ECE Seminar: Succinct and Assured Deep Learning: Training and Execution
Tuesday, November 13, 2018 - 12:00pm to 1:00pm
Bita Rouhani, a research scientist at Microsoft Research
One of the key challenges facing wide-scale adoption of Deep Learning (DL) is making the existing models more scalable, resource efficient, and reliable. This challenge is especially apparent on embedded edge devices where memory storage, battery life, and communication bandwidth are limited. A recent popular line of research has focused on performance optimization and DL acceleration using hardware and software co-design to address the scalability and resource efficiency issues. Reliability (safety) consideration is usually an afterthought if considered at all. My research work advances the state-of-the-art in this growing field by advocating a holistic co-design approach which not only includes hardware and software but also considers the geometry of the data, the learning model, as well as safety concerns (e.g., robustness against adversarial attacks and intellectual property infringement).