Abstract: This talk focuses on connections between relatively recent notions and variants of the Information Bottleneck and classical information theoretic frameworks such as: Remote Source-Coding; Information Combining; Common Reconstruction; The Wyner-Ahlswede-Korner Problem; The Efficiency of Investment Information; CEO Source Coding under Log-Loss and others. We overview the upink Cloud Radio Access Networks (CRAN) with oblivious processing, which is an attractive model for future wireless systems
- Tue, Feb 11, 2020, 4:30 pm to 5:30 pm
- Thu, Jan 9, 2020, 9:00 am to 11:30 am
- Mon, Dec 16, 2019, 10:00 am to 11:30 am
- Mon, Dec 9, 2019, 3:30 pm to 4:30 pm
Power and energy have become primary design constraints for modern processors. Power no longer scales with transistor channel length, causing power density to increase. Continued transistor scaling will require prohibitively expensive cooling technologies. This is particularly an issue in data centers, where the cost of power and cooling has a major impact on the total cost of ownership. Data centers have grown and expanded rapidly due to the advent of cloud computing and interactive web services.
- Fri, Dec 6, 2019, 11:30 am to 12:30 pm
- Mon, Dec 9, 2019, 4:30 pm to 5:30 pm
- Tue, Nov 5, 2019, 4:30 pm to 5:30 pm
Abstract: Integrated electronic-photonic co-design can profoundly impact both fields resulting in advances in several areas such as energy efficient communication, signal processing, imaging, and sensing.
- Thu, Dec 12, 2019, 3:00 pm to 4:00 pm
How to conduct real-time analytics of streaming measurement data in the power grid? This talk offers a dynamic systems approach to utilizing data of different time scale for improved monitoring of the grid cyber and physical security. This talk presents how to leverage synchrophasor data dimensionality reduction and Robust Principal Component Analysis for early anomaly detection, visualization, and localization. The underlying theme of the work suggests the importance of integrating data with dynamic physical models in the smart grid.
- Mon, Nov 18, 2019, 4:30 pm to 5:30 pm
We consider a class of distributed non-convex optimization problems, in which a number of agents are connected by a communication network, and they collectively optimize a sum of (possibly non-convex and non-smooth) local objective functions. This type of problem has gained some recent popularities, especially in the application of distributed training of deep neural networks.
- Fri, Nov 8, 2019, 12:30 pm to 1:30 pm