Katsaggelos Delivers Tutorial & Presents 2 Papers at IEEE International Conference on Image Processing
He taught a 3-hour tutorial, titled, "Optimization Techniques for Sparse/Low-Rank Recovery Problems in Image Processing and Machine Learning" and presented two papers.
Prof. Aggelos K. Katsaggelos traveled to Paris, France to attend the 2014 IEEE International Conference on Image Processing, held Oct 27-30, where he taught a 3-hour tutorial, titled, "Optimization Techniques for Sparse/Low-Rank Recovery Problems in Image Processing and Machine Learning" and presented two papers.
Prof. Katsaggelos also traveled to the University of Applied Science HSR, Rapperswil, Switzerland on Thursday, October 30, 2014, where he gave a 4-hour short course on the same topic.
Tutorial Description:
Due to their wide applicability, sparse and low-rank models have quickly become some of the most important tools for today’s researchers in image/video processing, computer vision, machine learning, statistics, optimization, and bioinformatics. Application areas in which sparse and low-rank modelling tools have been applied span a wide range of topics in these fields including: image inpainting and compressive sensing, object/face recognition, clustering and classification, Deep Learning feature selection, Collaborative Filtering, video survelience, and many more.
However while sparse and low-rank models themselves are typically fairly straightforward to grasp in applications, often times the optimization machinery required to make use of these models can be unfamiliar to students and researchers with a more traditional electrical, biomedical, statistics, or computer engineering/science background. Therefore a major distinctive feature of this tutorial course will be a practical focus on connecting fundamental concepts in optimization with their natural (and cutting edge) extensions for solving sparse and low-rank problems. No previous exposure to nonlinear programming is required for this tutorial. We will review the fundamental concepts as needed throughout the course.
In this tutorial, based on a book manuscript currently under development, we will spend the first third of the class introducing sparse and low-rank models in the context of various applications. We will then spend the remainder of the class accessibly explaining the cutting edge methods used to solve sparse and low-rank recovery problems. This coverage of optimization techniques will include: a discussion of greedy methods for sparse recovery, an overview of essential concepts from nonlinear programming, smooth reformulation techniques for sparse and low-rank problems, accelerated proximal gradient techniques, and the Alternating Direction Method of Multipliers framework.
IEEE ICIP 2014 Conference:
The International Conference on Image Processing (ICIP), sponsored by the IEEE Signal Processing Society, is the premier forum for the presentation of technological advances and research results in the fields of theoretical, experimental, and applied image and video processing. ICIP 2014, the 21st in the series that has been held annually since 1994, brings together leading engineers and scientists in image and video processing from around the world.