Michael Schmitt

Michael Schmitt, Uwe Stilla: Compressive Sensing Based Layover Separation in Airborne Single-Pass Multi-Baseline InSAR Data. IEEE Geosci. Remote Sensing Lett. 10(2): 313-317 (2013)

Takuma Anahara, Michael Schmitt, Junichi Susaki: Non-linear correction of polarization orientation for the application of ICA to PolSAR imagery. IGARSS 2012: 3142-3145

Oliver Maksymiuk, Michael Schmitt, Andreas R. Brenner, Uwe Stilla: First investigations on detection of stationary vehicles in airborne decimeter resolution SAR data by supervised learning. IGARSS 2012: 3584-3587

Takuma Anahara, Michael Schmitt, Masayuki Tamura: A filter for homogeneous areas in very high resolution SAR images based on hysteresis smoothing. IGARSS 2012: 3588-3591

Michael Schmitt, Uwe Stilla: Adaptive multilooking of airborne Ka-band multi-baseline InSAR data of urban areas. IGARSS 2012: 7401-7404

Michael Schmitt, Christophe Magnard, Thorsten Brehm, Uwe Stilla: Towards Airborne Single Pass Decimeter Resolution SAR Interferometry over Urban Areas. PIA 2011: 197-208

Michael Schmitt, Uwe Stilla: Utilization of airborne multi-aspect InSAR data for the generation of urban ortho-images. IGARSS 2010: 3937-3940

Michael Schmitt, Laura Martignon: On the Complexity of Learning Lexicographic Strategies. Journal of Machine Learning Research 7: 55-83 (2006)

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

Birger Andersson, Maria Bergholtz, Bertrand Grégoire, Paul Johannesson, Michael Schmitt, Jelena Zdravkovic: From Business to Process Models - a Chaining Methodology. BUSITAL 2006

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

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

Bertrand Grégoire, Michael Schmitt: Business Service Network Design: From Business Model to an Integrated Multi-Partner Business Transaction. CEC/EEE 2006: 84

Frauke Friedrichs, Michael Schmitt: On the power of Boolean computations in generalized RBF neural networks. Neurocomputing 63: 483-498 (2005)

Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Inner Product Spaces for Bayesian Networks. Journal of Machine Learning Research 6: 1383-1403 (2005)

Michael Schmitt: On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach. Neural Computation 17(3): 715-729 (2005)

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

Michael Schmitt, Laura Martignon: On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?. NIPS 2005

Michael Schmitt, Michael Trefz, Steffen Scholl: Einführung der Unternehmenssoftware SAP Business One beim Logistik-Dienstleiter Trefz. HMD - Praxis Wirtschaftsinform. 240 (2004)

Michael Schmitt: Some Dichotomy Theorems for Neural Learning Problems. Journal of Machine Learning Research 5: 891-912 (2004)

Michael Schmitt: New Designs for the Descartes Rule of Signs. The American Mathematical Monthly 111(2): 159-164 (2004)

Michael Schmitt: On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions. IEEE Transactions on Neural Networks 15(5): 995-1001 (2004)

Michael Schmitt: An Improved VC Dimension Bound for Sparse Polynomials. COLT 2004: 393-407

Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Bayesian Networks and Inner Product Spaces. COLT 2004: 518-533

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)

Michael Schmitt: Some dichotomy theorems for neural learning problems. Electronic Colloquium on Computational Complexity (ECCC)(075) (2004)

Michael Schmitt: Automatic test generation based on formal specifications: practical procedures for efficient state space exploration and improved representation of test cases. University of Göttingen 2003

Michael Schmitt: On the Complexity of Computing and Learning with Multiplicative Neural Networks. Neural Computation 14(2): 241-301 (2002)

Michael Schmitt: Neural Networks with Local Receptive Fields and Superlinear VC Dimension. Neural Computation 14(4): 919-956 (2002)

Michael Schmitt: Descartes' Rule of Signs for Radial Basis Function Neural Networks. Neural Computation 14(12): 2997-3011 (2002)

