Conference on Innovations in Intelligent Systems and Applications (ASYU 2019) is organized by Yaşar University, in cooperation with Yildiz Technical University and will be held in Izmir between the dates of October 31 – November 2, 2019. The language of the symposium will be English and Turkish. Special session proposals in hot topics will be evaluated by Program Chairs. Submitted papers of the general and special session tracks will undergo a triple-blind review process.
The topics of interest mainly cover Artificial Intelligence, Deep Learning, Fuzzy Logic, Smart Systems, Machine Learning, and Data Mining. In particular, the topics include:
Intelligent Life
Bioinformatics
Natural Language Processing
Swarm Intelligence
Genetic Algorithms
Memetic Computing
Neuroscience
Smart Environment
Technology and Law
Intelligent Approaches in Signal and Image Processing
Intelligent Applications in Biomedical Engineering
Hardware Implementations for Intelligent Systems
Intelligent Approaches in Robotic and Automation
Human-Computer Interaction
Augmented- Virtual Reality
Suggestion Systems
Intelligent Biometric Systems
Accepted papers will be published as full text on the IEEE Xplore digital library.
Deadline for Full Paper Submission : July 7th, 2019
Announcement of Accepted Papers: August 23th, 2019
Deadline for Camera Ready Papers & Early bird registration: September 13th, 2019
Conference: October 31st – November 2nd 2019
Vessel Tree Classification for Transplant Candidate
Click here for the web address of the contest.
Robot Football Competition
Click here for call for the competition.
The Adventure of Machine Learning
Prof.Dr. Fatos T. Yarman Vural
One of the fields of computer science is to develop thinking, learning and problem solving systems. Although our efforts in this area sometimes result in great disappointments, we do not give up. We are trying to develop more intelligent and resourceful machines. Here, Machine Learning is the adventure of mankind's racing his own intelligence with his own machines.
Machine Learning has recently been transformed into a new area called Deep Learning. Scientists who research in the field of Deep Learning model these processes by studying the cognitive processes of living things and develop algorithms that can learn using these models.In this speech, the process of machine learning to deep learning will be explained and the theoretical and technological end point of this field.In addition, the philosophical, sociological and ethical problems of Deep Learning technologies will be discussed.
Subspace Methods and Finance Applications
Subspace methods spanning from principal component analysis (PCA) and Karhunen-Loeve transform (KLT) to wavelet transform have been successfully used in applications including face recognition, facial emotion analysis, image/video compression, recommending systems and many others. In this talk, we will revisit the mathematical concepts underlying these powerful analytical tools and emphasize a unified perspective for their use in signal decomposition and time-frequency analysis. Then, we will focus on eigensubspace of normalized returns for a basket of assets and present the methodology to design their eigenportfolios for financial investments. We will present and compare performances of Minimum Variance, Market (Markowitz) and Eigen Portfolios for US Equities to highlight the merit of the latter.
Click for call for papers.
