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Investigating properties of Kneser Graphs PowerPoint PPT Presentation
Investigating properties of Kneser Graphs - Investigating properties of. Kneser Graphs. Modesty Briggs. California State ... For n 2t 1, the Kneser graph, K( n, t), is the graph whose vertices are the t ...
Investigating properties of. Kneser Graphs. Modesty Briggs. California State ... For n 2t 1, the Kneser graph, K( n, t), is the graph whose vertices are the t ...
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Xuding Zhu PowerPoint PPT Presentation
Xuding Zhu - Title: Recent development on circular coloring of graphs Author: zhu Last modified by: asus Created Date: 9/7/2002 4:13:35 AM Document presentation format
Title: Recent development on circular coloring of graphs Author: zhu Last modified by: asus Created Date: 9/7/2002 4:13:35 AM Document presentation format
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This research was partially supported by the U.S. National Science Foundation via STIMULATE grant No. 9618874 PowerPoint PPT Presentation
This research was partially supported by the U.S. National Science Foundation via STIMULATE grant No. 9618874 - Smoothing Issues in the Strucutred Language Model The Center for Language and Speech Processing The Johns Hopkins University 3400 N. Charles Street, Barton Hall
Smoothing Issues in the Strucutred Language Model The Center for Language and Speech Processing The Johns Hopkins University 3400 N. Charles Street, Barton Hall
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Evolution of models of atomic structure PowerPoint PPT Presentation
Evolution of models of atomic structure - Title: CHEM 5581: Graduate Level Quantum Chemistry Author: M Weber Last modified by: M Weber Created Date: 5/26/2006 11:33:43 PM Document presentation format
Title: CHEM 5581: Graduate Level Quantum Chemistry Author: M Weber Last modified by: M Weber Created Date: 5/26/2006 11:33:43 PM Document presentation format
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Random Forests for Language Modeling PowerPoint PPT Presentation
Random Forests for Language Modeling - Random Forests for Language Modeling Peng Xu and Frederick Jelinek IPAM: January 24, 2006 What Is a Language Model? A probability distribution over word sequences ...
Random Forests for Language Modeling Peng Xu and Frederick Jelinek IPAM: January 24, 2006 What Is a Language Model? A probability distribution over word sequences ...
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???????????? PowerPoint PPT Presentation
???????????? - Title: PowerPoint Presentation Last modified by: bonanza Created Date: 1/1/1601 12:00:00 AM Document presentation format: (4:3)
Title: PowerPoint Presentation Last modified by: bonanza Created Date: 1/1/1601 12:00:00 AM Document presentation format: (4:3)
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Evolution of models of atomic structure Breakdown of classical physics PowerPoint PPT Presentation
Evolution of models of atomic structure Breakdown of classical physics - Atoms: atomo (Greek) indivisible. first speculative atomistic theories by ... electrolysis found by Michael Faraday (1791-1861) ... more than 2000 years later ...
Atoms: atomo (Greek) indivisible. first speculative atomistic theories by ... electrolysis found by Michael Faraday (1791-1861) ... more than 2000 years later ...
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Ramseyan Theorems for Numbers PowerPoint PPT Presentation
Ramseyan Theorems for Numbers - A is a sum-free set, if: A N s.t. x,y A x y A. G: abelian group; S G a subset ... 2 strings will receive the same sequence of colors (pigeon hole principle) page 29 ...
A is a sum-free set, if: A N s.t. x,y A x y A. G: abelian group; S G a subset ... 2 strings will receive the same sequence of colors (pigeon hole principle) page 29 ...
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Investigating Linguistic Knowledge In A Maximum Entropy TokenBased Language Model PowerPoint PPT Presentation
Investigating Linguistic Knowledge In A Maximum Entropy TokenBased Language Model - basketball. Data sharing depends on knowledge: ... Addressing data sharing in both history and future . Enabling Unlabeled training ...
basketball. Data sharing depends on knowledge: ... Addressing data sharing in both history and future . Enabling Unlabeled training ...
