2006 | ||
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54 | EE | Birger Andersson, Maria Bergholtz, Bertrand Grégoire, Paul Johannesson, Michael Schmitt, Jelena Zdravkovic: From Business to Process Models - a Chaining Methodology. BUSITAL 2006 |
53 | EE | Michael Schmitt, Bertrand Grégoire, Stefan Leidner: Enhancing trust and buy-in from business: a platform for business -driven development of B2B transactions. CAiSE Forum 2006 |
52 | EE | Bertrand Grégoire, Michael Schmitt: Business Service Network Design: From Business Model to an Integrated Multi-Partner Business Transaction. CEC/EEE 2006: 84 |
51 | EE | Birger Andersson, Maria Bergholtz, Ananda Edirisuriya, Tharaka Ilayperuma, Paul Johannesson, Bertrand Grégoire, Michael Schmitt, Eric Dubois, Sven Abels, Axel Hahn, Jaap Gordijn, Hans Weigand, Benkt Wangler: Towards a Common Ontology for Business Models. EMOI-INTEROP 2006 |
50 | EE | Birger Andersson, Maria Bergholtz, Ananda Edirisuriya, Tharaka Ilayperuma, Paul Johannesson, Jaap Gordijn, Bertrand Grégoire, Michael Schmitt, Eric Dubois, Sven Abels, Axel Hahn, Benkt Wangler, Hans Weigand: Towards a Reference Ontology for Business Models. ER 2006: 482-496 |
49 | EE | Michael Schmitt, Laura Martignon: On the Complexity of Learning Lexicographic Strategies. Journal of Machine Learning Research 7: 55-83 (2006) |
2005 | ||
48 | EE | Michael Schmitt, Christophe Incoul, Eric Dubois: Supporting Business Experts in the Design of B2B Transactions Through Interactive Process Simulation. Business Process Management Workshops 2005: 342-352 |
47 | EE | Michael Schmitt, Laura Martignon: On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?. NIPS 2005 |
46 | EE | Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Inner Product Spaces for Bayesian Networks. Journal of Machine Learning Research 6: 1383-1403 (2005) |
45 | EE | Michael Schmitt: On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach. Neural Computation 17(3): 715-729 (2005) |
44 | EE | Frauke Friedrichs, Michael Schmitt: On the power of Boolean computations in generalized RBF neural networks. Neurocomputing 63: 483-498 (2005) |
2004 | ||
43 | EE | Michael Schmitt: An Improved VC Dimension Bound for Sparse Polynomials. COLT 2004: 393-407 |
42 | EE | Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Bayesian Networks and Inner Product Spaces. COLT 2004: 518-533 |
41 | EE | Michael Schmitt: On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions Electronic Colloquium on Computational Complexity (ECCC)(033): (2004) |
40 | EE | Michael Schmitt: Some dichotomy theorems for neural learning problems Electronic Colloquium on Computational Complexity (ECCC)(075): (2004) |
39 | EE | Michael Schmitt, Michael Trefz, Steffen Scholl: Einführung der Unternehmenssoftware SAP Business One beim Logistik-Dienstleiter Trefz. HMD - Praxis Wirtschaftsinform. 240: (2004) |
38 | EE | Michael Schmitt: Some Dichotomy Theorems for Neural Learning Problems. Journal of Machine Learning Research 5: 891-912 (2004) |
2002 | ||
37 | EE | Michael Schmitt: RBF Neural Networks and Descartes' Rule of Signs. ALT 2002: 321-335 |
36 | EE | Michael Schmitt: Descartes' Rule of Signs for Radial Basis Function Neural Networks. Neural Computation 14(12): 2997-3011 (2002) |
35 | EE | Michael Schmitt: On the Complexity of Computing and Learning with Multiplicative Neural Networks. Neural Computation 14(2): 241-301 (2002) |
34 | EE | Michael Schmitt: Neural Networks with Local Receptive Fields and Superlinear VC Dimension. Neural Computation 14(4): 919-956 (2002) |
2001 | ||
33 | EE | Michael Schmitt: Radial Basis Function Neural Networks Have Superlinear VC Dimension. COLT/EuroCOLT 2001: 14-30 |
32 | EE | Michael Schmitt: Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions. ICANN 2001: 247-252 |
31 | EE | Michael Schmitt: Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension. ICANN 2001: 253-258 |
30 | EE | Michael Schmitt: Neural Networks with Local Receptive Fields and Superlinear VC Dimension Electronic Colloquium on Computational Complexity (ECCC) 8(45): (2001) |
29 | EE | Michael Schmitt: On using the Poincaré polynomial for calculating the VC dimension of neural networks. Neural Networks 14(10): 1465- (2001) |
2000 | ||
