41 Semisupervised PPTs View free & download

Semisupervised Learning PowerPoint PPT Presentation

Semisupervised Learning - Run your favorite clustering algorithm on Xl,Xu. ... all 2u possible labeling of Xu. Build one standard SVM for ... Classify Xu with f(1) and f(2) separately. ...

Run your favorite clustering algorithm on Xl,Xu. ... all 2u possible labeling of Xu. Build one standard SVM for ... Classify Xu with f(1) and f(2) separately. ...

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Semisupervised Learning - Ontology. Why semi-supervised clustering? Why not clustering? ... Ontology based semi-supervised clustering 'A framework for ontology-driven ...

Ontology. Why semi-supervised clustering? Why not clustering? ... Ontology based semi-supervised clustering 'A framework for ontology-driven ...

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Semisupervised Classification PowerPoint PPT Presentation

Semisupervised Classification - ... the affinity matrix W defined by Wij = exp(-||xi-xj||2 /2 2) if i j and Wii = 0. ... Not all unlabeled data fit in one class. Reference ...

... the affinity matrix W defined by Wij = exp(-||xi-xj||2 /2 2) if i j and Wii = 0. ... Not all unlabeled data fit in one class. Reference ...

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Semisupervised learning and selftraining PowerPoint PPT Presentation

Semisupervised learning and selftraining - ... unlabeled data is ... strong and consistent clues to the sense of a target word. ... Sense A: 'life' Sense B: 'manufacturing' Our L(0) U(0) = S L(0) ...

... unlabeled data is ... strong and consistent clues to the sense of a target word. ... Sense A: 'life' Sense B: 'manufacturing' Our L(0) U(0) = S L(0) ...

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Inductive Semisupervised Learning PowerPoint PPT Presentation

Inductive Semisupervised Learning - Information Regularization. SSL for Structured Prediction. Conclusion. 3. Outline of the talk ... regularization. Where: H is the RKHS associated with kernel k ...

Information Regularization. SSL for Structured Prediction. Conclusion. 3. Outline of the talk ... regularization. Where: H is the RKHS associated with kernel k ...

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Semisupervised Learning and Class Discovery PowerPoint PPT Presentation

Semisupervised Learning and Class Discovery - Semisupervised Learning and Class Discovery. David Bazell Eureka Scientific, Inc. David Miller Penn State University. Funded by NASA/AISRP. Overview. Objectives ...

Semisupervised Learning and Class Discovery. David Bazell Eureka Scientific, Inc. David Miller Penn State University. Funded by NASA/AISRP. Overview. Objectives ...

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SemiSupervised Training for AppearanceBased Statistical Object Detection Methods PowerPoint PPT Presentation

SemiSupervised Training for AppearanceBased Statistical Object Detection Methods - Charles Rosenberg. Thesis Oral. May 10, 2004. Thesis Committee. Martial Hebert, co-chair ... Dietterich, Lathrop, Lozano-Perez, AI 97. Maron, Lozano-Perez, NIPS 1998. ...

Charles Rosenberg. Thesis Oral. May 10, 2004. Thesis Committee. Martial Hebert, co-chair ... Dietterich, Lathrop, Lozano-Perez, AI 97. Maron, Lozano-Perez, NIPS 1998. ...

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DB Seminar Series: The Semisupervised Clustering Problem PowerPoint PPT Presentation

DB Seminar Series: The Semisupervised Clustering Problem - A small amount of domain knowledge. Output: ... Little domain knowledge: number of resulting connected components (Kc) = 90% dataset size ...

A small amount of domain knowledge. Output: ... Little domain knowledge: number of resulting connected components (Kc) = 90% dataset size ...

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SemiSupervised Learning Using Label Mean PowerPoint PPT Presentation

SemiSupervised Learning Using Label Mean - Semi-Supervised Learning Using. Label Mean. Yu-Feng Li1, James T. Kwok2, Zhi-Hua Zhou1 ... Medical image segmentation [Grady & Funka-Lea, ECCV'04] ...

Semi-Supervised Learning Using. Label Mean. Yu-Feng Li1, James T. Kwok2, Zhi-Hua Zhou1 ... Medical image segmentation [Grady & Funka-Lea, ECCV'04] ...