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LING 406 Intro to Computational Linguistics Estimation and Smoothing PowerPoint PPT Presentation
LING 406 Intro to Computational Linguistics Estimation and Smoothing - Good-Turing and Word Frequency Distributions. Good-Turing and ... Why dost stand forth thy canopy, forsooth; he is this palpable hit the King Henry. ...
Good-Turing and Word Frequency Distributions. Good-Turing and ... Why dost stand forth thy canopy, forsooth; he is this palpable hit the King Henry. ...
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Language Models for Handwriting PowerPoint PPT Presentation
Language Models for Handwriting - Language Models for Handwriting
Language Models for Handwriting
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The Merris index of a graph Gregory Shapiro Joint work with Felix Goldberg PowerPoint PPT Presentation
The Merris index of a graph Gregory Shapiro Joint work with Felix Goldberg - Other Title: The Laplacian eigenvalues and graph independence number ... We will define the independence number of a graph as the maximal cardinality of ...
Other Title: The Laplacian eigenvalues and graph independence number ... We will define the independence number of a graph as the maximal cardinality of ...
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bcoloring of Graphs PowerPoint PPT Presentation
bcoloring of Graphs - Bounds for the b-chromatic no. of G-v - Bounds for b(G-v) in terms of b(G) ... F. Bonomo, G. Duran, F. Maffray, J. Marenco, and M.V. Pabon, On the b-coloring ...
Bounds for the b-chromatic no. of G-v - Bounds for b(G-v) in terms of b(G) ... F. Bonomo, G. Duran, F. Maffray, J. Marenco, and M.V. Pabon, On the b-coloring ...
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Using a Multirepresentational Design Framework to Develop and Evaluate a Dynamic Simulation Environm PowerPoint PPT Presentation
Using a Multirepresentational Design Framework to Develop and Evaluate a Dynamic Simulation Environm - Tabachneck, et al (1994) found that students who used more than one rep were ... e.g. concrete - abstract or Verdi, Johnson, Stock, Kulhavy, & Ahern, (1997) ...
Tabachneck, et al (1994) found that students who used more than one rep were ... e.g. concrete - abstract or Verdi, Johnson, Stock, Kulhavy, & Ahern, (1997) ...
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The Effect of Generation and Interaction on Robust Learning PowerPoint PPT Presentation
The Effect of Generation and Interaction on Robust Learning - Conceptual Engineering (Hausmann, 2006) Hundreds more... None: example studying. Method ... United States Naval Academy (N=100) Materials. Andes homework system ...
Conceptual Engineering (Hausmann, 2006) Hundreds more... None: example studying. Method ... United States Naval Academy (N=100) Materials. Andes homework system ...
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Improved Speech Recognition using Acoustic and Lexical Correlates of Pitch Accent in a NBest Rescori PowerPoint PPT Presentation
Improved Speech Recognition using Acoustic and Lexical Correlates of Pitch Accent in a NBest Rescori - These cues, which constitute the prosody of the utterance and occur at the ... De-lexicalized prosody sequence model ... Since we built prosody models at the ...
These cues, which constitute the prosody of the utterance and occur at the ... De-lexicalized prosody sequence model ... Since we built prosody models at the ...
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Poincar on the way to his conjecture PowerPoint PPT Presentation
Poincar on the way to his conjecture - Poincar on the way to his conjecture. Groningen, 4.5.07; Strasbourg, 9.5.07. Klaus Volkert (Universit t zu K ln/Archives Henri Poincar Nancy) Poincar und seine ...
Poincar on the way to his conjecture. Groningen, 4.5.07; Strasbourg, 9.5.07. Klaus Volkert (Universit t zu K ln/Archives Henri Poincar Nancy) Poincar und seine ...
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Algorithmic Problems for Curves PowerPoint PPT Presentation
Algorithmic Problems for Curves - algorithmic questions, history. TOOL: (Quadratic) word equations. Regular structures in drawings ... quadratic word equation drawing problem. bound on ...
algorithmic questions, history. TOOL: (Quadratic) word equations. Regular structures in drawings ... quadratic word equation drawing problem. bound on ...
