Past Events

Due to the privacy concerns of existing centralized Online Social Networks (OSN),  researchers and developers have tried to design, implement and deploy decentralized social networks (DSN) in  recent years. Despite numerous attempts and efforts, only a small portion of those projects have managed to achieve actual deployment status and none but one of them have more than one million users.

Join CalTech's Dr. Quentin Berthet in this one-hour seminar. We study the detection problem of finding planted solutions in random instances of flat satisfiability problems, a generalization of boolean satisfiability formulas. We describe the properties of random instances of flat satisfiability, as well of the optimal rates of detection of the associated hypothesis testing problem. We also study the performance of an algorithmically efficient testing procedure.

ISPLC has been running annually since 1997 as a worldwide forum for communications researchers and engineers to discuss issues relating to the use of electrical power distribution cables as a viable communication channel. An international meeting point for academics and industrial researchers as well as regulators, ISPLC now is the leading technical conference in the field of Power Line Communications (PLC) and the flagship event of the IEEE PLC Technical Committee.

WiFi has become the connection of choice (when available) for many users. For that reason, many operators have embraced WiFi as another radio access technology that eventually will be integrated to the network. In this talk we study concurrent user associations on the uplink of the OFDMA and CSMA  heterogeneous networks. Where user equipments assumed to have multi-homing capabilities.

The brain is simultaneously a biological object and a computing machine that represents and stores information about the external world, computes with this information, and generates adaptive behaviors in the world. Modern neuroscience is bringing sophisticated tools to observe neural codes. Our actual understanding of these codes is at a nascent stage, and opportunities to understand how the brain codes information and why it does so the way is does, abound. I'll talk about some fascinating neural codes and our work to theoretically analyze these codes.

Title: Towards a Mobile Content Marketplace: Proactive Caching and Pricing Strategies To view presentation slides from the day's event, view the PDF file.

Many emerging applications of machine learning involve time series and spatio-temporal data. In this talk, I will discuss a collection of machine learning approaches to effectively analyze and model large-scale time series and spatio-temporal data, including temporal causal models, sparse extreme-value models, and fast tensor-based forecasting models. Experiment results will be shown to demonstrate the effectiveness of our models in climate science and healthcare applications.

Millimeter wave wireless propagation and communications system design

In this talk, I will present two recent results in random matrix theory. In the first part of the talk, I will present a result that leads to analyzing the required number of labeled examples (also known as label complexity) of graph-based methods for semi-supervised learning. Graph-based methods have been quite successful in solving the semi-supervised learning problem, as they take into account the underlying geometry of the data.

Rate splitting and iterative decoding approaches for fading channels with imperfect CSI