Our research is conducted in the following research groups:
Laboratory Tensor networks and deep learning for applications in data mining under the guidance of Prof. Andrzej Cichocki on the basis of the Skolkovo Institute of Science and Technology develops new fundamental approaches for training, testing and storing parameters of deep neural networks based on tensor decomposition techniques. These approaches allow to reduce by orders of magnitude computational complexity and required memory for the operation of the network, while maintaining a high quality of prediction.
The Laboratory mission is to pursue cutting-edge research in the design and analysis of deep neural networks, tensor decompositions, tensor networks and multiway analysis with many potential practical applications.
The Laboratory brings together several professors and young researchers in the fields of machine learning, computer vision, artificial intelligence, robotics, large-scale data analysis, mathematics as well as computational neuroscience and bioinformatics.
The main research interest of the group is in finding new ways in chemical informatics that are based on a combination of physical chemistry methods with the machine learning techniques for prediction of properties of organic compounds. Our primary goal is to develop methods that, on one hand, are accurate and, on the other hand, are universal and have wide applicability domains.