28 | Alexandros Matsikis, Claudia Gönner, Michael Schmitt, Martin Rous, H. Jianxin, Karl-Friedrich Kraiss: Eliminierung von temporären Hindernissen im 2D- und 3D-Raum bei der Rekonstruktion einer Umgebung für einen teilautonomen mobilen Roboter. AMS 2000: 37-46 | |
27 | EE | Michael Schmitt: VC Dimension Bounds for Product Unit Networks. IJCNN (4) 2000: 165-170 |
26 | EE | Michael Schmitt: Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks Electronic Colloquium on Computational Complexity (ECCC) 7(2): (2000) |
25 | EE | Michael Schmitt: On the Complexity of Computing and Learning with Multiplicative Neural Networks Electronic Colloquium on Computational Complexity (ECCC) 7(86): (2000) |
1999 | ||
24 | Alexandros Matsikis, Michael Schmitt, Martin Rous, Karl-Friedrich Kraiss: Ein Konzept für die mobile Manipulation von unbekannten Objekten mit Hilfe von 3D-Rekonstruktion und Visual Servoing. AMS 1999: 179-187 | |
23 | Michael Schmitt, Jörg Brodersen, Georg Lietz, Frank Lomberg, Karl-Friedrich Kraiss: Kamerabasierte 3D-Rekonstruktion der Einsatzumgebung eines mobilen Roboters. AMS 1999: 356-365 | |
22 | EE | Michael Schmitt: VC dimension bounds for networks of spiking neurons. ESANN 1999: 429-434 |
21 | Michael Schmitt, Martin Rous, Alexandros Matsikis, Karl-Friedrich Kraiss: Vision-Based Self-Localization of a Mobile Robot Using a Virtual Environment. ICRA 1999: 2911-2916 | |
20 | EE | Michael Schmitt: Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks. NIPS 1999: 328-334 |
19 | Maximilian Ibel, Michael Schmitt, Klaus E. Schauser, Anurag Acharya: Shared Memory vs Message Passing on SCI: A Case Study Using Split-C. Scalable Coherent Interface 1999: 267-280 | |
18 | EE | Michael Schmitt: On the Sample Complexity for Nonoverlapping Neural Networks Electronic Colloquium on Computational Complexity (ECCC) 6(5): (1999) |
17 | Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding. Inf. Comput. 153(1): 26-46 (1999) | |
16 | Michael Schmitt: On the Sample Complexity for Nonoverlapping Neural Networks. Machine Learning 37(2): 131-141 (1999) | |
1998 | ||
15 | EE | Michael Schmitt: On the Sample Complexity for Neural Trees. ALT 1998: 375-384 |
14 | Michael Schmitt, Martin Rous, Karl-Friedrich Kraiss: Ein Leitstand zur Einsatzplanung und Überwachung mobiler Roboter. AMS 1998: 148-155 | |
13 | EE | Michael Schmitt, Maximilian Ibel, Anurag Acharya, Klaus E. Schauser: Adaptive Receiver Notification for Non-Dedicated Workstation Clusters. IEEE PACT 1998: 256-263 |
12 | Michael Schmitt, Thomas Krüger, Torsten Kuhlen, Karl-Friedrich Kraiss: Remore Virtual Reality - Ein Kommunikationssystem zur interaktiven Nutzung von Grafikanwendungen über ATM-Netze. Workshop Multimedia-Systeme, GI Jahrestagung 1998: 95-106 | |
11 | Michael Schmitt: On Computing Boolean Functions by a Spiking Neuron. Ann. Math. Artif. Intell. 24(1-4): 181-191 (1998) | |
10 | EE | Berthold Ruf, Michael Schmitt: Self-organization of spiking neurons using action potential timing. IEEE Transactions on Neural Networks 9(3): 575-578 (1998) |
9 | Michael Schmitt: Identification Criteria and Lower Bounds for Perceptron-LikeLearning Rules. Neural Computation 10(1): 235-250 (1998) | |
1997 | ||
8 | EE | Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for a Spiking Neuron (Extended Abstract). COLT 1997: 54-61 |
7 | Berthold Ruf, Michael Schmitt: Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. ICANN 1997: 361-366 | |
6 | Berthold Ruf, Michael Schmitt: Hebbian Learning in Networks of Spiking Neurons Using Temporal Coding. IWANN 1997: 380-389 | |
5 | EE | Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding Electronic Colloquium on Computational Complexity (ECCC) 4(49): (1997) |
4 | EE | Michael Schmitt: Proving Hardness of Neural Network Training Problems. Neural Networks 10(8): 1533-1534 (1997) |
3 | Berthold Ruf, Michael Schmitt: Learning Temporally Encoded Patterns in Networks of Spiking Neurons. Neural Processing Letters 5(1): 9-18 (1997) | |
1996 | ||
2 | EE | Thomas Natschläger, Michael Schmitt: Exact VC-Dimension of Boolean Monomials. Inf. Process. Lett. 59(1): 19-20 (1996) |
1 | EE | Thomas Natschläger, Michael Schmitt: Erratum: Exact VC-Dimension of Boolean Monomials. Inf. Process. Lett. 60(2): 107 (1996) |