Now showing items 746-765 of 806

    • 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 ...
    • UCM/MIT Indications, Referring Expressions, and Coreference Corpus (UMIREC corpus) 

      Hervas, Raquel; Finlayson, Mark Alan (2010-05-12)
      This version of the UMIREC corpus has been superseded by version 1.1, found at http://hdl.handle.net/1721.1/57507. Please do not use version 1.0, as it contains corrupted coreference information. The correct, uncorrupted ...
    • UCM/MIT Indications, Referring Expressions, and Coreference Corpus (UMIREC corpus) v1.1 

      Finlayson, Mark Alan; Hervas, Raquel (2010-05-12)
      The corpus comprises 62 files in "Story Workbench" annotation format: 30 folktales in English from a variety of sources, and 32 Wall Street Journal articles selected to coincide with articles found in the Penn Treebank. ...
    • 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 ...
    • Understanding the Performance of Broadband Networks through the Statistical Analysis of Speed Tests - Supplemental materials 

      García, Rubén (2011-05-10)
      Supplemental materials for the master thesis "Understanding the Performance of Broadband Networks Through the Statistical Analysis of Speed Tests", by Rubén García, submitted in May 2011 for the S.M. in Technology and ...
    • 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 ...
    • Universal Motion Generator: Trajectory Autocompletion by Motion Prompts 

      Wang, Yanwei; Shah, Julie (2022-06-15)
      Foundation models, which are large neural networks trained on massive datasets, have shown impressive generalization in both the language and the vision domain. While fine-tuning foundation models for new tasks at test-time ...
    • Unsupervised Distributed Feature Selection for Multi-view Object Recognition 

      Christoudias, C. Mario; Urtasun, Raquel; Darrell, Trevor (2008-02-17)
      Object recognition accuracy can be improved when information frommultiple views is integrated, but information in each view can oftenbe highly redundant. We consider the problem of distributed objectrecognition or indexing ...
    • Unsupervised Learning and Recognition of Physical Activity Plans 

      Dong, Shuonan (2007-08-23)
      This thesis desires to enable a new kind of interaction between humans and computational agents, such as robots or computers, by allowing the agent to anticipate and adapt to human intent. In the future, more robots may ...
    • Updatable Zero-Knowledge Sets 

      Liskov, Moses; Milcali, Silvio (2003-10-14)
      We build on the work of Micali, Rabin, and Killian [4] to introduce zero-knowledge sets and databases that may be updated in a desirable way. In particular, in order to make an update the owner of the set must publish a ...