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Hecker, Dirk

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Dr. rer. nat.

Hecker, Dirk

0000-0002-4742-6266

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Bauckhage, Christian

Wrobel, Stefan 2

Piatkowski, Nico 1

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Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS 2

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decision boundaries 1

hyperbolic tangent 1

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tanh Neurons are Bayesian Decision Makers

( 2021)
Bauckhage, Christian
;
Sifa, Rafet
;
Hecker, Dirk

The hyperbolic tangent (tanh) is a traditional choice for the activation function of the neurons of an artificial neural network. Here, we go through a simple calculation that shows that this modeling choice is linked to Bayesian decision theory. Our brief, tutorial-like discussion is intended as a reference to an observation rarely mentioned in standard textbooks.
Max-Sum Dispersion via Quantum Annealing

( 2019)
Bauckhage, Christian
;
Sifa, Rafet
;
Hecker, Dirk
;
Wrobel, Stefan

We devise an Ising model for the max-sum dispersion problem which occurs in contexts such as Web search or text summarization. Given this Ising model, max-sum dispersion can be solved on adiabatic quantum computers; in proof of concept simulations, we solve the corresponding Schrödinger equations and observe our approach to work well.
A QUBO Formulation of the k-Medoids Problem

( 2019)
Bauckhage, Christian
;
Piatkowski, Nico
;
Sifa, Rafet
;
Hecker, Dirk
;
Wrobel, Stefan

We are concerned with k-medoids clustering and propose aquadratic unconstrained binary optimization (QUBO) formulation of the problem of identifying k medoids among n data points without having to cluster the data. Given our QUBO formulation of this NP-hard problem, it should be possible to solve it on adiabatic quantum computers.

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