'Simplest case' diaporamas de présentation

Data Gathering Chapter 6

Data Gathering Chapter 6. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A. Rating. Area maturity Practical importance Theoretical importance. First steps Text book.

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Agreement dynamics on interaction networks: the Naming game

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Clustering

Clustering. Introduction K-means clustering Hierarchical clustering: COBWEB . Outline. Classification vs. Clustering. Classification: Supervised learning: Learns a method for predicting the instance class from pre-labeled (classified) instances. Clustering. Unsupervised learning:

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Knowledge Representation

Knowledge Representation. Outline: Output - Knowledge representation. Decision tables Decision trees Decision rules Rules involving relations Instance-based representation Prototypes, Clusters. witten&eibe. Output: representing structural patterns.

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Knowledge Representation

Knowledge Representation. Outline: Output - Knowledge representation. Decision tables Decision trees Decision rules Rules involving relations Instance-based representation Prototypes, Clusters. witten&eibe. Output: representing structural patterns.

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Engineering Optimization

Concepts and Applications. Engineering Optimization. Fred van Keulen Matthijs Langelaar CLA H21.1 A.vanKeulen@tudelft.nl. Optimization problem. Negative null form. Model. Definition. Checking. Recap / overview. Special topics. Linear / convex problems. Sensitivity analysis.

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12.15 Multiple Substituent Effects

12.15 Multiple Substituent Effects. O. CH 3. O. O. CH 3 COCCH 3. CH 3. The Simplest Case. all possible EAS sites may be equivalent. CH 3. CCH 3. AlCl 3. +. CH 3. 99%. CH 3. Br 2. Fe. NO 2. Another Straightforward Case. CH 3. Br.

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12.15 Multiple Substituent Effects

12.15 Multiple Substituent Effects. O. CH 3. CH 3. O. O. CCH 3. AlCl 3. +. CH 3 COCCH 3. CH 3. CH 3. 99%. The Simplest Case. all possible EAS sites may be equivalent. CH 3. CH 3. Br. Br 2. Fe. NO 2. NO 2. 86-90%. Another Straightforward Case.

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Knowledge Representation

Knowledge Representation. Outline: Output - Knowledge representation. Decision tables Decision trees Decision rules Rules involving relations Instance-based representation Prototypes, Clusters. witten&eibe. Output: representing structural patterns.

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Statistical NLP Winter 2008

Statistical NLP Winter 2008. Lecture 2: Language Models. Roger Levy ?? to Dan Klein, Jason Eisner, Joshua Goodman, Stan Chen. Language and probability. Birth of computational linguistics: 1950s & machine translation

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Effects of the superfluid neutrons on the dynamics of the crust

Effects of the superfluid neutrons on the dynamics of the crust. Lars Samuelsson, Nordita (Stockholm) Nils Andersson Kostas Glampedakis. [Karlovini & LS, CQG 20 3613 (2003), Carter & LS CQG 23 5367 (2006) LS & Andersson, MNRAS 374 256 (2007)]. Umberto Boccioni: Elasticity , 1912 .

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Decision Support Algorithms for Port of Entry Inspection

Decision Support Algorithms for Port of Entry Inspection. Fred S. Roberts DIMACS Center, Rutgers University In collaboration with Los Alamos National Laboratory Preliminary Support: Office of Naval Research. Port of Entry Inspection Algorithms. Goal : Find ways to intercept illicit

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Joint Modeling of Entity-Entity Links and Entity-Annotated Text

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L-4 constant acceleration and free fall

L-4 constant acceleration and free fall. REVIEW Acceleration is the change in velocity with time Galileo showed that i n the absence of air resistance, all objects, regardless of their mass, fall to earth with the same acceleration g

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Inheritance

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Quantifying Effectiveness of Failure Prediction and Response in HPC Systems: Methodology and Example

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" A short guide to breeding and taming highly intelligent ChIPMunks "

Using ChIPMunk for motif discovery - quick-start guide - slide 3:10 - preparing data slide 11:12 - running ChIPMunk slide 13:14 - do I need ChIPHorde ?. " A short guide to breeding and taming highly intelligent ChIPMunks ". Some basic questions.

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Enlargements

Enlargements. Last one of these - honest. Most complicated transformation. Can make the shape larger or smaller in size. The position of the centre of enlargement determines where the image will be, the scale factor determines the size. Keywords.

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Section 7.3 - Work

Section 7.3 - Work. Work is a measure of the cumulative effect of a force in moving an object from one position to another. Pushing a box full of books down the hallway. Raising a bucket full of water from the bottom of a well. Pumping oil from the ground.

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