Big Data Stream Analytics and Online Metric Learning

Dr. Latifur Khan
Dr. Latifur Khan

Abstract: Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Data streams demonstrate several unique properties that together conform to the characteristics of big data (i.e., volume, velocity, variety, and veracity) and add challenges to data mining. In this first part of this talk, we will present an organized picture on how to handle various data mining/machine learning techniques in data streams.

In the second part, we aim to address the open challenge of  Online Adaptive Metric Learning for learning adaptive metric functions on-the-fly. We present a new online metric learning framework that attempts to tackle the challenge by learning an ANN-based metric with adaptive model complexity from a stream of constraints. We empirically validate the effectiveness and efficacy of our framework on various applications such as real-world image classification, facial verification, and image retrieval.

This research was funded in part by National Science Foundation, National Aeronautics and Space Administration, Air Force Office of Scientific Research, National Security Agency, International Business Machines (IBM) Organization Research, and Raytheon.

Speaker’s Bio: Dr. Latifur Khan is currently a full Professor in the Computer Science department at the University of Texas at Dallas, where he has been teaching and conducting research since September 2000. He received his Ph.D. in Computer Science from the University of Southern California in August of 2000.  Dr. Khan is an Association for Computing Machinery

Distinguished Scientist and received Institute of Electrical and Electronics Engineers (IEEE)

Big Data Security Senior Research Award in May 2019, and the Society of Information Reuse and Integration award in August 2018. He has received prestigious awards including the IEEE Technical Achievement Award for Intelligence and Security Informatics and IBM Faculty Award (research) 2016. Recently, he has become a Fellow of British Computer Society, and Institution of Engineering and Technology.

More details can be found at: www.utdallas.edu/~lkhan/

Last Updated: December 8, 2021 - 7:38 am