Presented by: Awatif K. Al-Mutairi Hind K. Bin-Drees Sarah N. Al-Gubaisi Supervised by: Dr. Al-Johara Al- Quaiz

Nov 30, 2012

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Presented by: Awatif K. Al-Mutairi Hind K. Bin-Drees Sarah N. Al-Gubaisi Supervised by: Dr. Al-Johara Al- Quaiz

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Supervised Distance Metric Learning

Supervised Distance Metric Learning. Presented at CMU’s Computer Vision Misc-Read Reading Group May 9, 2007 by Tomasz Malisiewicz. Overview. Short Metric Learning Overview Eric Xing et al (2002) Kilian Weinberger et al (2005) Local Distance Functions Andrea Frome et al (2006).

986 views • 34 slides

Supervised Clustering --- Algorithms and Applications

Supervised Clustering --- Algorithms and Applications. Christoph F. Eick Department of Computer Science University of Houston Organization of the Talk Supervised Clustering Representative-based Supervised Clustering Algorithms Applications: Using Supervised Clustering for Dataset Editing

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Presented by Sam Supervised by Prof. Michael Lyu

Presented by Sam Supervised by Prof. Michael Lyu. Outline. What is Virtual Campus? Changing Trend of Learning Style New Learning Process Basic Architecture Components of Virtual Campus Future Work Conclusion. Delivery the ‘own-paced’ material to the right person in any time .

432 views • 25 slides

Supervised, semi-supervised and Unsu pervised approaches for word sense disambiguation

Supervised, semi-supervised and Unsu pervised approaches for word sense disambiguation. Slides by Arindam Chatterjee & Salil Joshi. Under the guidance of. Prof. Pushpak Bhattacharyya. May 01, 2010. roadmap. Bird’s Eye View. Supervised Approaches. Semi-supervised Approaches.

772 views • 56 slides

Presented by Sarah E. Johnston

Opportunistic Fungal infections that can occur in HIV infected individuals. Presented by Sarah E. Johnston. Overview. HIV effects on immune system potential fungal pathogens of HIV patients Pneumonocystis jirovecii and the disease PCP Cryptococcus neoformans and fungal meningitis

579 views • 15 slides

How to … teach English with technology

How to … teach English with technology. Presented by Sherefah Al- mutairi. http://setiteachers.ning.com http://eflclassroom.com. “ one teaches, two learn. ”. You and the computer. How do you use the computer in your classroom or in teaching?. Learning & teaching Tools.

1.34k views • 26 slides

SO, 12/13

SO, 12/13. Orthoptera (Grasshoppers and Crickets). Orthopterans all tend to have several traits Enlarged hind legs Big compound eyes (usually) Large pronotum If winged, forewings are thin and leathery Hind wings are broad and membranous Usually have two cerci

316 views • 13 slides

Supervised Agriculture Experience (SAE)

Supervised Agriculture Experience (SAE). Ms. Marlin Advanced Animal Science. SAE . SAE. What does this have to do with supervised agriculture experience? Why might we need to know our career paths?. Objectives. Determine how the FFA enhance SAEs.

351 views • 13 slides

Integrating Constraints and Metric Learning in Semi-Supervised Clustering

Integrating Constraints and Metric Learning in Semi-Supervised Clustering. Mikhail Bilenko, Sugato Basu, Raymond J. Mooney ICML 2004 Presented by Xin Li. Semi-Supervised Clustering. K=4. Semi-Supervised Clustering. Semi-Supervised Clustering. How to exploit supervision in clustering.

355 views • 21 slides

Inductive Semi-supervised Learning

Inductive Semi-supervised Learning. Gholamreza Haffari Supervised by: Dr. Anoop Sarkar Simon Fraser University, School of Computing Science. Outline of the talk. Introduction to Semi-Supervised Learning (SSL) Classifier based methods EM

857 views • 46 slides

Semi-Supervised Clustering

Semi-Supervised Clustering. CS 685: Special Topics in Data Mining Spring 2008 Jinze Liu. Outline of lecture. Overview of clustering and classification What is semi-supervised learning? Semi-supervised clustering Semi-supervised classification Semi-supervised clustering

1.15k views • 55 slides

Artificial Neural Network Supervised Learning

Artificial Neural Network Supervised Learning. دكترمحسن كاهاني http://www.um.ac.ir/~kahani/. Back-propagation neural network. Learning in a multilayer network proceeds the same way as for a perceptron. A training set of input patterns is presented to the network.

1.25k views • 45 slides

Sarah’s weekend

Sarah’s weekend. What did Sarah do last weekend?. Sarah visited her grandparents last weekend. First, she played with her dog. Then, she ate apples from the garden. After that, she helped her grandma in the kitchen. They made an apple pie. Finally, Sarah went to bed at 10 o’clock.

343 views • 5 slides

Supervised by Dr. W.H.Siew Presented by Yu Wang

Wireless Data Acquisition System and its application for electrical emission measurement in Substations. Supervised by Dr. W.H.Siew Presented by Yu Wang. Introduction of electrical emission measurement in substations.

251 views • 11 slides

Needle Exchange and Supervised Consumption

Needle Exchange and Supervised Consumption. Northamptonshire October 2010 – September 2011 1 Full calendar year. Supervised Consumption. Since October 2010, 386 clients have been on the Supervised Consumption plan. Each client had an average of 74.05 supervisions (399 last year)

244 views • 12 slides

Fig S1

Hind III. Arabidopsis thaliana. RB. d35S. LUC. AP2. d35S. NPTII. LB. Probe for southern blot. Hind III. EcoR I. Hind III. EcoR I. EcoR I. 2141 bp. 5348 bp. 12640 bp. Hind III. EcoR I. Col-0 LUCH. Col-0 LUCH. 20kb. 10kb. 7kb. 5kb. 4kb. 3kb. 1.6kb. 1kb. 700bp. 500bp.

227 views • 8 slides

Semi-Supervised Learning

Semi-Supervised Learning. Jing xu. Slides. From: Xiaojin (Jerry) Zhu ---An associate professor in the Department of Computer Sciences at University of Wisconsin-Madison. Outline. What’s semi-supervised learning? Self-training algorithm

483 views • 23 slides

PRESENTED BY: Sr. MABEL NDABU MBATE NSEKA JOEL WEPNGONG SUPERVISED BY: Mr. CHO FEDERICK NCHANG

AN INTERNSHIP REPORT CARRIED OUT AT SAINT FRANCIS OF ASSISI CATHOLIC HOSPITAL, NTASEN, BAMENDA FROM THE 23 RD OF APRIL TO THE 18 TH OF MAY 2012. PRESENTED BY: Sr. MABEL NDABU MBATE NSEKA JOEL WEPNGONG SUPERVISED BY: Mr. CHO FEDERICK NCHANG BMLS (Hons) & Mr. NGWANUE WILFRED

318 views • 15 slides

Jeff Hind Exceptional Car Smash Repairs

Jeff Hind Smash Repairs is leading the way in the repair industry, providing quality vehicle repairs and professional customer service and utilizing innovative technology.

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