Past Events

Video is a booming industry: content is embedded on many Web sites, delivered over the Internet, and streamed to mobile devices. Cisco statistics indicate that mobile video traffic exceeded 50% for the first time in 2012, and two-thirds of the world’s mobile data traffic will be video by 2017. This has produced a need for objective video quality metrics. The different approaches will be introduced and summarized, and the advantages and disadvantages identified. Research opportunities will be mentioned.

The problem of multiple hypothesis testing with observation control is considered in the sequential setting.  In the case of uniform sensing cost, a test based on earlier work by Chernoff for binary hypothesis testing is shown to be first-order asymptotically optimal for multihypothesis testing in a strong sense, using the notion of decision making risk in place of the overall probability of error.  Then, a new model for controlled sensing for sequential multihypothesis testing is proposed.  This new model generalizes the existing model in two aspects.

Crowdsourcing systems, like Amazon Mechanical Turk, provide platforms where large-scale projects are broken into small tasks that are electronically distributed to numerous on-demand contributors. Because these low-paid workers can be unreliable, we need to devise schemes to increase confidence in our answers, typically by assigning each task multiple times and combining the answers in some way.

We study auction-theoretic scheduling in cellular networks using the idea of a mean field equilibrium (MFE). Here, agents model their opponents through an assumed distribution over their action spaces, and play the best response action against this distribution. We say that the system is at MFE if this best response action turns out to be a sample drawn from the assumed distribution. In our setting, the agents are smartphone apps that generate service requests, have costs associated with waiting, and bid against each other for service from base stations.

Network bandwidth consumption is projected to accelerate as CE and mobile devices provisioned with network connectivity continue to evolve with diminishing silicon geometries and the advent of multi-core architectures. In particular, these technology advancements extend the benefits of lower power consumption and higher processing capabilities that enable consumers with the means to access or send video content via the network anywhere at any time.

Lattice coding has emerged as a fundamental theoretical tool in the Information Theory of Gaussian networks.

Many challenges arise in the operations management of service systems with uncertain time-varying arrivals, non-exponential service and patience times, and complex network structures. Stochastic offered load processes have been shown to provide useful insights in capacity planning and performance analysis of large-scale service systems. In this talk, we focus on stochastic offered load processes in non-Markovian many-server queueing systems with dependence among interarrival times and among service times.

The problem of high-dimensional function estimation is discussed including the need for joint consideration of issues of approximation, estimation and computation, and the role of information theory in understanding the relationships.  Flexible accurate function modeling arises by allowance of arbitrary order interactions among explanatory variables or by allowance of general ridge basis expansions.  However, the number of candidate basis functions becomes exponentially large in the number of variables, more than can be feasibly computed by standard greedy basis search algorithms.

Effective Big Data management and analysis poses several difficult challenges for modern database architectures. One key such challenge arises from the naturally streaming nature of big data, which mandates efficient algorithms for querying and analyzing massive, continuous data streams (that is, data that is seen only once and in a fixed order) with limited memory and CPU-time resources.

In recent years, there has been rapid progress on understanding Gaussian networks with multiple unicast connections and new coding techniques have emerged. The essence of multi-source networks is how to efficiently mitigate interference from the transmission of other sessions. Recently discovered interference alignment has led to a paradigm shift that interference might not be quite as detrimental after all. For multi-source Gaussian relay networks, interference cannot only be aligned, it can also be cancelled through multiple channel paths called interference neutralization.