## SSS Abstracts |

In partial fulfillment of the CSD Speaking Skills Requirement.

Joint work with Ryan O'Donnell

In partial fulfillment of the CSD Speaking Skills Requirement.

Thus, we need a prediction model that is (a) expressive enough to capture these complex relationships and (b) capable of updating quality predictions in near real-time. Unfortunately, several seemingly natural solutions (e.g., simple machine learning approaches and simple network models) fail on one or more fronts. Thus, the potential benefits promised by these prior efforts remain unrealized.

We address these challenges and present the design and implementation of Critical Feature Analytics (CFA). The design of CFA is driven by domain-specific insights that video quality is typically determined by a small subset of critical features whose criticality persists over several tens of minutes. This enables a scalable and accurate workflow where we automatically learn critical features for different sessions on coarse-grained timescales, while updating quality predictions in near real-time. Using a combination of a real-world pilot deployment and trace-driven analysis, we demonstrate that CFA leads to significant improvements in video quality; e.g., 32% less buffering time and 12% higher bitrate than a random decision maker.

Joint work with Vyas Sekar, Hui Zhang, and Ion Stoica

In partial fulfillment of the CSD Speaking Skills Requirement.

Joint work with Frank Pfenning and Limin Jia

In partial fulfillment of the Speaking Requirement

Recently, Haeupler '14 showed that if an eps > 0 fraction of transmissions are corrupted, adversarially or randomly, then it is possible to achieve a communication rate of 1 - Õ(sqrt(eps)). Furthermore, Haeupler conjectured that this rate is optimal for general input protocols. This stands in contrast to the classical setting of one-way communication in which error-correcting codes are known to achieve an optimal communication rate of 1 - θ(H(eps)).

In this work, we show that the quadratically smaller rate loss of the one-way setting can also be achieved in interactive coding schemes for a very natural class of input protocols. We introduce the notion of average message length, or the average number of bits a party sends before receiving a reply, as a natural parameter for measuring the level of interactivity in a protocol. Moreover, we show that any protocol with average message length l = Ω(poly(1/eps)) can be simulated by a protocol with optimal communication rate 1 - Θ(H(eps)) over an oblivious adversarial channel with error fraction eps.

This shows that the capacity gap between one-way and interactive communication can be bridged even for very small (constant in eps) average message lengths, which are likely to be found in many applications.

This is based on joint work with Bernhard Haeupler.

In partial fulfillment of the Speaking Requirement.

Joint work with Maxim Likhachev.

In partial fulfillment of the Speaking Requirement.

Joint work with David Farrow, Sangwon Hyun, Shannon Gallagher, Roni Rosenfeld, and Ryan Tibshirani

In Partial Fulfillment of the Speaking Requirement

This work was presented as "Data Retention in MLC NAND Flash Memory: Characterization, Optimization, and Recovery" in the best paper session at HPCA 2015.

Joint work with Yu Cai, Erich F. Haratsch, Ken Mai, and Onur Mutlu

In partial fulfillment of the Speaking Requirement.