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Course: ECE 580, Fall 2011School: UMass (Amherst)
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Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
ECE 580 FEEDBACK CONTROL SYSTEMS (I)Problem Set #4Issued: Thursday, October 13, 2011Problem 1:Due: Tuesday, October 25, 2011Automatic control of helicopters is necessary because, unlike fixed wing aircraft, thehelicopter is quite unstable. A helicop
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
ECE 580 FEEDBACK CONTROL SYSTEMS (I)Problem Set #6Issued: Thursday, November 3, 2011Problem 1:Due: Thursday, November 17, 2011a) Franklin, Powell and Emami-Naeini, Problem 6.4 (c), p. 390.b) Franklin, Powell and Emami-Naeini, Problem 6.5 (b), p. 390
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
ECE 580 FEEDBACK CONTROL SYSTEMS (I)Problem Set #7Issued: Thursday, November 17, 2011Due: Thursday, December 1, 2011Problem 1:Franklin, Powell and Emami-Naeini, Problem, 6.41 p. 401-402.Problem 2:Franklin, Powell and Emami-Naeini, Problem 6.45, p.
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
ECE 580 FEEDBACK CONTROL SYSTEMS (I)Problem Set #8Issued: Thursday, December 1, 2011Due: Thursday, December 8, 2011Problem 1:Franklin, Powell and Emami-Naeini, Problem 6.55a-i, p. 405-406.Problem 1:Franklin, Powell and Emami-Naeini, Problem 6.63, p
Rutgers - 510 - 101
UMass (Amherst) - ECE - 580
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
Speech and Language ProcessingAn Introduction to Natural Language Processing, Computational Linguistics, and Speech RecognitionSecond EditionDaniel JurafskyStanford UniversityJames H. MartinUniversity of Colorado at BoulderUpper Saddle River, New J
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
Introduction to Natural Language Processing (CMPSCI 585)Prof. Andrew McCallum (mccallum@cs.umass.edu)First-Day Questionnaire - September 4, 2007Name:Email (important!):Student ID#:Grad/UGrad, Department/Major, year, etc.:Are you in this cla
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
R e g u la r L a n g u a g e sL e c tu re # 2Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e r s t,in c lu d in g m a te r ia l f r o m
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
In t r o d u c t io n t o P y t h o nL e c tu re # 3Computational LinguisticsCMPSCI 591N, Spring 2006University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e r s t,in c lu d in g m a te r ia l f r o m E q a n
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
S t r in g E d it D is t a n c e( a n d in t r o t o d y n a m ic p r o g r a m m in g )L e c tu re # 4Computational LinguisticsCMPSCI 591N, Spring 2006University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
P r o b a b ilit yL e c tu re # 7Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e r s tT o d a y s M a in P o in t s Remember (or learn)
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
C la s s if ic a t io n & In f o r m a t io n T h e o r yL e c tu re # 8Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e r s tT o d a y s
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
N o is y C h a n n e l, N - g r a m s & S m o o t h in gL e c tu re # 9Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a s s A m h e r s tT o d a y s
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
P a r t - o f - s p e e c h T a g g in g &H id d e n M a r k o v M o d e l In t r oL e c tu re # 1 0Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallumA n d r e w M c C a llu m , U M a
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
ProbabilisticContext Free GrammarsLecture #14Computational LinguisticsCMPSCI 591N, Spring 2006Andrew McCallum(including slides from Jason Eisner)Ambiguity in Parsing Time flies like an arrow. Fruit flies like a banana. I saw the man with the tel
Rutgers - 510 - 101
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
Probabilistic Parsingin PracticeLecture #15Computational LinguisticsCMPSCI 591N, Spring 2006Andrew McCallum(including slides from Michael Collins, Chris Manning, Jason Eisner, Mary Harper)Todays Main Points Training data How to evaluate parsers
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
Maximum EntropyLecture #13Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007University of Massachusetts AmherstAndrew McCallum(Slides from Jason Eisner and Dan Klein)1summary of half of the course (statistics)Probability is Useful
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
The pragmatics of questions and answersChristopher PottsUMass Amherst LinguisticsCMPSCI 585, November 6, 2007BackgroundPragbotThis lecture123456A brief, semi-historial overview of linguistic pragmaticsA few notes on the SUBTLE projectSome i
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
Machine TranslationLecture #17Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007Andrew McCallum(including slides from Michael Collins, and Dan Klein)The challenges of Machine TranslationLexical AmbiguityExample 1 :b o o k the ightr
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
S t a t is t ic a l M o d e ls o f S e m a n t ic s a n dU n s u p e r v is e d L a n g u a g e D is c o v e r yL e c tu re # 1 8Introduction to Natural Language ProcessingCMPSCI 585, Fall 2007Andrew McCallumC o m p u t e r S c ie n c e D e p a r t
Rutgers - 510 - 101
Rutgers - 510 - 101
UMass (Amherst) - CMPSCI - 585
IntroQuestionsImplicaturesDecision theoryConclusionThe pragmatics of questions and answers, Part 2:Partition semantics and decision-theoreticpragmaticsChristopher PottsUMass Amherst LinguisticsCMPSCI 585, December 4, 2007IntroQuestionsImplica
Rutgers - 510 - 101