Provable Reinforcement Learning From Small Data
Fri, Oct 4, 2019, 4:30 pm to 5:30 pm
Abstract:
Seminars
Towards Learning with Brain Efficiency
Thu, Oct 17, 2019, 12:30 pm to 1:30 pmAbstract: Modern computing systems are plagued with significant issues in efficiently performing learning tasks. In this talk, I will present a new brain-inspired computing architecture. It supports a wide range of learning tasks while offering higher system efficiency than the other existing platforms. I will first focus on HyperDimensional (HD) computing, an alternative method of computation which exploits key principles of brain functionality: (i) robustness to noise/error and (ii) intertwined memory and logic.
Implantable Electronics for Highly Parallel Neural Interfaces
Tue, Oct 8, 2019, 4:30 pm to 5:30 pmAbstract: Implantable medical devices (IMD) are nowadays widely employed to restore functions to the impaired individuals suffering from diseases like deafness, blindness, cardiac insufficiency, incontinence, neural disorders, and many more. Such implantable systems become increasingly challenging, if a large number of sensing or stimulating sites needs to be realized - space and power budget, safety issues, high bidirectional data rates, as well as the vast number of electrical interfaces make the electronic circuit design a complex task of research and development.
Market Design for Peer-to-Peer Energy Trading and Distribution System Flexibility
Mon, Oct 28, 2019, 4:30 pm to 5:30 pmAbstract:
A Marauder's Map of Security and Privacy in Machine Learning
Thu, Oct 10, 2019, 4:30 pm to 5:30 pmAbstract:
Convergence Rates of Stochastic Algorithms in Nonsmooth Nonconvex Optimization
Thu, Nov 14, 2019, 4:30 pm to 5:30 pmAbstract:
Wireless Networks via the Cloud: An Information Theoretic View
Fri, Sep 6, 2019, 4:30 pm to 5:30 pmAbstract: Cloud based wireless networks named also as Cloud Radio Access Networks
(C-RANs) emerge as appealing architectures for next-generation wireless/cellular systems whereby the processing/encoding/decoding is migrated from the local base-stations/radio units (RUs) to a control/central units (CU) in the "cloud".
The network operates via fronthaul digital links connecting the CU and the RUs (operating as relays).
Beyond Supervised Learning for Biomedical Imaging
Wed, Oct 2, 2019, 4:30 pm to 5:30 pmAbstract:
Learning via Non-Convex Min-Max Games
Thu, Oct 17, 2019, 4:30 pm to 5:30 pmAbstract:
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