Now showing items 711-730 of 775

    • Tracking 3-D Rotations with the Quaternion Bingham Filter 

      Glover, Jared; Kaelbling, Leslie Pack (2013-03-27)
      A deterministic method for sequential estimation of 3-D rotations is presented. The Bingham distribution is used to represent uncertainty directly on the unit quaternion hypersphere. Quaternions avoid the degeneracies of ...
    • Trading Structure for Randomness in Wireless Opportunistic Routing 

      Chachulski, Szymon; Jennings, Michael; Katti, Sachin; Katabi, Dina (2007-02-23)
      Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on ...
    • Tragedy of the routing table: An analysis of collective action amongst Internet network operators 

      Woodrow, Stephen Robert (2011-08-06)
      This thesis analyzes and discusses the effectiveness of social efforts to achieve collective action amongst Internet network operators in order to manage the growth of the Internet routing table. The size and rate of growth ...
    • Trajectory Analysis and Semantic Region Modeling Using A Nonparametric Bayesian Model 

      Grimson, Eric; Wang, Xiaogang; Ng, Gee-Wah; Ma, Keng Teck (2008-06-24)
      We propose a novel nonparametric Bayesian model, Dual Hierarchical Dirichlet Processes (Dual-HDP), for trajectory analysis and semantic region modeling in surveillance settings, in an unsupervised way. In our approach, ...
    • Transductive Ranking on Graphs 

      Agarwal, Shivani (2008-08-07)
      In ranking, one is given examples of order relationships among objects, and the goal is to learn from these examples a real-valued ranking function that induces a ranking or ordering over the object space. We consider the ...
    • Transfer learning for image classification with sparse prototype representations 

      Quattoni, Ariadna; Collins, Michael; Darrell, Trevor (2008-03-03)
      To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful.  We develop a new method for transfer learning which exploits available unlabeled ...
    • Transfering Nonlinear Representations using Gaussian Processes with a Shared Latent Space 

      Urtasun, Raquel; Quattoni, Ariadna; Darrell, Trevor (2007-11-06)
      When a series of problems are related, representations derived fromlearning earlier tasks may be useful in solving later problems. Inthis paper we propose a novel approach to transfer learning withlow-dimensional, non-linear ...
    • Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space 

      Urtasun, Raquel; Quattoni, Ariadna; Lawrence, Neil; Darrell, Trevor (2008-04-11)
      When a series of problems are related, representations derived from learning earlier tasks may be useful in solving later problems. In this paper we propose a novel approach to transfer learning with low-dimensional, ...
    • Transparent Accountable Data Mining: New Strategies for Privacy Protection 

      Weitzner, Daniel J.; Abelson, Harold; Berners-Lee, Tim; Hanson, Chris; Hendler, James; e.a. (2006-01-27)
      Attempts to address issues of personal privacy in a world of computerized databases and information networks -- from security technology to data protection regulation to Fourth Amendment law jurisprudence -- typically ...
    • A Tree-Based Context Model for Object Recognition 

      Choi, Myung Jin; Lim, Joseph J.; Torralba, Antonio; Willsky, Alan S. (2010-10-29)
      There has been a growing interest in exploiting contextual information in addition to local features to detect and localize multiple object categories in an image. A context model can rule out some unlikely combinations ...
    • A (Truly) Local Broadcast Layer for Unreliable Radio Networks 

      Lynch, Nancy; Newport, Calvin (2015-05-18)
      In this paper, we implement an efficient local broadcast service for the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Our local broadcast service offers ...
    • Two-stage Optimization Approach to Robust Model Predictive Control with a Joint Chance Constraint 

      Ono, Masahiro; Williams, Brian C. (2008-03-06)
      When controlling dynamic systems such as mobile robots in uncertain environments, there is a trade off between risk and reward. For example, a race car can turn a corner faster by taking a more challenging path. This paper ...
    • Typesafety for Explicitly-Coded Probabilistic Inference Procedures 

      Atkinson, Eric; Carbin, Michael (2017-11-09)
      Researchers have recently proposed several systems that ease the process of developing Bayesian probabilistic inference algorithms. These include systems for automatic inference algorithm synthesis as well as stronger ...
    • Ubiquitous Memory Introspection (Preliminary Manuscript) 

      Zhao, Qin; Rabbah, Rodric; Amarasinghe, Saman; Rudolph, Larry; Wong, Weng-Fai (2006-09-25)
      Modern memory systems play a critical role in the performance ofapplications, but a detailed understanding of the application behaviorin the memory system is not trivial to attain. It requires timeconsuming simulations of ...
    • Ultra-fast Object Recognition from Few Spikes 

      Hung, Chou; Kreiman, Gabriel; Poggio, Tomaso; DiCarlo, James J. (2005-07-06)
      Understanding the complex brain computations leading to object recognition requires quantitatively characterizing the information represented in inferior temporal cortex (IT), the highest stage of the primate visual stream. ...
    • Understanding and evaluating blind deconvolution algorithms 

      Freeman, William; Durand, Fredo; Weiss, Yair; Levin, Anat (2009-03-31)
      Blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of the problem remain challenging and hard to ...
    • Understanding and Supporting Directed Content Sharing on the Web 

      Miller, Rob; Karger, David; Marcus, Adam; Bernstein, Michael (2009-10-07)
      To find interesting, personally relevant web content, we often rely on friends and colleagues to pass links along as they encounter them. In this paper, we study and augment link-sharing via e-mail, the most popular means ...
    • Understanding camera trade-offs through a Bayesian analysis of light field projections 

      Levin, Anat; Freeman, William T.; Durand, Fredo (2008-04-16)
      Computer vision has traditionally focused on extracting structure,such as depth, from images acquired using thin-lens or pinhole optics. The development of computational imaging is broadening this scope; a variety of ...
    • Understanding camera trade-offs through a Bayesian analysis of light field projections - A revision 

      Levin, Anat; Freeman, William; Durand, Fredo (2008-07-28)
      Computer vision has traditionally focused on extracting structure,such as depth, from images acquired using thin-lens or pinholeoptics. The development of computational imaging is broadening thisscope; a variety of ...
    • A Unified Operating System for Clouds and Manycore: fos 

      Modzelewski, Kevin; Miller, Jason; Belay, Adam; Beckmann, Nathan; Gruenwald, Charles, III; e.a. (2009-11-20)
      Single chip processors with thousands of cores will be available in the next ten years and clouds of multicore processors afford the operating system designer thousands of cores today. Constructing operating systems for ...