Komplexität neuronaler Lernprobleme. - Michael Schmitt 001 (Lang, 1994)

Exact VC-Dimension of Boolean Monomials. - Thomas Natschläger; Michael Schmitt 001 (Inf. Process. Lett., 1996)

Erratum: Exact VC-Dimension of Boolean Monomials. - Thomas Natschläger; Michael Schmitt 001 (Inf. Process. Lett., 1996)

On the Complexity of Learning for a Spiking Neuron (Extended Abstract). - Wolfgang Maass 001; Michael Schmitt 001 (COLT, 1997)

Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. - Berthold Ruf; Michael Schmitt 001 (ICANN, 1997)

Hebbian Learning in Networks of Spiking Neurons Using Temporal Coding. - Berthold Ruf; Michael Schmitt 001 (IWANN, 1997)

On the Complexity of Learning for Spiking Neurons with Temporal Coding - Wolfgang Maass 001; Michael Schmitt 001 (Electron. Colloquium Comput. Complex., 1997)

Proving Hardness of Neural Network Training Problems. - Michael Schmitt 001 (Neural Networks, 1997)

Learning Temporally Encoded Patterns in Networks of Spiking Neurons. - Berthold Ruf; Michael Schmitt 001 (Neural Process. Lett., 1997)

On the Sample Complexity for Neural Trees. - Michael Schmitt 001 (ALT, 1998)

On Computing Boolean Functions by a Spiking Neuron. - Michael Schmitt 001 (Ann. Math. Artif. Intell., 1998)

Identification Criteria and Lower Bounds for Perceptron-LikeLearning Rules. - Michael Schmitt 001 (Neural Comput., 1998)

Self-organization of spiking neurons using action potential timing. - Berthold Ruf; Michael Schmitt 001 (IEEE Trans. Neural Networks, 1998)

VC dimension bounds for networks of spiking neurons. - Michael Schmitt 001 (ESANN, 1999)

Simplicity and Robustness of Fast and Frugal Heuristics. - Laura Martignon; Michael Schmitt 001 (Minds Mach., 1999)

On the Sample Complexity for Nonoverlapping Neural Networks. - Michael Schmitt 001 (Mach. Learn., 1999)

VC Dimension Bounds for Product Unit Networks. - Michael Schmitt 001 (IJCNN (4), 2000)

Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks - Michael Schmitt 001 (Electron. Colloquium Comput. Complex., 2000)

On the Complexity of Computing and Learning with Multiplicative Neural Networks - Michael Schmitt 001 (Electron. Colloquium Comput. Complex., 2000)

Radial Basis Function Neural Networks Have Superlinear VC Dimension. - Michael Schmitt 001 (COLT/EuroCOLT, 2001)

Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions. - Michael Schmitt 001 (ICANN, 2001)

Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension. - Michael Schmitt 001 (ICANN, 2001)

Neural Networks with Local Receptive Fields and Superlinear VC Dimension - Michael Schmitt 001 (Electron. Colloquium Comput. Complex., 2001)

On using the Poincaré polynomial for calculating the VC dimension of neural networks. - Michael Schmitt 001 (Neural Networks, 2001)

RBF Neural Networks and Descartes' Rule of Signs. - Michael Schmitt 001 (ALT, 2002)

Descartes' Rule of Signs for Radial Basis Function Neural Networks. - Michael Schmitt 001 (Neural Comput., 2002)

Bayesian Networks and Inner Product Spaces. - Atsuyoshi Nakamura; Michael Schmitt 001; Niels Schmitt; Hans Ulrich Simon (COLT, 2004)

An Improved VC Dimension Bound for Sparse Polynomials. - Michael Schmitt 001 (COLT, 2004)

Some dichotomy theorems for neural learning problems - Michael Schmitt 001 (Electron. Colloquium Comput. Complex., 2004)

New Designs for the Descartes Rule of Signs. - Michael Schmitt 001 (Am. Math. Mon., 2004)

On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions. - Michael Schmitt 001 (IEEE Trans. Neural Networks, 2004)

On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?. - Michael Schmitt 001; Laura Martignon (NIPS, 2005)

On the power of Boolean computations in generalized RBF neural networks. - Frauke Friedrichs; Michael Schmitt 001 (Neurocomputing, 2005)

Inner Product Spaces for Bayesian Networks. - Atsuyoshi Nakamura; Michael Schmitt 001; Niels Schmitt; Hans Ulrich Simon (J. Mach. Learn. Res., 2005)

On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach. - Michael Schmitt 001 (Neural Comput., 2005)

On the Complexity of Learning Lexicographic Strategies. - Michael Schmitt 001; Laura Martignon (J. Mach. Learn. Res., 2006)