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SemiSupervised Classification by Low Density Separation PowerPoint PPT Presentation

SemiSupervised Classification by Low Density Separation - Text: the classes mac and mswindows of the Newsgroup20 dataset preprocessed. ... If L(v) is replaced, put a label (L(v), ui) on v. ...

Text: the classes mac and mswindows of the Newsgroup20 dataset preprocessed. ... If L(v) is replaced, put a label (L(v), ui) on v. ...

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SemiSupervised Boosting for Statistical Word Alignment PowerPoint PPT Presentation

SemiSupervised Boosting for Statistical Word Alignment - Phrase-based machine translation. System: Pharaoh. Metrics: NIST and BLEU ... Boosting does improve word alignment and translation quality ...

Phrase-based machine translation. System: Pharaoh. Metrics: NIST and BLEU ... Boosting does improve word alignment and translation quality ...

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Semisupervised learning - Bayesian methods in a straight discriminative SSL cannot be employed ... Discriminative vs Generative ... about a discriminative approach? Strictly speaking, ...

Bayesian methods in a straight discriminative SSL cannot be employed ... Discriminative vs Generative ... about a discriminative approach? Strictly speaking, ...

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Identification of Causal Variables for Building Energy Fault Detection by Semisupervised LDA PowerPoint PPT Presentation

Identification of Causal Variables for Building Energy Fault Detection by Semisupervised LDA - Keigo Yoshida, Minoru Inui, Takehisa Yairi, Kazuo Machida ... Data Deluge from Numerous Sensors (approx. 2000 sensors for 20-story) Current EF Detection: ...

Keigo Yoshida, Minoru Inui, Takehisa Yairi, Kazuo Machida ... Data Deluge from Numerous Sensors (approx. 2000 sensors for 20-story) Current EF Detection: ...

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DB Seminar Series: Semisupervised Projected Clustering PowerPoint PPT Presentation

DB Seminar Series: Semisupervised Projected Clustering - ... a small amount of domain knowledge available (e.g. the functions ... is no way to utilize the domain knowledge that is accessible (active learning v. ...

... a small amount of domain knowledge available (e.g. the functions ... is no way to utilize the domain knowledge that is accessible (active learning v. ...

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Report on Semisupervised Training for Statistical Parsing PowerPoint PPT Presentation

Report on Semisupervised Training for Statistical Parsing - Idea: two different students learn from each other, incrementally, mutually improving ' ... Composite vs. Monolithic. Large parameter space vs. Small ... LTAG ...

Idea: two different students learn from each other, incrementally, mutually improving ' ... Composite vs. Monolithic. Large parameter space vs. Small ... LTAG ...

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An Overview on SemiSupervised Learning Methods PowerPoint PPT Presentation

An Overview on SemiSupervised Learning Methods - Note: Citations omitted here (given in. my literature review) Semi ... Ask Philosophers! My guess: Selection bias for features/distance. No Matter Why: ...

Note: Citations omitted here (given in. my literature review) Semi ... Ask Philosophers! My guess: Selection bias for features/distance. No Matter Why: ...

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SemiSupervised Approaches for Learning to Parse Natural Languages PowerPoint PPT Presentation

SemiSupervised Approaches for Learning to Parse Natural Languages - Resolve local ambiguities with global likelihood. Rule Exceptions? ... A new challenge: how to obtain training corpora? ... (n, saw, stars, with, Oscars) ...

Resolve local ambiguities with global likelihood. Rule Exceptions? ... A new challenge: how to obtain training corpora? ... (n, saw, stars, with, Oscars) ...

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Identification of Causal Variables for Building Energy Fault Detection by Semisupervised LDA - Heuristics Based on Expert's Empirical Knowledge, usually fuzzy 'IF-THEN' rules. ... beginning with fuzzy heuristics based on domain knowledge. Room for improvements ...

Heuristics Based on Expert's Empirical Knowledge, usually fuzzy 'IF-THEN' rules. ... beginning with fuzzy heuristics based on domain knowledge. Room for improvements ...

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IntraDocument Structural Frequency Features for SemiSupervised Domain Adaptation PowerPoint PPT Presentation

IntraDocument Structural Frequency Features for SemiSupervised Domain Adaptation - Intra-Document Structural Frequency Features for. Semi-Supervised Domain Adaptation ... abbreviated protein name. parenthetical abbreviated protein name ...

Intra-Document Structural Frequency Features for. Semi-Supervised Domain Adaptation ... abbreviated protein name. parenthetical abbreviated protein name ...

