Markovitch