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Browsing Computer Science and Artificial Intelligence Lab (CSAIL) by Title

Research and Teaching Output of the MIT Community

Browsing Computer Science and Artificial Intelligence Lab (CSAIL) by Title

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  • Gilbert, Seth; Guerraoui, Rachid; Newport, Calvin (2006-04-19)
    How much damage can a malicious tiny device cause in a single-hopwireless network? Imagine two players, Alice and Bob, who want toexchange information. Collin, a malicious adversary, wants to preventthem from communicating. ...
  • Flynn, Anita (1988-12-01)
    The 1989 AI Lab Winter Olympics will take a slightly different twist from previous Olympiads. Although there will still be a dozen or so athletic competitions, the annual talent show finale will now be a display not ...
  • Fan, Rui; Lynch, Nancy (2006-07-23)
    We prove an $\Omega(n \log n)$ lower bound on the number ofnon-busywaiting memory accesses by any deterministic algorithm solving$n$ process mutual exclusion that communicates via shared registers.The cost of the algorithm ...
  • Zhao, Feng (1987-10-01)
    We develop an algorithm that computes the gravitational potentials and forces on N point-masses interacting in three-dimensional space. The algorithm, based on analytical techniques developed by Rokhlin and Greengard, ...
  • Marnette, Bruno; Kuncak, Viktor; Rinard, Martin (2005-08-03)
    Typestate systems ensure many desirable properties of imperativeprograms, including initialization of object fields and correct use ofstateful library interfaces. Abstract sets with cardinalityconstraints naturally ...
  • Caponnetto, Andrea; Poggio, Tomaso; Smale, Steve (2008-04-04)
    In this paper we present a class of algorithms for similarity learning on spaces of images. The general framework that we introduce is motivated by some well-known hierarchical pre-processing architectures for object ...
  • Herskovits, Annette; Binford, Thomas O. (1970-07-01)
    A description is given of how edge erase of prismatic objects appear through a television camera serving as visual input to a computer. Two types of edge-finding predicates are proposed and compared, one linear in intensity, ...
  • Jordan, Michael; Xu, Lei (1995-04-21)
    "Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a ...
  • Kuncak, Viktor; Rinard, Martin (2004-11-30)
    An important feature of object-oriented programming languages is the ability todynamically instantiate user-defined container data structures such as lists, trees,and hash tables. Programs implement such data structures ...
  • Stein, Gideon P.; Shashua, Amnon (1997-12-01)
    This paper investigates the linear degeneracies of projective structure estimation from point and line features across three views. We show that the rank of the linear system of equations for recovering the trilinear tensor ...
  • Borg-Graham, Lyle J. (1992-01-01)
    This thesis describes an investigation of retinal directional selectivity. We show intracellular (whole-cell patch) recordings in turtle retina which indicate that this computation occurs prior to the ganglion cell, ...
  • Eppinger, Steven D.; Seering, Warren P. (1986-07-01)
    For precise robot control, endpoint compliance strategies utilize feedback from a force sensor located near the tool/workpiece interface. Such endpoint force control systems have been observed in the laboratory to be ...
  • Lawler, R.W. (1980-03-01)
    This is a case study of how one child learned to write in a computer-rich setting. Although computer access did affect her learning significantly, the details presented here go beyond supporting that claim. They provide ...
  • Abari, Omid; Rahul, Hariharan; Katabi, Dina (2014-04-27)
    Implementing distributed wireless protocols at the physical layer today is challenging because different nodes have different clocks, each of which has slightly different frequencies. This causes the nodes to have frequency ...
  • Torre, V.; Poggio, T. (1984-08-01)
    Edge detection is the process that attempts to characterize the intensity changes in the image in terms of the physical processes that have originated them. A critical, intermediate goal of edge detection is the detection ...
  • 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 ...
  • Rieger, Chuck (MIT Artificial Intelligence Laboratory, 1975-11)
    Plan synthesis and language comprehension, or more generally, the act of discovering how one perception relates to others, are two sides of the same coin, because they both rely on a knowledge of cause and effect - algorithmic ...
  • Woo, Grace; Katabi, Dina; Chachulski, Szymon (2008-10-18)
    The fundamental problem of wireless video multicast is to scalably serve multiple receivers which may have very different channel characteristics. Ideally, one would like to broadcast a single stream that allows each ...
  • Wies, Thomas; Kuncak, Viktor; Lam, Patrick; Podelski, Andreas; Rinard, Martin (2005-11-03)
    We introduce field constraint analysis, a new technique for verifying data structure invariants. A field constraint for a field is a formula specifying a set of objects to which the field can point. Field constraints ...
  • Kuncak, Viktor; Rinard, Martin (2004-04-06)
    We have previously introduced role logic as a notation fordescribing properties of relational structures in shapeanalysis, databases and knowledge bases. A natural fragmentof role logic corresponds to two-variable logic ...
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