posted by organizer: dhan9000 || 4149 views || tracked by 5 users: [display]

ICASSP 2019 : Special Session on LEARNING METHODS IN COMPLEX AND HYPERCOMPLEX DOMAINS

FacebookTwitterLinkedInGoogle

Link: https://sites.google.com/uniroma1.it/icassp2019-hypercomplex/home
 
When May 12, 2019 - May 17, 2019
Where Brighton, UK
Submission Deadline Oct 29, 2018
Notification Due Feb 1, 2019
Final Version Due Feb 18, 2019
Categories    machine learning   signal processing   neural networks   learning algorithms
 

Call For Papers

Traditional signal processing and machine learning applications rely on the use of learning methods in the real- and complex-valued domains. However, modern technologies have fueled an ever-increasing number of emerging applications in which signals relies on unconventional algebraic structures (e.g., non-commutative). In this context, advanced complex- and hypercomplex-valued signal processing encompasses many of these challenging areas. In the complex domain, the augmented statistics have been found to be very effective in different methods of machine learning and nonlinear signal processing. However, processing signals in hypercomplex domains enables us to exploit some different properties, albeit raising challenges in designing and implementing new and more effective learning algorithms. More generally, learning in the hypercomplex domain allows us to process multidimensional data as a single entity rather than modelling as a multichannel entity, hence preserving the integrity of the data. In that direction, quaternions have attracted attention in the signal processing and machine learning communities for their capability of dealing with 3D and 4D models.

The aim of this special session is to bring together leading researchers in the fields of signal processing and machine learning and provide advances on learning methods in complex and hypercomplex domains that can empower science and technology for humankind.



List of Topics:
- Advanced Complex-Valued Learning Methods
- Complex-Valued Nonlinear Adaptive Filters
- Clifford and Geometric Algebras for Adaptive Filtering and Signal Processing
- Hypercomplex Machine Learning
- Complex- and Quaternion-Valued Neural Networks
- Complex- and Hypercomplex-Valued Activation Functions
- Sparse Representations in the Hypercomplex Domain
- Complex and Hypercomplex Learning over Graphs and Networks
- Algorithms for Hypercomplex Optimization
- Advances in Image Processing using Quaternions
- Audio Processing in the Hypercomplex Domain
- Emerging Fields of Applications in the Hypercomplex Domain

Related Resources

MLDM 2023   18th International Conference on Machine Learning and Data Mining
IJCNN 2023   International Joint Conference on Neural Networks
ISIR-eCom 2022   INTERACTIVE AND SCALABLE INFORMATION RETRIEVAL METHODS FOR ECOMMERCE ((conjunction with WSDM 2022)
CFDSP 2023   2023 International Conference on Frontiers of Digital Signal Processing (CFDSP 2023)
ICASSP 2022   2022 IEEE International Conference on Acoustics, Speech, & Signal Processing
ICMLA 2022   IEEE International conference on Machine Learning and Applications
MLMHCIHCAMCI 2022   Machine Learning Methods in High-Content Imaging and High-Content Analysis for Molecular and Cellular Imaging
MLMHCIHCAMCI 2022   Machine Learning Methods in High-Content Imaging and High-Content Analysis for Molecular and Cellular Imaging
AIMLNET 2022   2nd International conference on AI, Machine Learning in Communications and Networks
AICE 2022   Call for Chapters: Artificial Intelligence Methods and Applications in Computer Engineering