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The development of the HTK Broadcast News transcription system: An overview PowerPoint PPT Presentation
The development of the HTK Broadcast News transcription system: An overview - with or without background music or other background noise ... wideband speech, narrowband speech, music ( reject) ... Vocal tract length normalization (VTLN) ...
with or without background music or other background noise ... wideband speech, narrowband speech, music ( reject) ... Vocal tract length normalization (VTLN) ...
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MT System Combination PowerPoint PPT Presentation
MT System Combination - Make use of the individual strengths of the different systems to ... 2.7 giga words English data, 5-gram LM. SRI LM toolkit. LDC: Linguistic Data Consortium ...
Make use of the individual strengths of the different systems to ... 2.7 giga words English data, 5-gram LM. SRI LM toolkit. LDC: Linguistic Data Consortium ...
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Weighted%20Deduction%20as%20an%20Abstraction%20Level%20for%20AI PowerPoint PPT Presentation
Weighted%20Deduction%20as%20an%20Abstraction%20Level%20for%20AI - Eric Goldlust, Noah A. Smith, John Blatz, Wes Filardo, Wren Thornton ... I thought computers were supposed to automate drudgery. How to spend one's life? ...
Eric Goldlust, Noah A. Smith, John Blatz, Wes Filardo, Wren Thornton ... I thought computers were supposed to automate drudgery. How to spend one's life? ...
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Interfacing with Learning Technologies PowerPoint PPT Presentation
Interfacing with Learning Technologies - Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989) ... Machine-Mediated Learning, 5(2), 119-133. Larkin, J. H., & Simon, H. A. (1987) ...
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989) ... Machine-Mediated Learning, 5(2), 119-133. Larkin, J. H., & Simon, H. A. (1987) ...
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Novel Speech Recognition Models for Arabic PowerPoint PPT Presentation
Novel Speech Recognition Models for Arabic - AR 'knitting' example. unknown: t bqwA. kn.roman: yibqu. ops: ... Knitting local model n-best 30.0% 23.1% (n = 25) Varying the number of dictionary matches ...
AR 'knitting' example. unknown: t bqwA. kn.roman: yibqu. ops: ... Knitting local model n-best 30.0% 23.1% (n = 25) Varying the number of dictionary matches ...
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Weighted Deduction as a Programming Language PowerPoint PPT Presentation
Weighted Deduction as a Programming Language - co-authors on various parts of this work: ... MELISMA. MSA of protein structures. C . 3524. 7620. 50. MUSTANG. MSA of amino acid seqs ...
co-authors on various parts of this work: ... MELISMA. MSA of protein structures. C . 3524. 7620. 50. MUSTANG. MSA of amino acid seqs ...
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STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHER-DOMAIN CORPUS
STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHER-DOMAIN CORPUS - STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHER-DOMAIN CORPUS Lucia Na inovi , Sanda Martin i -Ip i and Ivo Ip i Department of Informatics, University of ...
STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHER-DOMAIN CORPUS Lucia Na inovi , Sanda Martin i -Ip i and Ivo Ip i Department of Informatics, University of ...
STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHERDOMAIN CORPUS
STATISTICAL LANGUAGE MODELS FOR CROATIAN WEATHERDOMAIN CORPUS - Lucia Nacinovic, Sanda Martincic-Ip ic and Ivo Ip ic ... Statistical language modelling estimates the regularities in natural languages ...
Lucia Nacinovic, Sanda Martincic-Ip ic and Ivo Ip ic ... Statistical language modelling estimates the regularities in natural languages ...
A Bit of Progress in Language Modeling Extended Version
A Bit of Progress in Language Modeling Extended Version - ... data source will have the lowest possible perplexity. The lower the perplexity of our model, the closer it is, ... Entropy, which is simply log2 of perplexity ...
... data source will have the lowest possible perplexity. The lower the perplexity of our model, the closer it is, ... Entropy, which is simply log2 of perplexity ...
