WNCG Prof. Robert Heath discusses Millimeter Wave for 5G in this 20 minute video from his talk at the Texas Wireless Summit 2015: The View to 5G.
Miss your chance to attend Texas Wireless Summit 2015: The View to 5G? Now you can watch the entire event online, courtesy of TWS 2015 media sponsor, RCR Wireless.
Hosted by the University of Texas at Austin’s Wireless Networking and Communications Group (WNCG), the 13th annual Texas Wireless Summit (TWS) offered direct access to cutting-edge research and innovations from industry leaders, investors, academics and startups. This year’s theme was The View to 5G: From Applications to the Air Interface.
The keynote speakers included Gerhard Fettweis and Tom Marzetta, from TU Dresden and Alcatel-Lucent Bell Labs, respectively.
Additional speakers included: Amitava Ghosh (Nokia Networks), Anthony Soong (Huawei), Arun Ghosh (AT&T Labs), Brian Modoff (Qualcomm), Charlie Zhang (Samsung Research America), Eduardo Esteves (Qualcomm), Erik Dahlman (Ericsson), Farooq Khan (Samsung Research America), Ian Wong (National Instruments), Mike Barrick (Anritsu), Nihar Jindal (Google), Gaurav Bansal (Toyota), Theodore Rappaport (NYU Wireless), Vinko Erceg (Broadcom), and Xinzhou Wu (Qualcomm).
To watch the full event online, visit: https://www.youtube.com/playlist?list=PLwHfYh9uobIvYyS2sp6Gm5DbxYbaSZDo_
Abstract: Sampling is a standard approach to big graph analytics. But a good sample need to represent graph properties of interest with a known degree of accuracy. This talk describes a generic tunable sampling framework, graph sample and hold, that applies to graph stream sampling in which edges are presented one at a time, and from which unbiased estimators of graph properties can be produced in post-processing. The talk also describes the performance of the method on various types of graph, including social graphs, amongst others.
Speaker Bio: Nick Duffield is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University. From 2013 until 2014, he was a Research Professor at DIMACS (the Center for Discrete Mathematics and Theoretical Computer Science) at Rutgers University, New Jersey, USA. From 1995 until 2013, he worked at AT&T Labs-Research where he was a Distinguished Member of Technical Staff and an AT&T Fellow.
Prof. Duffield works on the acquisition, analysis and applications of Big Data to communication networks and beyond.
We consider the task of summing (integrating) a non-negative function over a discrete domain, e.g., to compute the partition function of a graphical model. It is known that in a probabilistic approximate sense, summation can be reduced to maximization over random subsets of the domain defined by systems of linear equations modulo 2 (parity constraints). Unfortunately, random parity constraints with many variables are computationally intractable, while random parity constraints with few variables have poor statistical performance.
Speaker Bio: Dimitris Achlioptas joined the Department of Computer Science of UC Santa Cruz in 2006, following his Ph.D. from the University of Toronto and a 7 year stint at Microsoft Research, Redmond. In theory, his expertise lies in the interaction between randomness and computation and his work on that topic has appeared in journals including Nature, Science, and the Annals of Mathematics. For that work has received an NSF CAREER award, a Sloan Fellowship, and an ERC Starting Grant. In practice, he likes to think about scalability questions and holds over twenty US patents on topics ranging from load balancing and cache optimization to web search personalization.