2009 | ||
---|---|---|
114 | EE | Daniil Ryabko, Jürgen Schmidhuber: Using data compressors to construct order tests for homogeneity and component independence. Appl. Math. Lett. 22(7): 1029-1032 (2009) |
2008 | ||
113 | EE | Matteo Gagliolo, Jürgen Schmidhuber: Towards Distributed Algorithm Portfolios. DCAI 2008: 634-643 |
112 | EE | Thomas Rückstieß, Martin Felder, Jürgen Schmidhuber: State-Dependent Exploration for Policy Gradient Methods. ECML/PKDD (2) 2008: 234-249 |
111 | EE | Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber: Policy Gradients with Parameter-Based Exploration for Control. ICANN (1) 2008: 387-396 |
110 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Episodic Reinforcement Learning by Logistic Reward-Weighted Regression. ICANN (1) 2008: 407-416 |
109 | EE | Julian Togelius, Faustino J. Gomez, Jürgen Schmidhuber: Learning what to ignore: Memetic climbing in topology and weight space. IEEE Congress on Evolutionary Computation 2008: 3274-3281 |
108 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Natural Evolution Strategies. IEEE Congress on Evolutionary Computation 2008: 3381-3387 |
107 | EE | Jürgen Schmidhuber: Driven by Compression Progress. KES (1) 2008: 11 |
106 | EE | Alex Graves, Jürgen Schmidhuber: Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks. NIPS 2008: 545-552 |
105 | EE | Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber: Fitness Expectation Maximization. PPSN 2008: 337-346 |
104 | EE | Julian Togelius, Tom Schaul, Jürgen Schmidhuber, Faustino J. Gomez: Countering Poisonous Inputs with Memetic Neuroevolution. PPSN 2008: 610-619 |
103 | EE | Santiago Fernández, Alex Graves, Jürgen Schmidhuber: Phoneme recognition in TIMIT with BLSTM-CTC CoRR abs/0804.3269: (2008) |
102 | EE | Matteo Gagliolo, Jürgen Schmidhuber: Algorithm Selection as a Bandit Problem with Unbounded Losses CoRR abs/0807.1494: (2008) |
101 | EE | Jürgen Schmidhuber: Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes CoRR abs/0812.4360: (2008) |
2007 | ||
100 | EE | Jürgen Schmidhuber: Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity. ALT 2007: 32-33 |
99 | EE | Jürgen Schmidhuber: Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity. Discovery Science 2007: 26-38 |
98 | EE | Daan Wierstra, Jürgen Schmidhuber: Policy Gradient Critics. ECML 2007: 466-477 |
97 | EE | Alexander Förster, Alex Graves, Jürgen Schmidhuber: RNN-based Learning of Compact Maps for Efficient Robot Localization. ESANN 2007: 537-542 |
96 | EE | Alex Graves, Santiago Fernández, Jürgen Schmidhuber: Multi-dimensional Recurrent Neural Networks. ICANN (1) 2007: 549-558 |
95 | EE | Daan Wierstra, Alexander Förster, Jan Peters, Jürgen Schmidhuber: Solving Deep Memory POMDPs with Recurrent Policy Gradients. ICANN (1) 2007: 697-706 |
94 | EE | Santiago Fernández, Alex Graves, Jürgen Schmidhuber: An Application of Recurrent Neural Networks to Discriminative Keyword Spotting. ICANN (2) 2007: 220-229 |
93 | EE | Santiago Fernández, Alex Graves, Jürgen Schmidhuber: Sequence Labelling in Structured Domains with Hierarchical Recurrent Neural Networks. IJCAI 2007: 774-779 |
92 | EE | Matteo Gagliolo, Jürgen Schmidhuber: Learning Restart Strategies. IJCAI 2007: 792-797 |
91 | EE | Alex Graves, Santiago Fernández, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber: Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks. NIPS 2007 |
90 | EE | Jürgen Schmidhuber: New Millennium AI and the Convergence of History. Challenges for Computational Intelligence 2007: 15-35 |
89 | EE | Alex Graves, Santiago Fernández, Jürgen Schmidhuber: Multi-Dimensional Recurrent Neural Networks CoRR abs/0705.2011: (2007) |
88 | EE | Jürgen Schmidhuber: 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years CoRR abs/0708.4311: (2007) |
87 | EE | Daniil Ryabko, Jürgen Schmidhuber: Using Data Compressors to Construct Rank Tests CoRR abs/0709.0670: (2007) |