Language Models: Given the text so far, what word comes _______
Language Models: Given the text so far, what word comes _______ - ... (or unseen) n-grams is overestimated. Therefore, too much probability mass is shifted towards unseen n-grams ... All unseen n-grams are smoothed in the same way ...
... (or unseen) n-grams is overestimated. Therefore, too much probability mass is shifted towards unseen n-grams ... All unseen n-grams are smoothed in the same way ...
The Sequence Memoizer
The Sequence Memoizer - Rule for stochastic memoization. TexPoint fonts used in EMF. ... Latent conditional distributions with Pitman Yor priors / stochastic memoizers ...
Rule for stochastic memoization. TexPoint fonts used in EMF. ... Latent conditional distributions with Pitman Yor priors / stochastic memoizers ...
SI485i : NLP
SI485i : NLP - Perplexity. Perplexity is the probability of the test set (assigned by the language model), normalized by the number of words: Chain rule: For bigrams:
Perplexity. Perplexity is the probability of the test set (assigned by the language model), normalized by the number of words: Chain rule: For bigrams:
Statistical Inference: ngram Models over Sparse Data
Statistical Inference: ngram Models over Sparse Data - bigram PELE PMLE. Still too much discount? Yes. P(she was inferior to both sisters) Bigram ELE - PELE = 6.89 10-20 ( =0.5) Worse than Unigram MLE. Low prob than ...
bigram PELE PMLE. Still too much discount? Yes. P(she was inferior to both sisters) Bigram ELE - PELE = 6.89 10-20 ( =0.5) Worse than Unigram MLE. Low prob than ...
CS 388: Natural Language Processing: N-Gram Language Models
CS 388: Natural Language Processing: N-Gram Language Models - Initialize sentence with N s symbols. Until /s is generated do: ... P(food | chinese) P( /s | food) = .25 x .33 x .0065 x .52 x .68 = .00019 ...
Initialize sentence with N s symbols. Until /s is generated do: ... P(food | chinese) P( /s | food) = .25 x .33 x .0065 x .52 x .68 = .00019 ...
The State of the Art in PhraseBased Statistical Machine Translation SMT
The State of the Art in PhraseBased Statistical Machine Translation SMT - WPT/WMT usually organized each spring by Philipp Koehn & Christoph Monz ... 2. in 2006 WMT evaluation Systran was scored comparably to other systems for ...
WPT/WMT usually organized each spring by Philipp Koehn & Christoph Monz ... 2. in 2006 WMT evaluation Systran was scored comparably to other systems for ...
Speech Recognition and Understanding
Speech Recognition and Understanding - Pitch and formant structure. Quantization. Segmentation (blocking) Windowing. Preemphasis ... Formants. Noise. removal, Normalization. M,N. Energy. Zero ...
Pitch and formant structure. Quantization. Segmentation (blocking) Windowing. Preemphasis ... Formants. Noise. removal, Normalization. M,N. Energy. Zero ...
Smoothing
Smoothing - ... conditional entropy, mutual information ... much count mass did we harvest ... We redistribute the count mass of types observed r 1 times evenly among ...
... conditional entropy, mutual information ... much count mass did we harvest ... We redistribute the count mass of types observed r 1 times evenly among ...
Language Modeling experiences collected over the past evaluations SWB, MT
Language Modeling experiences collected over the past evaluations SWB, MT - Language Modeling experiences collected. over the ... Switchboard. 52.0% Switchboard. Meeting. 51.6% Meeting. Meeting. WER. Dictionary type. Acoustic Model ...
Language Modeling experiences collected. over the ... Switchboard. 52.0% Switchboard. Meeting. 51.6% Meeting. Meeting. WER. Dictionary type. Acoustic Model ...
Natural Language Processing
Natural Language Processing - theta bled own there. Instead ... I notice three guys standing on the ? ... (I notice), (notice three), (three guys), (guys standing), (standing on), (on the) ...
theta bled own there. Instead ... I notice three guys standing on the ? ... (I notice), (notice three), (three guys), (guys standing), (standing on), (on the) ...
