no code implementations • 16 Oct 2023 • Thanh Tung Khuat, Robert Bassett, Ellen Otte, Alistair Grevis-James, Bogdan Gabrys
While machine learning (ML) has made significant contributions to the biopharmaceutical field, its applications are still in the early stages in terms of providing direct support for quality-by-design based development and manufacturing of biopharmaceuticals, hindering the enormous potential for bioprocesses automation from their development to manufacturing.
no code implementations • 23 Sep 2023 • Jiaqi Wen, Bogdan Gabrys, Katarzyna Musial
This study aims to improve the expressive power of node features in Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with heterogeneous feature representation principles.
no code implementations • 18 Aug 2023 • Jiaqi Wen, Bogdan Gabrys, Katarzyna Musial
This study proposes an extendable modelling framework for Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with a goal of generating networks that faithfully represent real systems.
no code implementations • 22 Jun 2023 • David Jacob Kedziora, Anna Musiał, Wojciech Rudno-Rudziński, Bogdan Gabrys
Novel methods for rapidly estimating single-photon source (SPS) quality have been promoted in recent literature to address the expensive and time-consuming nature of experimental validation via intensity interferometry.
no code implementations • 12 Jan 2023 • Mingshan Jia, Bogdan Gabrys, Katarzyna Musial
The mining and exploitation of graph structural information have been the focal points in the study of complex networks.
no code implementations • 8 Nov 2022 • Alexander Scriven, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
With most technical fields, there exists a delay between fundamental academic research and practical industrial uptake.
1 code implementation • 6 Oct 2022 • Thanh Tung Khuat, Bogdan Gabrys
hyperbox-brain is an open-source Python library implementing the leading hyperbox-based machine learning algorithms.
1 code implementation • 8 Aug 2022 • David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
The automated machine learning (AutoML) process can require searching through complex configuration spaces of not only machine learning (ML) components and their hyperparameters but also ways of composing them together, i. e. forming ML pipelines.
no code implementations • 9 May 2022 • Thanh Tung Khuat, David Jacob Kedziora, Bogdan Gabrys
As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the `how' and `why' of human-computer interaction (HCI) within these frameworks, both current and expected.
no code implementations • 15 Feb 2022 • Jiaqi Wen, Bogdan Gabrys, Katarzyna Musial
This paper aims to provide a comprehensive critical overview on how entities and their interactions in Complex Networked Systems (CNS) are modelled across disciplines as they approach their ultimate goal of creating a Digital Twin (DT) that perfectly matches the reality.
1 code implementation • 16 Dec 2021 • Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
That stated, NAS is not the be-all and end-all of AutoDL.
1 code implementation • 29 Sep 2021 • Joakim Skarding, Matthew Hellmich, Bogdan Gabrys, Katarzyna Musial-Gabrys
We compare link prediction heuristics, GNNs, discrete DGNNs, and continuous DGNNs on dynamic link prediction.
no code implementations • ICML Workshop AutoML 2021 • Rashid Bakirov, Damien Fay, Bogdan Gabrys
In this work, we propose using multi-armed bandit algorithms for learning adaptive strategies from incrementally streaming data on-the-fly.
2 code implementations • 1 May 2021 • Tien-Dung Nguyen, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
Machine learning (ML) pipeline composition and optimisation have been studied to seek multi-stage ML models, i. e. preprocessor-inclusive, that are both valid and well-performing.
no code implementations • 8 Jan 2021 • Patryk Grelewicz, Thanh Tung Khuat, Jacek Czeczot, Pawel Nowak, Tomasz Klopot, Bogdan Gabrys
In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed.
2 code implementations • 23 Dec 2020 • David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence, stimulated by advances in optimisation techniques and their impact on selecting ML models/algorithms.
1 code implementation • 21 Nov 2020 • Tien-Dung Nguyen, Bogdan Gabrys, Katarzyna Musial
Instead of executing the original ML pipeline to evaluate its validity, the AVATAR evaluates its surrogate model constructed by capabilities and effects of the ML pipeline components and input/output simplified mappings.
