IEEE DSLW 2021 - IEEE Data Science and Learning Workshop
Topics/Call fo Papers
The 2021 IEEE Data Science & Learning Workshop (DSLW 2021), to be co-located with ICASSP 2021, will be held at the University of Toronto on June 05-06, 2021. The workshop is organized by Data Science Initiative group of the IEEE Signal Processing Society. The workshop will bring together researchers in academia and industry to share the most recent and exciting advances in data science and learning theory and applications, in disciplines including signal processing, statistics, machine learning, data mining and computer vision. Papers are solicited in, but not limited to, the following areas:
Statistical learning algorithms, models and theories
Machine learning theories, models and systems
Computational models and representation for data science
Visualization, summarization, and analytics
Acquisition, storage, and retrieval for big data
Large scale optimization
Learning, modeling, and inference with data
Data science process and principles
Ethics, privacy, fairness, security and trust in data science & learning
Applications
Statistical learning algorithms, models and theories
Machine learning theories, models and systems
Computational models and representation for data science
Visualization, summarization, and analytics
Acquisition, storage, and retrieval for big data
Large scale optimization
Learning, modeling, and inference with data
Data science process and principles
Ethics, privacy, fairness, security and trust in data science & learning
Applications
Other CFPs
Last modified: 2020-09-10 17:30:39