86 | EE | Jürgen Schmidhuber: Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity CoRR abs/0709.0674: (2007) |
85 | EE | Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic Complexity Bounds on Future Prediction Errors CoRR abs/cs/0701120: (2007) |
84 | EE | Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic complexity bounds on future prediction errors. Inf. Comput. 205(2): 242-261 (2007) |
83 | EE | Jürgen Schmidhuber, Daan Wierstra, Matteo Gagliolo, Faustino J. Gomez: Training Recurrent Networks by Evolino. Neural Computation 19(3): 757-779 (2007) |
2006 | ||
82 | EE | Jürgen Schmidhuber: 2006: Celebrating 75 Years of AI - History and Outlook: The Next 25 Years. 50 Years of Artificial Intelligence 2006: 29-41 |
81 | EE | Matteo Gagliolo, Jürgen Schmidhuber: Impact of Censored Sampling on the Performance of Restart Strategies. CP 2006: 167-181 |
80 | EE | Alexey V. Chernov, Jürgen Schmidhuber: Prefix-Like Complexities and Computability in the Limit. CiE 2006: 85-93 |
79 | EE | Faustino J. Gomez, Jürgen Schmidhuber, Risto Miikkulainen: Efficient Non-linear Control Through Neuroevolution. ECML 2006: 654-662 |
78 | EE | Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez: Evolino for recurrent support vector machines. ESANN 2006: 593-598 |
77 | Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber: Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. IAS 2006: 272-281 | |
76 | EE | Alex Graves, Santiago Fernández, Faustino J. Gomez, Jürgen Schmidhuber: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. ICML 2006: 369-376 |
75 | Bram Bakker, Viktor Zhumatiy, Gabriel Gruener, Jürgen Schmidhuber: Quasi-online Reinforcement Learning for Robots. ICRA 2006: 2997-3002 | |
74 | 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 |
73 | EE | Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Complexity Monotone in Conditions and Future Prediction Errors. Kolmogorov Complexity and Applications 2006 |
72 | EE | Matteo Gagliolo, Jürgen Schmidhuber: Learning dynamic algorithm portfolios. Ann. Math. Artif. Intell. 47(3-4): 295-328 (2006) |
71 | EE | Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber: Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot CoRR abs/cs/0603023: (2006) |
70 | EE | Jürgen Schmidhuber: New Millennium AI and the Convergence of History CoRR abs/cs/0606081: (2006) |
69 | EE | Jürgen Schmidhuber: Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts. Connect. Sci. 18(2): 173-187 (2006) |
2005 | ||
68 | EE | Jürgen Schmidhuber: Gödel Machines: Towards a Technical Justification of Consciousness. Adaptive Agents and Multi-Agent Systems 2005: 1-23 |
67 | EE | Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber: Modeling systems with internal state using evolino. GECCO 2005: 1795-1802 |
66 | EE | Faustino J. Gomez, Jürgen Schmidhuber: Co-evolving recurrent neurons learn deep memory POMDPs. GECCO 2005: 491-498 |
65 | EE | Martijn van de Giessen, Jürgen Schmidhuber: Fast Color-Based Object Recognition Independent of Position and Orientation. ICANN (1) 2005: 469-474 |
64 | EE | Nicole Beringer, Alex Graves, Florian Schiel, Jürgen Schmidhuber: Classifying Unprompted Speech by Retraining LSTM Nets. ICANN (1) 2005: 575-581 |
63 | EE | Jürgen Schmidhuber: Completely Self-referential Optimal Reinforcement Learners. ICANN (2) 2005: 223-233 |
62 | EE | Faustino J. Gomez, Jürgen Schmidhuber: Evolving Modular Fast-Weight Networks for Control. ICANN (2) 2005: 383-389 |
61 | EE | Matteo Gagliolo, Jürgen Schmidhuber: A Neural Network Model for Inter-problem Adaptive Online Time Allocation. ICANN (2) 2005: 7-12 |
60 | EE | Alex Graves, Santiago Fernández, Jürgen Schmidhuber: Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition. ICANN (2) 2005: 799-804 |
59 | EE | Jürgen Schmidhuber, Daan Wierstra, Faustino J. Gomez: Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning. IJCAI 2005: 853-858 |