1 code implementation • 30 Sep 2020 • Thanh Tung Khuat, Bogdan Gabrys
However, one of the downsides of its original learning algorithms is the inability to handle and learn from the mixed-attribute data.
no code implementations • 1 Sep 2020 • Thanh Tung Khuat, Bogdan Gabrys
A general fuzzy min-max (GFMM) neural network is one of the efficient neuro-fuzzy systems for classification problems.
2 code implementations • 28 Aug 2020 • Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys
In this paper, we propose NATS-Bench, a unified benchmark on searching for both topology and size, for (almost) any up-to-date NAS algorithm.
no code implementations • 17 Jul 2020 • Abbas Raza Ali, Marcin Budka, Bogdan Gabrys
The exponential growth of volume, variety and velocity of data is raising the need for investigations of automated or semi-automated ways to extract useful patterns from the data.
no code implementations • 11 Jun 2020 • Neil Vaughan, Bogdan Gabrys
Expert VR data recordings can be used for guidance of novices.
no code implementations • 5 Jun 2020 • Xuanyi Dong, Mingxing Tan, Adams Wei Yu, Daiyi Peng, Bogdan Gabrys, Quoc V. Le
Efficient hyperparameter or architecture search methods have shown remarkable results, but each of them is only applicable to searching for either hyperparameters (HPs) or architectures.
no code implementations • 2 Jun 2020 • Hongxu Chen, Hongzhi Yin, Xiangguo Sun, Tong Chen, Bogdan Gabrys, Katarzyna Musial
Moreover, to adapt the proposed method to be capable of handling large-scale social networks, we propose a two-phase space reconciliation mechanism to align the embedding spaces in both network partitioning based parallel training and account matching across different social networks.
no code implementations • 1 Jun 2020 • Thanh Tung Khuat, Bogdan Gabrys
This paper proposes a simple yet powerful ensemble classifier, called Random Hyperboxes, constructed from individual hyperbox-based classifiers trained on the random subsets of sample and feature spaces of the training set.
no code implementations • 13 May 2020 • Joakim Skarding, Bogdan Gabrys, Katarzyna Musial
Second, we present a comprehensive survey of dynamic graph neural network models using the proposed terminology
no code implementations • 25 Mar 2020 • Thanh Tung Khuat, Bogdan Gabrys
Our proposed approach is based on the mathematical formulas to form a branch-and-bound solution aiming to remove the hyperboxes which are certain not to satisfy expansion or aggregation conditions, and in turn, decreasing the training time of learning algorithms.
no code implementations • 30 Jan 2020 • Tien-Dung Nguyen, Tomasz Maszczyk, Katarzyna Musial, Marc-Andre Zöller, Bogdan Gabrys
The evaluation of machine learning (ML) pipelines is essential during automatic ML pipeline composition and optimisation.
no code implementations • 8 Jan 2020 • Thanh Tung Khuat, Fang Chen, Bogdan Gabrys
This paper proposes an improved version of the current online learning algorithm for a general fuzzy min-max neural network (GFMM) to tackle existing issues concerning expansion and contraction steps as well as the way of dealing with unseen data located on decision boundaries.
1 code implementation • 31 Jul 2019 • Thanh Tung Khuat, Bogdan Gabrys
General fuzzy min-max (GFMM) neural network is a generalization of fuzzy neural networks formed by hyperbox fuzzy sets for classification and clustering problems.
1 code implementation • 29 May 2019 • Thanh Tung Khuat, Fang Chen, Bogdan Gabrys
Motivated by the practical demands for simplification of data towards being consistent with human thinking and problem solving as well as tolerance of uncertainty, information granules are becoming important entities in data processing at different levels of data abstraction.
no code implementations • 31 Jan 2019 • Thanh Tung Khuat, Dymitr Ruta, Bogdan Gabrys
With the rapid development of digital information, the data volume generated by humans and machines is growing exponentially.
1 code implementation • 27 Dec 2018 • Rashid Bakirov, Bogdan Gabrys, Damien Fay
Automation of machine learning model development is increasingly becoming an established research area.
no code implementations • 28 Dec 2016 • Manuel Martin Salvador, Marcin Budka, Bogdan Gabrys
In a range of extensive experiments, three different optimization strategies are used to automatically compose MCPSs for 21 publicly available data sets.