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

Now showing items 2586-2605 of 2625

  • Wandering About the Top of the Robot 

    Unknown author (MIT Artificial Intelligence Laboratory, 1971-07)
    Part I of this paper describes some of the new functions in the system. The discussion is seasoned here and there with parenthetical code fragments that may be ignored by readers unfamiliar with PLANNER. Part II discussed ...

  • Was the Patient Cured? Understanding Semantic Categories and Their Relationships in Patient Records 

    Unknown author (2006-06-28)
    In this thesis, we detail an approach to extracting key information in medical discharge summaries. Starting with a narrative patient report, we first identify and remove information that compromises privacy (de-identifi ...

  • WaveScript: A Case-Study in Applying a Distributed Stream-Processing Language 

    Unknown author (2008-01-31)
    Applications that combine live data streams with embedded, parallel,and distributed processing are becoming more commonplace. WaveScriptis a domain-specific language that brings high-level, type-safe,garbage-collected ...

  • Werner Reichardt: the man and his scientific legacy 

    Unknown author (2011-03-04)
    Excerpts from a talk given by Tomaso Poggio in Tübingen on the opening ofthe Werner Reichardt Centrun für Integrative Neurowissenschaften, December 8, 2008.

  • Whanaungatanga: Sybil-proof routing with social networks 

    Unknown author (2009-09-24)
    Decentralized systems, such as distributed hash tables, are subject to the Sybil attack, in which an adversary creates many false identities to increase its influence. This paper proposes a routing protocol for a distributed ...

  • What a Parallel Programming Language Has to Let You Say 

    Unknown author (1984-09-01)
    We have implemented in simulation a prototype language for the Connection Machine called CL1. CL1 is an extrapolation of serial machine programming language technology: in CL1 one programs the individual processors ...

  • What Are Plans For? 

    Unknown author (1989-10-01)
    What plans are like depends on how they're used. We contrast two views of plan use. On the plan-as-program-view, plan use is the execution of an effective procedure. On the plan-as-communication view, plan use is like ...

  • What Corners Look Like 

    Unknown author (MIT Artificial Intelligence Laboratory, 1971-06)
    An algorithm is presented which provides a way of telling what a given trihedral corner will look like if viewed from a particular angle. The resulting picture is a junction of two or more lines each labelled according to ...

  • What is Decidable about Strings? 

    Unknown author (2011-02-01)
    We prove several decidability and undecidability results for the satisfiability/validity problem of formulas over a language of finite-length strings and integers (interpreted as lengths of strings). The atomic formulas ...

  • What is Delaying the Manipulator Revolution? 

    Unknown author (MIT Artificial Intelligence Laboratory, 1978-02)
    Despite two decades of work on mechanical manipulators and their associated controls, we do not see wide-spread application of these devices to many of the tasks to which they seem so obviously suited. Somehow, a variety ...

  • What Makes a Good Feature? 

    Unknown author (1992-04-01)
    Using a Bayesian framework, we place bounds on just what features are worth computing if inferences about the world properties are to be made from image data. Previously others have proposed that useful features reflect ...

  • What the Assassin's Guild Taught Me About Distributed Computing 

    Unknown author (2006-05-27)
    Distributed computing and live-action roleplaying share many of thesame fundamental problems, as live-action roleplaying games commonly include simulations carried out by their players.Games run by the MIT Assassin's Guild ...

  • What to Read: A Biased Guide to AI Literacy for the Beginner 

    Unknown author (MIT Artificial Intelligence Laboratory, 1972-11)
    This note tries to provide a quick guide to AI literacy for the beginning AI hacker and for the experienced AI hacker or two whose scholarship isn't what it should be. most will recognize it as the same old list of classic ...

  • What's in a Tune 

    Unknown author (1974-11-01)
    The work reported here began with two fundamental assumptions: 1) The perception of music is an active process; it involves the individual in selecting, sorting, and grouping the features of the phenomena before her. ...

  • What's What 

    Unknown author (MIT Artificial Intelligence Laboratory, 1971-03)
    An outline of the modules used in the copy demonstration, the reasons for doing robotics, and some possible directions for further work.

  • Why are There so Few Female Computer Scientists? 

    Unknown author (1991-08-01)
    This report examines why women pursue careers in computer science and related fields far less frequently than men do. In 1990, only 13% of PhDs in computer science went to women, and only 7.8% of computer science ...

  • Why Conniving is Better than Planning 

    Unknown author (1972-02-01)
    A higher level language derives its great power form the fact that it tends to impose structure on the problem solving behavior for the user. Besides providing a library of useful subroutines with a uniform calling ...

  • Why Conniving is Better than Plannng 

    Unknown author (1972-04-01)
    This paper is a critique of a computer programming language, Carl Hewitts PLANNER, a formalism designed especially to cope with the problems that Artificial Intelligence encounters. It is our contention that the ...

  • Why Do We See Three-dimensional Objects? 

    Unknown author (1992-06-01)
    When we look at certain line-drawings, we see three-dimensional objects. The question is why; why not just see two-dimensional images? We theorize that we see objects rather than images because the objects we see are, ...

  • Why Stereo Vision is Not Always About 3D Reconstruction 

    Unknown author (1993-07-01)
    It is commonly assumed that the goal of stereovision is computing explicit 3D scene reconstructions. We show that very accurate camera calibration is needed to support this, and that such accurate calibration is difficult ...