Past Events

Anonymous messaging platforms, such as Secret, Whisper and Yik Yak, have emerged as important social media for sharing one's thoughts without the fear of being judged by friends, family, or the public. Further, such anonymous platforms are crucial in nations with authoritarian governments, where the right to free expression and sometimes the personal safety of the message author depends on anonymity.

Modern datasets are rapidly growing in size and complexity, and this wealth of data holds the promise for many transformational applications. Machine learning is seemingly poised to deliver on this promise, having proposed and rigorously evaluated a wide range of data processing techniques over the past several decades. However, concerns over scalability and usability present major roadblocks to the wider adoption of these methods.

Hosted by the Department of Mathematics and the Wireless Networking and Communications Group (WNCG) at the University of Texas at Austin, the Simons Conference brings together a diverse set of world-class researchers from various scientific communities to foster interdisciplinary engagement.

A fundamental problem in Markov Chains is estimating the probability of transitioning to a given terminal state in k steps from some initial distribution. This has received added attention in recent years due to the success of PageRank and related Markov-Chain based centrality measures for networks. Standard approaches to this problem use linear-algebraic methods (power iteration) or Monte Carlo.

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.