Now showing items 356-375 of 763

    • Keeping Mobile Robots Connected 

      Lynch, Nancy; Ley-Wild, Ruy; Kuhn, Fabian; Cornejo, Alejandro (2009-06-17)
      Designing robust algorithms for mobile agents with reliable communication is difficult due to the distributed nature of computation, in mobile ad hoc networks (MANETs) the matter is exacerbated by the need to ensure ...
    • Kernels for Vector-Valued Functions: a Review 

      Alvarez, Mauricio A.; Rosasco, Lorenzo; Lawrence, Neil D. (2011-06-30)
      Kernel methods are among the most popular techniques in machine learning. From a frequentist/discriminative perspective they play a central role in regularization theory as they provide a natural choice for the hypotheses ...
    • Keys Under Doormats: Mandating insecurity by requiring government access to all data and communications 

      Abelson, Harold; Anderson, Ross; Bellovin, Steven M.; Benaloh, Josh; Blaze, Matt; e.a. (2015-07-06)
      Twenty years ago, law enforcement organizations lobbied to require data and communication services to engineer their products to guarantee law enforcement access to all data. After lengthy debate and vigorous predictions ...
    • Kintinuous: Spatially Extended KinectFusion 

      Whelan, Thomas; Kaess, Michael; Fallon, Maurice; Johannsson, Hordur; Leonard, John; e.a. (2012-07-19)
      In this paper we present an extension to the KinectFusion algorithm that permits dense mesh-based mapping of extended scale environments in real-time. This is achieved through (i) altering the original algorithm such that ...
    • Knowledge Benchmarks in Adversarial Mechanism Design (Part I) and Implementation in Surviving Strategies (Part I) 

      Chen, Jing; Micali, Silvio (2008-07)
      We put forward new benchmarks and solution concepts for Adversarial Mechanism Design, as defined by [MV07.a], and we exemplify them in the case of truly combinatorial auctions.We benchmark the combined performance (the sum ...
    • Knowledge Benchmarks in Adversarial Mechanism Design and Implementation in Surviving Strategies (Part I) 

      Chen, Jing; Micali, Silvio (2008-06)
      We put forward new benchmarks and solution concepts for Adversarial Mechanism Design, as defined by [MV07.a], and we exemplify them in the case of truly combinatorial auctions.We benchmark the combined performance (the sum ...
    • Knowledge Flow Analysis for Security Protocols 

      Torlak, Emina; van Dijk, Marten; Gassend, Blaise; Jackson, Daniel; Devadas, Srinivas (2005-10-19)
      Knowledge flow analysis offers a simple and flexible way to find flaws in security protocols. A protocol is described by a collection of rules constraining the propagation of knowledge amongst principals. Because this ...
    • Kongming: A Generative Planner for Hybrid Systems with Temporally Extended Goals 

      Li, Hui X. (2010-04-09)
      Most unmanned missions in space and undersea are commanded by a "script" that specifies a sequence of discrete commands and continuous actions. Currently such scripts are mostly hand-generated by human operators. This ...
    • LabelMe: a database and web-based tool for image annotation 

      Russell, Bryan C.; Torralba, Antonio; Murphy, Kevin P.; Freeman, William T. (2005-09-08)
      Research in object detection and recognition in cluttered scenes requires large image collections with ground truth labels. The labels should provide information about the object classes present in each image, as well as ...
    • Language and Compiler Support for Auto-Tuning Variable-Accuracy Algorithms 

      Ansel, Jason; Wong, Yee Lok; Chan, Cy; Olszewski, Marek; Edelman, Alan; e.a. (2010-07-27)
      Approximating ideal program outputs is a common technique for solving computationally difficult problems, for adhering to processing or timing constraints, and for performance optimization in situations where perfect ...
    • Latent Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification 

      Kim, Been; Rudin, Cynthia; Shah, Julie (2014-05-26)
      We present a general framework for Bayesian case-based reasoning and prototype classification and clustering -- Latent Case Model (LCM). LCM learns the most representative prototype observations of a dataset by performing ...
    • Latent-Dynamic Discriminative Models for Continuous Gesture Recognition 

      Morency, Louis-Philippe; Quattoni, Ariadna; Darrell, Trevor (2007-01-07)
      Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper we develop a discriminative framework for simultaneous sequence segmentation and labeling which can ...
    • Leader Election Using Loneliness Detection 

      Ghaffari, Mohsen; Lynch, Nancy; Sastry, Srikanth (2011-10-12)
      We consider the problem of leader election (LE) in single-hop radio networks with synchronized time slots for transmitting and receiving messages. We assume that the actual number n of processes is unknown, while the size ...
    • LEAP Scratchpads: Automatic Memory and Cache Management for Reconfigurable Logic [Extended Version] 

      Adler, Michael; Fleming, Kermin E.; Parashar, Angshuman; Pellauer, Michael; Emer, Joel (2010-11-23)
      Developers accelerating applications on FPGAs or other reconfigurable logic have nothing but raw memory devices in their standard toolkits. Each project typically includes tedious development of single-use memory management. ...
    • Learning a Dictionary of Shape-Components in Visual Cortex: Comparison with Neurons, Humans and Machines 

      Serre, Thomas (2006-04-25)
      In this thesis, I describe a quantitative model that accounts for the circuits and computations of the feedforward path of the ventral stream of visual cortex. This model is consistent with a general theory of visual ...
    • Learning and disrupting invariance in visual recognition 

      Isik, Leyla; Leibo, Joel Z; Poggio, Tomaso (2011-09-10)
      Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments ...
    • Learning and Invariance in a Family of Hierarchical Kernels 

      Wibisono, Andre; Bouvrie, Jake; Rosasco, Lorenzo; Poggio, Tomaso (2010-07-30)
      Understanding invariance and discrimination properties of hierarchical models is arguably the key to understanding how and why such models, of which the the mammalian visual system is one instance, can lead to good ...
    • Learning and recognition of hybrid manipulation tasks in variable environments using probabilistic flow tubes 

      Dong, Shuonan (2012-08-23)
      Robots can act as proxies for human operators in environments where a human operator is not present or cannot directly perform a task, such as in dangerous or remote situations. Teleoperation is a common interface for ...
    • Learning by Learning To Communicate 

      Beal, Jacob (2007-08-23)
      Human intelligence is a product of cooperation among many different specialists. Much of this cooperation must be learned, but we do not yet have a mechanism that explains how this might happen for the "high-level" agile ...
    • Learning Commonsense Categorical Knowledge in a Thread Memory System 

      Stamatoiu, Oana L. (2004-05-18)
      If we are to understand how we can build machines capable of broadpurpose learning and reasoning, we must first aim to build systemsthat can represent, acquire, and reason about the kinds of commonsenseknowledge that we ...