Applications of Statistical Natural Language Processing
Applications of Statistical Natural Language Processing - LSI text classification, Ontological Engineering, Question Answering. Multi-Agent coordination ... Shallow parsing, grammar debug, Named Entity Recognition ...
LSI text classification, Ontological Engineering, Question Answering. Multi-Agent coordination ... Shallow parsing, grammar debug, Named Entity Recognition ...
Part II. Statistical NLP
Part II. Statistical NLP - ... (n-gram) + 1 The idea is to give a little bit of the probability space ... In NLP applications that are very sparse, Laplace s ... The channel transforms the ...
... (n-gram) + 1 The idea is to give a little bit of the probability space ... In NLP applications that are very sparse, Laplace s ... The channel transforms the ...
Style
Style - An effective LM needs to not only account for the casual ... In this paper, the syntactic state and semantic topic ... ensemble of 'walkers' moves around ...
An effective LM needs to not only account for the casual ... In this paper, the syntactic state and semantic topic ... ensemble of 'walkers' moves around ...
Smoothing
Smoothing - This black art is why NLP is taught in the engineering school. 600.465 - Intro to ... Should we conclude. p(a | xy) = 1/3? p(d | xy) = 2/3? p(z | xy) = 0/3? NO! ...
This black art is why NLP is taught in the engineering school. 600.465 - Intro to ... Should we conclude. p(a | xy) = 1/3? p(d | xy) = 2/3? p(z | xy) = 0/3? NO! ...
The State of The Art in Language Modeling
The State of The Art in Language Modeling - P(baby is a boy) 0.5 (% of total that are boys) ... 'sales' (1 in 4), 30,000 names (1 in 120,000) Imagine data: All 30,004 equally likely ...
P(baby is a boy) 0.5 (% of total that are boys) ... 'sales' (1 in 4), 30,000 names (1 in 120,000) Imagine data: All 30,004 equally likely ...
The Sequence Memoizer
The Sequence Memoizer - Smoothing Markov model of discrete sequences ... of the string 'cacao' ``Non-Markov'' Model ... All suffixes of the string 'cacao' Suffix Trie Datastructure ...
Smoothing Markov model of discrete sequences ... of the string 'cacao' ``Non-Markov'' Model ... All suffixes of the string 'cacao' Suffix Trie Datastructure ...
LSA 352: Speech Recognition and Synthesis
LSA 352: Speech Recognition and Synthesis - Telephone-based Information (directions, air travel, banking, etc) Hands-free (in car) ... based Information (directions, air travel, banking, etc) Eyes-free ...
Telephone-based Information (directions, air travel, banking, etc) Hands-free (in car) ... based Information (directions, air travel, banking, etc) Eyes-free ...
Part II. Statistical NLP
Part II. Statistical NLP - Wolfram Burgard, Luc De Raedt, Bernhard Nebel, Lars Schmidt-Thieme ... gun, gum, Gus, and gull are words, but gun has a higher probability in the context of a bank ...
Wolfram Burgard, Luc De Raedt, Bernhard Nebel, Lars Schmidt-Thieme ... gun, gum, Gus, and gull are words, but gun has a higher probability in the context of a bank ...
CS 124LINGUIST 180: From Language to Information
CS 124LINGUIST 180: From Language to Information - So in general, Laplace is a blunt instrument. But Laplace smoothing not used for ... Despite its flaws Laplace (add-k) is however still used to smooth other ...
So in general, Laplace is a blunt instrument. But Laplace smoothing not used for ... Despite its flaws Laplace (add-k) is however still used to smooth other ...
CSCI 5832 Natural Language Processing
CSCI 5832 Natural Language Processing - ... (ish) traditional parts of speech Noun, verb, adjective, preposition, adverb ... IN outer/JJ space/NN How do we pick the right ... presentation format:
... (ish) traditional parts of speech Noun, verb, adjective, preposition, adverb ... IN outer/JJ space/NN How do we pick the right ... presentation format:


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