58 | EE | Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez: Evolino for recurrent support vector machines CoRR abs/cs/0512062: (2005) |
57 | EE | Alex Graves, Jürgen Schmidhuber: Framewise phoneme classification with bidirectional LSTM and other neural network architectures. Neural Networks 18(5-6): 602-610 (2005) |
2004 | ||
56 | EE | Alex Graves, Douglas Eck, Nicole Beringer, Jürgen Schmidhuber: Biologically Plausible Speech Recognition with LSTM Neural Nets. BioADIT 2004: 127-136 |
55 | EE | Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber: Adaptive Online Time Allocation to Search Algorithms. ECML 2004: 134-143 |
54 | Bram Bakker, Jürgen Schmidhuber: Hierarchical reinforcement learning with subpolicies specializing for learned subgoals. Neural Networks and Computational Intelligence 2004: 125-130 | |
53 | Alex Graves, Nicole Beringer, Jürgen Schmidhuber: A comparison between spiking and differentiable recurrent neural networks on spoken digit recognition. Neural Networks and Computational Intelligence 2004: 164-168 | |
52 | EE | Jürgen Schmidhuber: Optimal Ordered Problem Solver. Machine Learning 54(3): 211-254 (2004) |
2003 | ||
51 | EE | Jürgen Schmidhuber: The New AI: General & Sound & Relevant for Physics CoRR cs.AI/0302012: (2003) |
50 | EE | Jürgen Schmidhuber: Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements CoRR cs.LO/0309048: (2003) |
49 | EE | Juan Antonio Pérez-Ortiz, Felix A. Gers, Douglas Eck, Jürgen Schmidhuber: Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets. Neural Networks 16(2): 241-250 (2003) |
2002 | ||
48 | EE | Jürgen Schmidhuber: The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions. COLT 2002: 216-228 |
47 | Felix A. Gers, Juan Antonio Pérez-Ortiz, Douglas Eck, Jürgen Schmidhuber: DEKF-LSTM. ESANN 2002: 369-376 | |
46 | EE | Juan Antonio Pérez-Ortiz, Jürgen Schmidhuber, Felix A. Gers, Douglas Eck: Improving Long-Term Online Prediction with Decoupled Extended Kalman Filters. ICANN 2002: 1055-1069 |
45 | EE | Douglas Eck, Jürgen Schmidhuber: Learning the Long-Term Structure of the Blues. ICANN 2002: 284-289 |
44 | EE | Felix A. Gers, Juan Antonio Pérez-Ortiz, Douglas Eck, Jürgen Schmidhuber: Learning Context Sensitive Languages with LSTM Trained with Kalman Filters. ICANN 2002: 655-660 |
43 | EE | Jürgen Schmidhuber: Bias-Optimal Incremental Problem Solving. NIPS 2002: 1547-1546 |
42 | EE | Jürgen Schmidhuber: Optimal Ordered Problem Solver CoRR cs.AI/0207097: (2002) |
41 | EE | Jürgen Schmidhuber: Hierarchies of Generalized Kolmogorov Complexities and Nonenumerable Universal Measures Computable in the Limit. Int. J. Found. Comput. Sci. 13(4): 587-612 (2002) |
40 | EE | Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber: Learning Precise Timing with LSTM Recurrent Networks. Journal of Machine Learning Research 3: 115-143 (2002) |
39 | EE | Jürgen Schmidhuber, Felix A. Gers, Douglas Eck: Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM. Neural Computation 14(9): 2039-2041 (2002) |
2001 | ||
38 | EE | Michele Milano, Jürgen Schmidhuber, Petros Koumoutsakos: Active Learning with Adaptive Grids. ICANN 2001: 436-442 |
37 | EE | Felix A. Gers, Douglas Eck, Jürgen Schmidhuber: Applying LSTM to Time Series Predictable through Time-Window Approaches. ICANN 2001: 669-676 |
36 | EE | Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber: Unsupervised Learning in LSTM Recurrent Neural Networks. ICANN 2001: 684-691 |
35 | EE | Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds. ICANN 2001: 865-873 |
34 | EE | Jürgen Schmidhuber: Sequential Decision Making Based on Direct Search. Sequence Learning 2001: 213-240 |
33 | EE | Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds CoRR cs.AI/0105025: (2001) |
32 | EE | Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Gradient-based Reinforcement Planning in Policy-Search Methods CoRR cs.AI/0111060: (2001) |
2000 | ||
31 | EE | Felix A. Gers, Jürgen Schmidhuber: Recurrent Nets that Time and Count. IJCNN (3) 2000: 189-194 |
