| 2008 |
|---|
| 12 | EE | Daan Wierstra,
Tom Schaul,
Jan Peters,
Jürgen Schmidhuber:
Episodic Reinforcement Learning by Logistic Reward-Weighted Regression.
ICANN (1) 2008: 407-416 |
| 11 | EE | Daan Wierstra,
Tom Schaul,
Jan Peters,
Jürgen Schmidhuber:
Natural Evolution Strategies.
IEEE Congress on Evolutionary Computation 2008: 3381-3387 |
| 10 | EE | Daan Wierstra,
Tom Schaul,
Jan Peters,
Jürgen Schmidhuber:
Fitness Expectation Maximization.
PPSN 2008: 337-346 |
| 2007 |
|---|
| 9 | EE | Daan Wierstra,
Jürgen Schmidhuber:
Policy Gradient Critics.
ECML 2007: 466-477 |
| 8 | EE | Daan Wierstra,
Alexander Förster,
Jan Peters,
Jürgen Schmidhuber:
Solving Deep Memory POMDPs with Recurrent Policy Gradients.
ICANN (1) 2007: 697-706 |
| 7 | EE | Jürgen Schmidhuber,
Daan Wierstra,
Matteo Gagliolo,
Faustino J. Gomez:
Training Recurrent Networks by Evolino.
Neural Computation 19(3): 757-779 (2007) |
| 2006 |
|---|
| 6 | EE | Jürgen Schmidhuber,
Matteo Gagliolo,
Daan Wierstra,
Faustino J. Gomez:
Evolino for recurrent support vector machines.
ESANN 2006: 593-598 |
| 5 | EE | Hermann Georg Mayer,
Faustino J. Gomez,
Daan Wierstra,
Istvan Nagy,
Alois Knoll,
Jürgen Schmidhuber:
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks.
IROS 2006: 543-548 |
| 2005 |
|---|
| 4 | EE | Daan Wierstra,
Faustino J. Gomez,
Jürgen Schmidhuber:
Modeling systems with internal state using evolino.
GECCO 2005: 1795-1802 |
| 3 | EE | Jürgen Schmidhuber,
Daan Wierstra,
Faustino J. Gomez:
Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning.
IJCAI 2005: 853-858 |
| 2 | EE | Jürgen Schmidhuber,
Matteo Gagliolo,
Daan Wierstra,
Faustino J. Gomez:
Evolino for recurrent support vector machines
CoRR abs/cs/0512062: (2005) |
| 2004 |
|---|
| 1 | EE | Daan Wierstra,
Marco Wiering:
Utile distinction hidden Markov models.
ICML 2004 |
