17th Asian Conference on Intelligent Information and Database Systems
23-25 April 2025, Kitakyushu, Japan
Submit to this session
23-25 April 2025, Kitakyushu, Japan
MLA 2025
Special Session onMachine Learning Algorithms
at the 17th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2025)23-25 April 2025, Kitakyushu, Japan
Special Session Organizers
Prof. dr hab. Urszula Boryczka
University of Silesia in Katowice, Poland
E-mail: urszula.boryczka@us.edu.pl
Dr Rustam Mussabayev
Institute of Information and Computational Technologies, Satbayev University, Almaty, Kazakhstan
E-mail: ru.mussabayev@satbayev.university
Dr hab. Małgorzata Przybyła-Kasperek, prof. US
University of Silesia in Katowice, Poland
E-mail: malgorzata.przybyla-kasperek@us.edu.pl
Dr Rafał Skinderowicz
University of Silesia in Katowice, Poland
E-mail: rafal.skinderowicz@us.edu.pl
University of Silesia in Katowice, Poland
E-mail: urszula.boryczka@us.edu.pl
Dr Rustam Mussabayev
Institute of Information and Computational Technologies, Satbayev University, Almaty, Kazakhstan
E-mail: ru.mussabayev@satbayev.university
Dr hab. Małgorzata Przybyła-Kasperek, prof. US
University of Silesia in Katowice, Poland
E-mail: malgorzata.przybyla-kasperek@us.edu.pl
Dr Rafał Skinderowicz
University of Silesia in Katowice, Poland
E-mail: rafal.skinderowicz@us.edu.pl
Objectives and topics
Machine learning algorithms are inspired by the way living beings learn. Most often, we are dealing with a simple mechanism of reinforcing desirable behaviour and ignoring inappropriate behaviour, combined with providing the necessary time to develop its own mode of action. The IT equivalent of such a process is called machine learning, which is a subset of artificial intelligence solutions. In the nutshell, a Machine Learning algorithm is given input, a goal and feedback if it is moving in the right direction. It is also given time to work out for itself the best way to achieve its goal.
In the business sphere, machine learning allows compa nies to understand the data they have and extract relevant management information from it. A company can use this technology in a wide variety of applications, the goal of which can be, for example, to increase sales, to create an effective product search engine with hints and suggestions for the buyer, or even to launch an autonomous car.
ML algorithms have proven their usefulness wherever traditional solutions based on lists of instructions have proved useless. Their outstanding capabilities can be seen, for example, in recognising objects in photographs, recognising speech and translating it into other languages, and in analysing and searching for correlations in large Big Data datasets.
Artificial intelligence and machine learning are increasingly being used to create works of art or simulate creative processes. From computational intelligence algorithms to sophisticated neural network architectures , this interesting discipline of computer science is revolutionising the fields of art, poetry and music. The explanation of these processes and their correct interpretability may contribute to the discovery of completely new areas of application, at a completely different level of abstraction.
Topics:
In the business sphere, machine learning allows compa nies to understand the data they have and extract relevant management information from it. A company can use this technology in a wide variety of applications, the goal of which can be, for example, to increase sales, to create an effective product search engine with hints and suggestions for the buyer, or even to launch an autonomous car.
ML algorithms have proven their usefulness wherever traditional solutions based on lists of instructions have proved useless. Their outstanding capabilities can be seen, for example, in recognising objects in photographs, recognising speech and translating it into other languages, and in analysing and searching for correlations in large Big Data datasets.
Artificial intelligence and machine learning are increasingly being used to create works of art or simulate creative processes. From computational intelligence algorithms to sophisticated neural network architectures , this interesting discipline of computer science is revolutionising the fields of art, poetry and music. The explanation of these processes and their correct interpretability may contribute to the discovery of completely new areas of application, at a completely different level of abstraction.
Topics:
- Regression
- Classification
- Clustering
- Time-series forecasting
- Anomaly detection
- Ranking
- Recommendation
- Data generation
- Optimization
- Deep Learning Algorithms
- Dimensionality Reduction Algorithms
- Ensemble Algorithms
- Generative Art
ACIIDS 2025 important dates
Paper submission: January 19, 2025 (hard deadline)
Notification of acceptance: February 10, 2025
Camera-ready papers: February 24, 2025
Registration & payment: February 24, 2025
Conference date: April 23-25, 2025
Notification of acceptance: February 10, 2025
Camera-ready papers: February 24, 2025
Registration & payment: February 24, 2025
Conference date: April 23-25, 2025