30 | EE | Felix A. Gers, Jürgen Schmidhuber: Neural Processing of Complex Continual Input Streams. IJCNN (4) 2000: 557-562 |
29 | EE | Jürgen Schmidhuber: Algorithmic Theories of Everything CoRR quant-ph/0011122: (2000) |
28 | Felix A. Gers, Jürgen Schmidhuber, Fred A. Cummins: Learning to Forget: Continual Prediction with LSTM. Neural Computation 12(10): 2451-2471 (2000) | |
1999 | ||
27 | EE | Sepp Hochreiter, Jürgen Schmidhuber: Nonlinear ICA through low-complexity autoencoders. ISCAS (5) 1999: 53-56 |
26 | Marco Wiering, Rafal Salustowicz, Jürgen Schmidhuber: Reinforcement Learning Soccer Teams with Incomplete World Models. Auton. Robots 7(1): 77-88 (1999) | |
25 | EE | Jürgen Schmidhuber: A Computer Scientist's View of Life, the Universe, and Everything CoRR quant-ph/9904050: (1999) |
24 | Sepp Hochreiter, Jürgen Schmidhuber: Feature Extraction Through LOCOCODE. Neural Computation 11(3): 679-714 (1999) | |
1998 | ||
23 | Marco Wiering, Jürgen Schmidhuber: Speeding up Q(lambda)-Learning. ECML 1998: 352-363 | |
22 | Rafal Salustowicz, Jürgen Schmidhuber: Evolving Structured Programs with Hierarchical Instructions and Skip Nodes. ICML 1998: 488-496 | |
21 | EE | Sepp Hochreiter, Jürgen Schmidhuber: Source Separation as a By-Product of Regularization. NIPS 1998: 459-465 |
20 | Marco Wiering, Jürgen Schmidhuber: Fast Online Q(lambda). Machine Learning 33(1): 105-115 (1998) | |
19 | Rafal Salustowicz, Marco Wiering, Jürgen Schmidhuber: Learning Team Strategies: Soccer Case Studies. Machine Learning 33(2-3): 263-282 (1998) | |
1997 | ||
18 | Rafal Salustowicz, Jürgen Schmidhuber: Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space. ECML 1997: 213-220 | |
17 | EE | Jürgen Schmidhuber: A Computer Scientist's View of Life, the Universe, and Everything. Foundations of Computer Science: Potential - Theory - Cognition 1997: 201-208 |
16 | Sepp Hochreiter, Jürgen Schmidhuber: Unsupervised Coding with LOCOCODE. ICANN 1997: 655-660 | |
15 | Rafal Salustowicz, Marco Wiering, Jürgen Schmidhuber: On Learning Soccer Strategies. ICANN 1997: 769-774 | |
14 | Rafal Salustowicz, Jürgen Schmidhuber: Probabilistic Incremental Program Evolution. Evolutionary Computation 5(2): 123-141 (1997) | |
13 | Jürgen Schmidhuber, Jieyu Zhao, Marco Wiering: Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement. Machine Learning 28(1): 105-130 (1997) | |
12 | EE | Sepp Hochreiter, Jürgen Schmidhuber: Flat Minima Neural Computation 9(1): 1-42 (1997) |
11 | EE | Sepp Hochreiter, Jürgen Schmidhuber: Long Short-Term Memory. Neural Computation 9(8): 1735-1780 (1997) |
10 | EE | Jürgen Schmidhuber: Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability. Neural Networks 10(5): 857-873 (1997) |
1996 | ||
9 | Jürgen Schmidhuber, Jieyu Zhao: Multi-Agent Learning with the Success-Story Algorithm. ECAI Workshop LDAIS / ICMAS Workshop LIOME 1996: 82-93 | |
8 | Marco Wiering, Jürgen Schmidhuber: Solving POMDPs with Levin Search and EIRA. ICML 1996: 534-542 | |
7 | EE | Sepp Hochreiter, Jürgen Schmidhuber: LSTM can Solve Hard Long Time Lag Problems. NIPS 1996: 473-479 |
1995 | ||
6 | Jürgen Schmidhuber: Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability. ICML 1995: 488-496 | |
1994 | ||
5 | EE | Jürgen Schmidhuber, Stefan Heil: Predictive Coding with Neural Nets: Application to Text Compression. NIPS 1994: 1047-1054 |
4 | EE | Sepp Hochreiter, Jürgen Schmidhuber: Simplifying Neural Nets by Discovering Flat Minima. NIPS 1994: 529-536 |
1991 | ||
3 | EE | Jürgen Schmidhuber: Learning Unambiguous Reduced Sequence Descriptions. NIPS 1991: 291-298 |
2 | EE | Jürgen Schmidhuber, Rudolf Huber: Learning to Generate Artificial Fovea Trajectories for Target Detection. Int. J. Neural Syst. 2(1-2): 125-134 (1991) |
1990 | ||
1 | EE | Jürgen Schmidhuber: Reinforcement Learning in Markovian and Non-Markovian Environments. NIPS 1990: 500-506 |