Now showing items 497-516 of 775

    • 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 ...
    • The Order Independence of Iterated Dominance in Extensive Games, with Connections to Mechanism Design and Backward Induction 

      Chen, Jing; Micali, Silvio (2012-07-31)
      Shimoji and Watson (1998) prove that a strategy of an extensive game is rationalizable in the sense of Pearce if and only if it survives the maximal elimination of conditionally dominated strategies. Briefly, this process ...
    • Organic Indoor Location Discovery 

      Hicks, Jamey; Curtis, Dorothy; Teller, Seth; Charrow, Ben; Ryan, Russell; e.a. (2008-12-30)
      We describe an indoor, room-level location discovery method based on spatial variations in "wifi signatures," i.e., MAC addresses and signal strengths of existing wireless access points. The principal novelty of our system ...
    • Organon: A Symbolic Constraint Framework & Solver 

      Evans, Isaac; Lynch, Joseph (2013-05-24)
      Organon is an open source system for expressing and solving complex symbolic constraints between generic entities. Our design avoids restricting the programmer s ability to phrase constraints; Organon acts purely as a ...
    • Outlier Detection in Heterogeneous Datasets using Automatic Tuple Expansion 

      Pit-Claudel, Clément; Mariet, Zelda; Harding, Rachael; Madden, Sam (2016-02-08)
      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 ...
    • Overcoming the Antennas-Per-Node Throughput Limit in MIMO LANs 

      Perli, Samuel David; Gollakota, Shyamnath; Katabi, Dina (2009-02-18)
      Today, the number of concurrent packets in a MIMO LAN is limited by the number of antennas on the AP. This paper shows how to overcome this limit. It presents a new design where multiple client-AP pairs can communicate ...