Michael Schmitt: RBF Neural Networks and Descartes' Rule of Signs. ALT 2002: 321-335

Michael Schmitt: On using the Poincaré polynomial for calculating the VC dimension of neural networks. Neural Networks 14(10): 1465- (2001)

Michael Schmitt: Radial Basis Function Neural Networks Have Superlinear VC Dimension. COLT/EuroCOLT 2001: 14-30

Michael Schmitt: Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions. ICANN 2001: 247-252

Michael Schmitt: Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension. ICANN 2001: 253-258

Michael Schmitt: Neural Networks with Local Receptive Fields and Superlinear VC Dimension. Electronic Colloquium on Computational Complexity (ECCC) 8(45) (2001)

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

Michael Schmitt: VC Dimension Bounds for Product Unit Networks. IJCNN (4) 2000: 165-170

Michael Schmitt: Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks. Electronic Colloquium on Computational Complexity (ECCC) 7(2) (2000)

Michael Schmitt: On the Complexity of Computing and Learning with Multiplicative Neural Networks. Electronic Colloquium on Computational Complexity (ECCC) 7(86) (2000)

Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding. Inf. Comput. 153(1): 26-46 (1999)

Michael Schmitt: On the Sample Complexity for Nonoverlapping Neural Networks. Machine Learning 37(2): 131-141 (1999)

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

Michael Schmitt, Jörg Brodersen, Georg Lietz, Frank Lomberg, Karl-Friedrich Kraiss: Kamerabasierte 3D-Rekonstruktion der Einsatzumgebung eines mobilen Roboters. AMS 1999: 356-365

Michael Schmitt: VC dimension bounds for networks of spiking neurons. ESANN 1999: 429-434

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

Michael Schmitt: Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks. NIPS 1999: 328-334

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

Michael Schmitt: On the Sample Complexity for Nonoverlapping Neural Networks. Electronic Colloquium on Computational Complexity (ECCC) 6(5) (1999)

Michael Schmitt: On Computing Boolean Functions by a Spiking Neuron. Ann. Math. Artif. Intell. 24(1-4): 181-191 (1998)

Michael Schmitt: Identification Criteria and Lower Bounds for Perceptron-LikeLearning Rules. Neural Computation 10(1): 235-250 (1998)

Berthold Ruf, Michael Schmitt: Self-organization of spiking neurons using action potential timing. IEEE Transactions on Neural Networks 9(3): 575-578 (1998)

Michael Schmitt, Maximilian Ibel, Anurag Acharya, Klaus E. Schauser: Adaptive Receiver Notification for Non-Dedicated Workstation Clusters. IEEE PACT 1998: 256-263

Michael Schmitt: On the Sample Complexity for Neural Trees. ALT 1998: 375-384

Michael Schmitt, Martin Rous, Karl-Friedrich Kraiss: Ein Leitstand zur Einsatzplanung und Überwachung mobiler Roboter. AMS 1998: 148-155

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

Michael Schmitt: Proving Hardness of Neural Network Training Problems. Neural Networks 10(8): 1533-1534 (1997)

Berthold Ruf, Michael Schmitt: Learning Temporally Encoded Patterns in Networks of Spiking Neurons. Neural Processing Letters 5(1): 9-18 (1997)

Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for a Spiking Neuron (Extended Abstract). COLT 1997: 54-61

Berthold Ruf, Michael Schmitt: Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. ICANN 1997: 361-366

Berthold Ruf, Michael Schmitt: Hebbian Learning in Networks of Spiking Neurons Using Temporal Coding. IWANN 1997: 380-389

Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding. Electronic Colloquium on Computational Complexity (ECCC) 4(49) (1997)

Thomas Natschläger, Michael Schmitt: Exact VC-Dimension of Boolean Monomials. Inf. Process. Lett. 59(1): 19-20 (1996)

Thomas Natschläger, Michael Schmitt: Erratum: Exact VC-Dimension of Boolean Monomials. Inf. Process. Lett. 60(2): 107 (1996)