Now showing items 483-502 of 763

    • On the Non-Existence of Blockwise 2-Local PRGs with Applications to Indistinguishability Obfuscation 

      Lombardi, Alex; Vaikuntanathan, Vinod (2017-04-06)
      Lin and Tessaro (Eprint 2017/250) recently proposed indistinguishability obfuscation and functional encryption candidates and proved their security based on a standard assumption on bilinear maps and a non-standard assumption ...
    • On Using First-Order Theorem Provers in the Jahob Data Structure Verification System 

      Bouillaguet, Charles; Kuncak, Viktor; Wies, Thomas; Zee, Karen; Rinard, Martin (2006-11-09)
      This paper presents our integration of efficient resolution-based theorem provers into the Jahob data structure verification system. Our experimental results show that this approach enables Jahob to automatically ...
    • On Verifying a File System Implementation 

      Arkoudas, Konstantine; Zee, Karen; Kuncak, Viktor; Rinard, Martin (2004-05-06)
      We present a correctness proof for a basic file system implementation. This implementation contains key elements of standard Unix file systems such as inodes and fixed-size disk blocks. We prove the implementation correct ...
    • One Clock to Rule Them All: A Primitive for Distributed Wireless Protocols at the Physical Layer 

      Abari, Omid; Rahul, Hariharan; Katabi, Dina (2014-04-27)
      Implementing distributed wireless protocols at the physical layer today is challenging because different nodes have different clocks, each of which has slightly different frequencies. This causes the nodes to have frequency ...
    • One Video Stream to Serve Diverse Receivers 

      Woo, Grace; Katabi, Dina; Chachulski, Szymon (2008-10-18)
      The fundamental problem of wireless video multicast is to scalably serve multiple receivers which may have very different channel characteristics. Ideally, one would like to broadcast a single stream that allows each ...
    • One-Shot Learning with a Hierarchical Nonparametric Bayesian Model 

      Salakhutdinov, Ruslan; Tenenbaum, Josh; Torralba, Antonio (2010-10-13)
      We develop a hierarchical Bayesian model that learns to learn categories from single training examples. The model transfers acquired knowledge from previously learned categories to a novel category, in the form of a prior ...
    • Online Active Learning in Practice 

      Monteleoni, Claire; Kaariainen, Matti (2007-01-23)
      We compare the practical performance of several recently proposed algorithms for active learning in the online setting. We consider two algorithms (and their combined variants) that are strongly online, in that they do ...
    • Online Learning of Non-stationary Sequences 

      Monteleoni, Claire; Jaakkola, Tommi (2005-11-17)
      We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a class of universal learning algorithms involving ...
    • Oort: User-Centric Cloud Storage with Global Queries 

      Chajed, Tej; Gjengset, Jon; Kaashoek, M. Frans; Mickens, James; Morris, Robert; e.a. (2016-12-08)
      In principle, the web should provide the perfect stage for user-generated content, allowing users to share their data seamlessly with other users across services and applications. In practice, the web fragments a user's ...
    • OpenTuner: An Extensible Framework for Program Autotuning 

      Ansel, Jason; Kamil, Shoaib; Veeramachaneni, Kalyan; O'Reilly, Una-May; Amarasinghe, Saman (2013-11-01)
      Program autotuning has been shown to achieve better or more portable performance in a number of domains. However, autotuners themselves are rarely portable between projects, for a number of reasons: using a domain-informed ...
    • An Operating System for Multicore and Clouds: Mechanisms and Implementation 

      Modzelewski, Kevin; Miller, Jason; Belay, Adam; Beckmann, Nathan; Gruenwald, Charles, III; e.a. (2010-02-08)
      Cloud computers and multicore processors are two emerging classes of computational hardware that have the potential to provide unprecedented compute capacity to the average user. In order for the user to effectively harness ...
    • OpLog: a library for scaling update-heavy data structures 

      Boyd-Wickizer, Silas; Kaashoek, M. Frans; Morris, Robert; Zeldovich, Nickolai (2014-09-16)
      Existing techniques (e.g., RCU) can achieve good multi-core scaling for read-mostly data, but for update-heavy data structures only special-purpose techniques exist. This paper presents OpLog, a general-purpose library ...
    • Optimal and Player-Replaceable Consensus with an Honest Majority 

      Micali, Silvio; Vaikuntanathan, Vinod (2017-03-31)
      We construct a Byzantine Agreement protocol that tolerates t < n/2 corruptions, is very efficient in terms of the number of rounds and the number of bits of communication, and satisfies a strong notion of robustness called ...
    • Optimal Approximations of the Frequency Moments 

      Indyk, Piotr; Woodruff, David (2004-07-02)
      We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data stream for any real k>2. Together with known lower bounds, this resolves the main problem left open by Alon, Matias, ...
    • Optimal Bidirectional Rapidly-Exploring Random Trees 

      Jordan, Matthew; Perez, Alejandro (2013-08-15)
      In this paper we present a simple, computationally-efficient, two-tree variant of the RRT* algorithm along with several heuristics.
    • Optimal Parametric Auctions 

      Azar, Pablo; Micali, Silvio (2012-05-08)
      We study the problem of profit maximization in auctions of one good where the buyers' valuations are drawn from independent distributions. When these distributions are known to the seller, Myerson's optimal auction is a ...
    • Optimal Parametric Auctions 

      Azar, Pablo Daniel; Micali, Silvio (2012-06-14)
      We study the problem of an auctioneer who wants to maximize her profits. In our model, there are n buyers with private valuations drawn from independent distributions F_1,...,F_n. When these distributions are known to the ...
    • Optimal Rates for Regularization Operators in Learning Theory 

      Caponnetto, Andrea (2006-09-10)
      We develop some new error bounds for learning algorithms induced by regularization methods in the regression setting. The "hardness" of the problem is characterized in terms of the parameters r and s, the first related ...
    • Optimal Temporal Planning at Reactive Time Scales via Dynamic Backtracking Branch and Bound 

      Effinger, Robert (2006-08-25)
      Autonomous robots are being considered for increasingly capable roles in our society, such as urban search and rescue, automation for assisted living, and lunar habitat construction. To fulfill these roles, teams of ...
    • Optimizing MapReduce for Multicore Architectures 

      Kaashoek, Frans; Morris, Robert; Mao, Yandong (2010-05-02)
      MapReduce is a programming model for data-parallel programs originally intended for data centers. MapReduce simplifies parallel programming, hiding synchronization and task management. These properties make it a promising ...