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Pairwise Constraint Propagation by Semidefinite Programming for SemiSupervised Classification PowerPoint PPT Presentation

Pairwise Constraint Propagation by Semidefinite Programming for SemiSupervised Classification - Department of Information Engineering. The Chinese University of Hong Kong. 2. Outline ... implicitly obtain the feature map by explicitly pursuing the ...

Department of Information Engineering. The Chinese University of Hong Kong. 2. Outline ... implicitly obtain the feature map by explicitly pursuing the ...

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COMP3503 Semi-Supervised Learning PowerPoint PPT Presentation

COMP3503 Semi-Supervised Learning - COMP3503 Semi-Supervised Learning Daniel L. Silver

COMP3503 Semi-Supervised Learning Daniel L. Silver

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Prediction using Side Information PowerPoint PPT Presentation

Prediction using Side Information - Bin Yu Department of Statistics, UC Berkeley Joint work with Peng Zhao, Guilherme Rocha, and Vince Vu

Bin Yu Department of Statistics, UC Berkeley Joint work with Peng Zhao, Guilherme Rocha, and Vince Vu

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Data Association for Topic Intensity Tracking PowerPoint PPT Presentation

Data Association for Topic Intensity Tracking - Title: Slide 1 Author: School of Computer Science Last modified by: Andreas Krause Created Date: 11/28/2005 1:16:20 AM Document presentation format

Title: Slide 1 Author: School of Computer Science Last modified by: Andreas Krause Created Date: 11/28/2005 1:16:20 AM Document presentation format

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Semi-Supervised Clustering and its Application to Text Clustering and Record Linkage PowerPoint PPT Presentation

Semi-Supervised Clustering and its Application to Text Clustering and Record Linkage - Title: KGP 2002 Talk Author: Sugato Basu Last modified by: Raymond Mooney Created Date: 5/20/2001 10:11:52 PM Document presentation format: On-screen Show

Title: KGP 2002 Talk Author: Sugato Basu Last modified by: Raymond Mooney Created Date: 5/20/2001 10:11:52 PM Document presentation format: On-screen Show

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Semi-Supervised Clustering PowerPoint PPT Presentation

Semi-Supervised Clustering - ... for initialization: initial center for cluster i is the mean of the seed points having label i. ... C: number of points involved in must-link constraints. N: ...

... for initialization: initial center for cluster i is the mean of the seed points having label i. ... C: number of points involved in must-link constraints. N: ...

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PEBL: Web Page Classification without Negative Examples PowerPoint PPT Presentation

PEBL: Web Page Classification without Negative Examples - Manually collected negative training examples could be biased. ... 188 resume pages, 533 non-resume pages. Experiments. Experiment2: University CS Department ...

Manually collected negative training examples could be biased. ... 188 resume pages, 533 non-resume pages. Experiments. Experiment2: University CS Department ...

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NVOSS08 - THE US NATIONAL VIRTUAL OBSERVATORY Basic Concepts in Data Mining Kirk Borne George Mason University * *

THE US NATIONAL VIRTUAL OBSERVATORY Basic Concepts in Data Mining Kirk Borne George Mason University * *

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Dr. C. Lee Giles PowerPoint PPT Presentation

Dr. C. Lee Giles - IST 511 Information Management: Information and Technology Machine Learning Dr. C. Lee Giles David Reese Professor, College of Information Sciences and Technology

IST 511 Information Management: Information and Technology Machine Learning Dr. C. Lee Giles David Reese Professor, College of Information Sciences and Technology

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CS 388: Natural Language Processing: Part-Of-Speech Tagging, Sequence Labeling, and Hidden Markov Models (HMMs) PowerPoint PPT Presentation

CS 388: Natural Language Processing: Part-Of-Speech Tagging, Sequence Labeling, and Hidden Markov Models (HMMs) - Part-Of-Speech Tagging ... Verb * Forward Classification NNP VBD DT NN CC John saw the saw and decided to take it to the table . classifier VBD ... John saw the saw ...

Part-Of-Speech Tagging ... Verb * Forward Classification NNP VBD DT NN CC John saw the saw and decided to take it to the table . classifier VBD ... John saw the saw ...

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Semi-Supervised Clustering and its Application to Text Clustering and Record Linkage - Combines labeled and unlabeled data during training to improve performance: ... 864 restaurant listings from Fodor's and Zagat's guidebooks. ...

