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NECO
2007
115views more  NECO 2007»
13 years 8 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
14 years 3 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
14 years 1 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»
13 years 8 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
14 years 24 days 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