Now showing items 533-552 of 763

    • Practical Color-Based Motion Capture 

      Wang, Robert; Paris, Sylvain; Popovic, Jovan (2010-09-10)
      Motion capture systems have been widely used for high quality content creation and virtual reality but are rarely used in consumer applications due to their price and setup cost. In this paper, we propose a motion capture ...
    • Predicting Problems Caused by Component Upgrades 

      McCamant, Stephen; Ernst, Michael D. (2004-03-30)
      This report presents a new, automatic technique to assess whether replacing a component of a softwaresystem by a purportedly compatible component may change the behavior of the system. The techniqueoperates before integrating ...
    • Predicting the Risk and Trajectory of Intensive Care Patients Using Survival Models 

      Hug, Caleb W. (2006-08-30)
      Using artificial intelligence to assist physicians in patient care has received sustained interest over the past several decades. Recently, with automated systems at most bedsides, the amount of patient information collected ...
    • Predicting Unroll Factors Using Nearest Neighbors 

      Stephenson, Mark; Amarasinghe, Saman (2004-03-22)
      In order to deliver the promise of MooreÂ’s Law to the enduser, compilers must make decisions that are intimately tiedto a specific target architecture. As engineers add architecturalfeatures to increase performance, systems ...
    • Predictive identification of alternative events conserved in human and mouse 

      Yeo, Gene; Van Nostrand, Eric; Holste, Dirk; Poggio, Tomaso; Burge, Christopher (2004-09-30)
      Alternative pre-messenger RNA splicing affects a majority of human genes and plays important roles in development and disease. Alternative splicing (AS) events conserved since the divergence of human and mouse are likely ...
    • Preliminary MEG decoding results 

      Isik, Leyla; Meyers, Ethan M.; Leibo, Joel Z.; Poggio, Tomaso (2012-04-20)
      Decoding analysis has been applied to electrophysiology and fMRI data to study the visual system, however, this method has only been applied to MEG visual data in a few instances. Here we use the Neural Decoding Toolbox ...
    • Privacy and Security Risks for National Health Records Systems 

      Alawaji, Ahmed; Sollins, Karen (2018-01-24)
      A review of national health records (NEHR) systems shows that privacy and security risks have a profound impact on the success of such projects. Countries have different approaches when dealing with privacy and security ...
    • Probabilistic and Statistical Analysis of Perforated Patterns 

      Misailovic, Sasa; Roy, Daniel M.; Rinard, Martin (2011-01-19)
      We present a new foundation for the analysis and transformation of computer programs.Standard approaches involve the use of logical reasoning to prove that the applied transformation does not change the observable semantics ...
    • Programming a Sensor Network as an Amorphous Medium 

      Bachrach, Jonathan; Beal, Jacob (2006-06)
      In many sensor network applications, the network is deployedto approximate a physical space. The network itself is not ofinterest: rather, we are interested in measuring the propertiesof the space it fills, and of establishing ...
    • Programming an Amorphous Computational Medium 

      Beal, Jacob (2004-09)
      Amorphous computing considers the problem of controllingmillions of spatially distributed unreliable devices which communicateonly with nearby neighbors. To program such a system, we need a highleveldescription language ...
    • Programming Manifolds 

      Bachrach, Jonathan; Beal, Jacob (2007)
      Many programming domains involve the manipulation of values distributed through a manifold - examples include sensor networks, smart materials, and biofilms. This paper describes a programming semantics for manifolds based ...
    • A Projected Subgradient Method for Scalable Multi-Task Learning 

      Quattoni, Ariadna; Carreras, Xavier; Collins, Michael; Darrell, Trevor (2008-07-23)
      Recent approaches to multi-task learning have investigated the use of a variety of matrix norm regularization schemes for promoting feature sharing across tasks.In essence, these approaches aim at extending the l1 framework ...
    • Propagation Networks: A Flexible and Expressive Substrate for Computation 

      Radul, Alexey (2009-11-03)
      I propose a shift in the foundations of computation. Practically all ideas of general-purpose computation today are founded either on execution of sequences of atomic instructions, i.e., assembly languages, or on evaluation ...
    • Prophet: Automatic Patch Generation via Learning from Successful Human Patches 

      Long, Fan; Rinard, Martin (2015-05-26)
      We present Prophet, a novel patch generation system that learns a probabilistic model over candidate patches from a large code database that contains many past successful human patches. It defines the probabilistic model ...
    • Prophet: Automatic Patch Generation via Learning from Successful Patches 

      Long, Fan; Rinard, Martin (2015-07-13)
      We present Prophet, a novel patch generation system that learns a probabilistic model over candidate patches from a database of past successful patches. Prophet defines the probabilistic model as the combination of a ...
    • Propositional and Activity Monitoring Using Qualitative Spatial Reasoning 

      Lane, Spencer Dale (2016-12-14)
      Communication is the key to effective teamwork regardless of whether the team members are humans or machines. Much of the communication that makes human teams so effective is non-verbal; they are able to recognize the ...
    • Proving Atomicity: An Assertional Approach 

      Chockler, Gregory; Lynch, Nancy; Mitra, Sayan; Tauber, Joshua (2005-07-22)
      Atomicity (or linearizability) is a commonly used consistency criterion for distributed services and objects. Although atomic object implementations are abundant, proving that algorithms achieve atomicity has turned out ...
    • A Publish-Subscribe Implementation of Network Management 

      Simosa, Jorge D. (2013-06-04)
      As modern networks become highly integrated, heterogeneous, and experience exponential growth, the task of network management becomes increasingly unmanageable for network administrators and designers. The Knowledge Plane ...
    • Pyramid Match Kernels: Discriminative Classification with Sets of Image Features 

      Grauman, Kristen; Darrell, Trevor (2005-03-17)
      Discriminative learning is challenging when examples are setsof local image features, and the sets vary in cardinality and lackany sort of meaningful ordering. Kernel-based classificationmethods can learn complex decision ...
    • Pyramid Match Kernels: Discriminative Classification with Sets of Image Features (version 2) 

      Grauman, Kristen; Darrell, Trevor (2006-03-18)
      Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification methods can learn complex decision boundaries, ...