Combines labeled and unlabeled data during training to improve performance: ... 864 restaurant listings from Fodor's and Zagat's guidebooks. ...

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Recognition and 3D Reconstruction from Video - Recognition and 3D Reconstruction from Video

Recognition and 3D Reconstruction from Video

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Data Association for Topic Intensity Tracking - Two topics: Conference and Hiking. What if we had temporal information? ... 'Hiking' (parameter for. exponential d.) Problem: ...

Two topics: Conference and Hiking. What if we had temporal information? ... 'Hiking' (parameter for. exponential d.) Problem: ...

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Text summarization PowerPoint PPT Presentation

Text summarization - NSF (joint with Kevin Quinn of Harvard, Burt Monroe of PSU) ... Language Model Based Document Clustering Using Random Walks (HLT-NAACL 2006) ...

NSF (joint with Kevin Quinn of Harvard, Burt Monroe of PSU) ... Language Model Based Document Clustering Using Random Walks (HLT-NAACL 2006) ...

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BrainComputer Interfaces Current Research and Future Prospects PowerPoint PPT Presentation

BrainComputer Interfaces Current Research and Future Prospects - ... rare stimulus (e.g. spotting the store you were looking for while driving) ... joystick in 1 of 4 directions by recognizing 'readiness potentials' and ...

... rare stimulus (e.g. spotting the store you were looking for while driving) ... joystick in 1 of 4 directions by recognizing 'readiness potentials' and ...

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Semi-Supervised Clustering - between O1 and O2 is a real number denoted by D(O1, ... Hierarchy algorithms ... If S 0 then swap o with o' to form the new set of k medoids. K-Medoids example ...

between O1 and O2 is a real number denoted by D(O1, ... Hierarchy algorithms ... If S 0 then swap o with o' to form the new set of k medoids. K-Medoids example ...

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BioDCV: a gridenabled complete validation setup for functional profiling PowerPoint PPT Presentation

BioDCV: a gridenabled complete validation setup for functional profiling - Starting from a suite of C modules and Perl/shell scripts running. on a local HPC resource ... Rewrite shell/Perl scripts in C language. control I/O costs, ...

Starting from a suite of C modules and Perl/shell scripts running. on a local HPC resource ... Rewrite shell/Perl scripts in C language. control I/O costs, ...

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Search Engine Technology PowerPoint PPT Presentation

Search Engine Technology - In what year did baseball become an offical sport? Who is the largest man in ... Compare two approaches: noisy channel model and rule-based. Sentence ranking ...

In what year did baseball become an offical sport? Who is the largest man in ... Compare two approaches: noisy channel model and rule-based. Sentence ranking ...

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Sergios Theodoridis PowerPoint PPT Presentation

Sergios Theodoridis - It turns out that the Na ve Bayes classifier works reasonably well even in cases that violate the independence assumption.

It turns out that the Na ve Bayes classifier works reasonably well even in cases that violate the independence assumption.

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P' Blonda, C' Tarantino PowerPoint PPT Presentation

P' Blonda, C' Tarantino - Hybrid techniques. Future work. ground truth availability ... hybrid compound. EVG1-CT-2001-00055 LEWIS. Thematic Change Detection. Techniques ...

Hybrid techniques. Future work. ground truth availability ... hybrid compound. EVG1-CT-2001-00055 LEWIS. Thematic Change Detection. Techniques ...

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Active SemiSupervision for Pairwise Constrained Clustering PowerPoint PPT Presentation

Active SemiSupervision for Pairwise Constrained Clustering - In each step, assign each point x to the cluster which has the minimum objective function on x. ... When each cluster has at least 1 point, we can use random ...

In each step, assign each point x to the cluster which has the minimum objective function on x. ... When each cluster has at least 1 point, we can use random ...

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Semisupervised Classification of Astronomical Objects PowerPoint PPT Presentation

Semisupervised Classification of Astronomical Objects - David Bazell (PI) Johns Hopkins University Applied Physics Laboratory. David.Bazell@jhuapl.edu. David Miller, Penn State University. Project Summary ...

David Bazell (PI) Johns Hopkins University Applied Physics Laboratory. David.Bazell@jhuapl.edu. David Miller, Penn State University. Project Summary ...

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Semisupervised PowerPoint PPT Presentations