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NECO
2007
115views more  NECO 2007»
13 years 7 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...
ATAL
2008
Springer
13 years 10 months ago
Optimal-in-expectation redistribution mechanisms
Many important problems in multiagent systems involve the allocation of multiple resources among the agents. If agents are self-interested, they will lie about their valuations fo...
Mingyu Guo, Vincent Conitzer
ICFP
2003
ACM
14 years 8 months ago
An effective theory of type refinements
We develop an explicit two level system that allows programmers to reason about the behavior of effectful programs. The first level is an ordinary ML-style type system, which conf...
Yitzhak Mandelbaum, David Walker, Robert Harper
ICASSP
2011
IEEE
12 years 11 months ago
Estimation and dynamic updating of time-varying signals with sparse variations
This paper presents an algorithm for an 1-regularized Kalman filter. Given observations of a discrete-time linear dynamical system with sparse errors in the state evolution, we e...
Muhammad Salman Asif, Adam Charles, Justin K. Romb...
LCTRTS
2001
Springer
14 years 12 days ago
A Dynamic Programming Approach to Optimal Integrated Code Generation
Phase-decoupled methods for code generation are the state of the art in compilers for standard processors but generally produce code of poor quality for irregular target architect...
Christoph W. Keßler, Andrzej Bednarski