On March 30 & 31, 2015, an international group of twenty-three researchers with expertise in linguistic annotation convened in Sunny Isles Beach, Florida to discuss problems with and potential solutions for the state of ...

Alpenhorn is the first system for initiating an encrypted connection between two users that provides strong privacy and forward secrecy guarantees for metadata (i.e., information about which users connected to each other) ...

The problem we address in this thesis is to uncover the design elements in a network architecture design that may open it up to denial of service (DoS) attacks and to expose the tradeoffs in mitigating those DoS opportunities. ...

Rapid convergence to a desired allocation of network resources to endpoint traffic has been a long-standing challenge for packet-switched networks. The reason for this is that congestion control decisions are distributed ...

We present a new system, Genesis, that processes sets of human patches to automatically infer code transforms and search spaces for automatic patch generation. We present results that characterize the effectiveness of the ...

This thesis seeks to test and evaluate the effects of in-­network storage in novel proposed Internet architectures in terms of their performance. In a world where more and more people are mobile and connected to the Internet, ...

This project involves learning to predict users' mobility within the network topology. Topological mobility, as opposed to physical mobility, can be substantial as a user switches from LTE to wifi network, while moving ...

This thesis discusses novel principles to improve the theoretical analyses of a class of methods, aiming to provide theoretically driven yet practically useful methods. The thesis focuses on a class of methods, called ...

In this paper, we prove a conjecture published in 1989 and also partially address an open problem announced at the Conference on Learning Theory (COLT) 2015. For an expected loss function of a deep nonlinear neural network, ...

This paper presents Delphi, a mobile software controller that helps applications select the best network among available choices for their data transfers. Delphi optimizes a specified objective such as transfer completion ...

We present the first systematic analysis of the characteristics of patch search spaces for automatic patch generation systems. We analyze the search spaces of two current state-of- the-art systems, SPR and Prophet, with ...

Rapidly developing areas of information technology are generating massive amounts of data. Human errors, sensor failures, and other unforeseen circumstances unfortunately tend to undermine the quality and consistency of ...

There is a growing demand for data-driven web applications that help automate organizational and business processes of low to medium complexity by letting users view and update structured data in controlled ways. We present ...

We present a new language construct, filtered iterators, for safe and robust input processing. Filtered iterators are designed to eliminate many common input-processing errors while enabling robust continued execution. The ...

Conventional memory systems are organized as a rigid hierarchy, with multiple levels of progressively larger and slower memories. Hierarchy allows a simple, fixed design to benefit a wide range of applications, because ...

Much prior work has studied processor cache replacement policies, but a large gap remains between theory and practice. The optimal policy (MIN) requires unobtainable knowledge of the future, and prior theoretically-grounded ...

Caches are critical to performance, yet their behavior is hard to understand and model. In particular, prior work does not provide closed-form solutions of cache performance, i.e. simple expressions for the miss rate of a ...

This archive contains the supplementary material for the journal article "ProppLearner: Deeply Annotating a Corpus of Russian Folktales to Enable the Machine Learning of a Russian Formalist Theory", published in the Journal ...

Recent years have seen increased interest in non-parametric reinforcement learning. There are now practical kernel-based algorithms for approximating value functions; however, kernel regression requires that the underlying ...

In this paper, we present ForeCache, a general-purpose tool for exploratory browsing of large datasets. ForeCache utilizes a client-server architecture, where the user interacts with a lightweight client-side interface to ...