 | 2006 |
|---|
| 54 |       | Birger Andersson,
Maria Bergholtz,
Bertrand Grégoire,
Paul Johannesson,
Michael Schmitt,
Jelena Zdravkovic:
From Business to Process Models - a Chaining Methodology.
BUSITAL 2006 |
| 53 | | 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 | | Bertrand Grégoire,
Michael Schmitt:
Business Service Network Design: From Business Model to an Integrated Multi-Partner Business Transaction.
CEC/EEE 2006: 84 |
| 51 | | 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 | | 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 | | Michael Schmitt,
Laura Martignon:
On the Complexity of Learning Lexicographic Strategies.
Journal of Machine Learning Research 7: 55-83 (2006) |
| 2005 |
|---|
| 48 | | 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 | | Michael Schmitt,
Laura Martignon:
On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?.
NIPS 2005 |
| 46 | | 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 | | Michael Schmitt:
On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach.
Neural Computation 17(3): 715-729 (2005) |
| 44 | | Frauke Friedrichs,
Michael Schmitt:
On the power of Boolean computations in generalized RBF neural networks.
Neurocomputing 63: 483-498 (2005) |
| 2004 |
|---|
| 43 | | Michael Schmitt:
An Improved VC Dimension Bound for Sparse Polynomials.
COLT 2004: 393-407 |
| 42 | | Atsuyoshi Nakamura,
Michael Schmitt,
Niels Schmitt,
Hans-Ulrich Simon:
Bayesian Networks and Inner Product Spaces.
COLT 2004: 518-533 |
| 41 | | 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 | | Michael Schmitt:
Some dichotomy theorems for neural learning problems
Electronic Colloquium on Computational Complexity (ECCC)(075): (2004) |
| 39 | | Michael Schmitt,
Michael Trefz,
Steffen Scholl:
Einführung der Unternehmenssoftware SAP Business One beim Logistik-Dienstleiter Trefz.
HMD - Praxis Wirtschaftsinform. 240: (2004) |
| 38 | | Michael Schmitt:
Some Dichotomy Theorems for Neural Learning Problems.
Journal of Machine Learning Research 5: 891-912 (2004) |
| 2002 |
|---|
| 37 | | Michael Schmitt:
RBF Neural Networks and Descartes' Rule of Signs.
ALT 2002: 321-335 |
| 36 | | Michael Schmitt:
Descartes' Rule of Signs for Radial Basis Function Neural Networks.
Neural Computation 14(12): 2997-3011 (2002) |
| 35 | | Michael Schmitt:
On the Complexity of Computing and Learning with Multiplicative Neural Networks.
Neural Computation 14(2): 241-301 (2002) |
| 34 | | Michael Schmitt:
Neural Networks with Local Receptive Fields and Superlinear VC Dimension.
Neural Computation 14(4): 919-956 (2002) |
| 2001 |
|---|
| 33 | | Michael Schmitt:
Radial Basis Function Neural Networks Have Superlinear VC Dimension.
COLT/EuroCOLT 2001: 14-30 |
| 32 | | Michael Schmitt:
Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions.
ICANN 2001: 247-252 |
| 31 | | Michael Schmitt:
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension.
ICANN 2001: 253-258 |
| 30 | | Michael Schmitt:
Neural Networks with Local Receptive Fields and Superlinear VC Dimension
Electronic Colloquium on Computational Complexity (ECCC) 8(45): (2001) |
| 29 | | 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 | | Michael Schmitt:
VC Dimension Bounds for Product Unit Networks.
IJCNN (4) 2000: 165-170 |
| 26 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | Thomas Natschläger,
Michael Schmitt:
Exact VC-Dimension of Boolean Monomials.
Inf. Process. Lett. 59(1): 19-20 (1996) |
| 1 | | Thomas Natschläger,
Michael Schmitt:
Erratum: Exact VC-Dimension of Boolean Monomials.
Inf. Process. Lett. 60(2): 107 (1996) |
