18 citations · 19 across the 7 of their papers we have counts for
7 papers
Safety and optimality in learning-based control at low computational cost
Dominik Baumann, Krzysztof Kowalczyk, Cristian R. Rojas +2
Applying machine learning methods to physical systems that are supposed to act in the real world requires providing safety guarantees. However, methods that include such guarantees…
Kernel-based learning with guarantees for multi-agent applications
Krzysztof Kowalczyk, Paweł Wachel, Cristian R. Rojas
This paper addresses a kernel-based learning problem for a network of agents locally observing a latent multidimensional, nonlinear phenomenon in a noisy environment. We propose a…
A computationally lightweight safe learning algorithm
Dominik Baumann, Krzysztof Kowalczyk, Koen Tiels +1
Safety is an essential asset when learning control policies for physical systems, as violating safety constraints during training can lead to expensive hardware damage. In response…
Decentralized diffusion-based learning under non-parametric limited prior knowledge
Paweł Wachel, Krzysztof Kowalczyk, Cristian R. Rojas
We study the problem of diffusion-based network learning of a nonlinear phenomenon, , from local agents' measurements collected in a noisy environment. For a decentralized netwo…
Orthogonal Transforms in Neural Networks Amount to Effective Regularization
Krzysztof Zając, Wojciech Sopot, Paweł Wachel
We consider applications of neural networks in nonlinear system identification and formulate a hypothesis that adjusting general network structure by incorporating frequency inform…
On state-space representations of general discrete-time dynamical systems
Cristian R. Rojas, Pawel Wachel
In this paper we establish that every (deterministic) non-autonomous, discrete-time, causal, time invariant system has a state-space representation, and discuss its minimality.
Nonlinear system modeling based on constrained Volterra series estimates
P. Śliwiński, A. Marconato, P. Wachel +1
A simple nonlinear system modeling algorithm designed to work with limited \emph{a priori }knowledge and short data records, is examined. It creates an empirical Volterra series-ba…