Now showing items 1-14 of 14

    • Acquiring and Aggregating Information from Strategic Sources 

      Waggoner, Bo (2016-07-28)
      This thesis considers, from a theoretical perspective, the design of mechanisms to accomplish the objective described in the title. Two cases of this problem are considered: information as represented by data points in a ...
    • Bayesian Methods for Discovering Structure in Neural Spike Trains 

      Linderman, Scott Warren (2016-05-18)
      Neuroscience is entering an exciting new age. Modern recording technologies enable simultaneous measurements of thousands of neurons in organisms performing complex behaviors. Such recordings offer an unprecedented opportunity ...
    • Design and Modeling of Specialized Architectures 

      Shao, Yakun (2016-05-19)
      Hardware acceleration in the form of customized datapath and control circuitry tuned to specific applications has gained popularity for its promise to utilize transistors more efficiently. However, architectural research ...
    • Experimental Studies of Human Behavior in Social Computing Systems 

      Mao, Qiushi (2015-05-18)
      Social computing systems, fueled by the ability of the Internet to engage millions of individuals, have redefined computation to include not only the application of algorithms but also the participation of people. Yet, the ...
    • Extensible Proof Engineering in Intensional Type Theory 

      Malecha, Gregory (2015-02-24)
      We increasingly rely on large, complex systems in our daily lives---from the computers that park our cars to the medical devices that regulate insulin levels to the servers that store our personal information in the cloud. ...
    • A Foundational Proof Framework for Cryptography 

      Petcher, Adam (2015-05-18)
      I present a state-of-the-art mechanized framework for developing and checking proofs of security for cryptographic schemes in the computational model. This system, called the Foundational Cryptography Framework (FCF) is ...
    • Gradient Descent for Optimization Problems With Sparse Solutions 

      Chen, Hsieh-Chung (2016-05-18)
      Sparse modeling is central to many machine learning and signal processing algorithms, because finding a parsimonious model often implicitly removes noise and reveals structure in data. They appear in applications such as ...
    • Incentives Design in the Presence of Externalities 

      Rao, Malvika (2015-09-23)
      The design of incentives becomes challenging when faced with externalities. In this thesis I resolve this difficulty in two settings: position auctions and software economies. The first part of the thesis studies value ...
    • Making Peer Prediction Practical 

      Shnayder, Victor (2016-07-13)
      My dissertation is on crowdsourcing---using crowds of people to accomplish tasks that are impractical or far more expensive otherwise. I focus specifically on crowdsourcing of information, where workers do tasks such as ...
    • New Separations in the Complexity of Differential Privacy 

      Bun, Mark Mar (2016-08-03)
      In this thesis, we study when algorithmic tasks can be performed on sensitive data while protecting the privacy of individuals whose information is collected. We focus on the notion of differential privacy, which gives a ...
    • Precise Scalable Static Analysis for Application-Specific Security Guarantees 

      Johnson, Andrew Arthur (2015-08-27)
      This dissertation presents Pidgin, a static program analysis and understanding tool that enables the specification and enforcement of precise application-specific information security guarantees. Pidgin also allows developers ...
    • Software Contracts for Security 

      Moore, Scott David (2016-08-11)
      Component-based software engineering facilitates the design of complex systems by subdividing the programming task into separate components that interact via clearly defined interfaces. A component-based system is correct ...
    • Sparse Robust Recovery and Learning 

      Gwon, Youngjune Lee (2015-05-18)
      Sparse linear models pose dual views toward data that are embodied in compressive sensing and sparse coding. Despite mathematical equivalence, compressive sensing and sparse coding are two different classes of application ...
    • Upper and Lower Bounds for Privacy and Adaptivity in Algorithmic Data Analysis 

      Steinke, Thomas Alexander (2016-08-03)
      The increasing collection and use of sensitive personal data raises important privacy concerns. Another concern arising from the use of data in empirical sciences is the danger of producing results that are not statistically ...