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Announcements: projects 805 students: Project proposals are due S

Announcements: projects 805 students: Project proposals are due S

  • karlyn-bohler
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un 10/1. . If you’d like to work with 605 stud...

Introduction to Parallel Programming

Introduction to Parallel Programming

  • pamella-moone
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& Cluster Computing. Stupid Compiler Tricks. ...

Supercomputing in Plain English

Supercomputing in Plain English

  • kittie-lecroy
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Stupid Compiler Tricks. Henry Neeman, Director. D...

EECE 310: Software Engineering

EECE 310: Software Engineering

  • tatiana-dople
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Final Exam Review. About the final exam. Comprehe...

GraphLab : how I understood it

GraphLab : how I understood it

  • aaron
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with sample code. Aapo. . Kyrola. ,. Carnegie Me...

Type Inference with Run-time Logs

Type Inference with Run-time Logs

  • ellena-manuel
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Ravi Chugh. Motivation: Dynamic Languages. Dynami...

An Improved Probabilistic Graphical Model for the Detection of Internal Layers from Polar Radar Im

An Improved Probabilistic Graphical Model for the Detection of Internal Layers from Polar Radar Im

  • danika-pritchard
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Jerome E. . Mitchell. 2013 NASA Earth and Space S...

Matteo Macchini Student meeting – June 2014

Matteo Macchini Student meeting – June 2014

  • aaron
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Motion control design for the new BWS. Matteo Mac...

Scalable Parallel Computing

Scalable Parallel Computing

  • yoshiko-marsland
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on . Clouds. Thilina. . Gunarathne. (tgunarat@i...

1 Planning under Uncertainty

1 Planning under Uncertainty

  • aaron
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Today’s Topics. Sequential Decision Problems. M...

RV-Monitor: Efficient Parametric Runtime Verification

RV-Monitor: Efficient Parametric Runtime Verification

  • test
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with Simultaneous Properties. Qingzhou. Luo, Yi ...

Sec:5.2 The Bisection Method

Sec:5.2 The Bisection Method

  • liane-varnes
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Sec:5.2 . The Bisection Method. The . root-findi...

Spelling Correction for Advertising:

Spelling Correction for Advertising:

  • mitsue-stanley
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How “Noise” Can Help. Silviu. . Cucerzan. Mi...

1 Agile Methodology and Scrum

1 Agile Methodology and Scrum

  • lindy-dunigan
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What is Agile ? . Agile proponents believe. Curre...

Avoiding Synchronization in Geometric

Avoiding Synchronization in Geometric

  • cheryl-pisano
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Multigrid. Erin . C. . Carson. 1. Samuel Williams...

© 2014 Project Lead The Way, Inc.

© 2014 Project Lead The Way, Inc.

  • debby-jeon
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Roles of Variables with Examples in Scratch. A va...

ARS REE Administrative Portal

ARS REE Administrative Portal

  • tawny-fly
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Modernization:. Overview . of the New Portal. Kar...

CSE 554 Lecture 6: Fairing

CSE 554 Lecture 6: Fairing

  • alida-meadow
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Fall 2016. Review. Iso. -contours in grayscale im...

Rutgers May 25, 2011 TexPoint fonts used in EMF.

Rutgers May 25, 2011 TexPoint fonts used in EMF.

  • tatyana-admore
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Read the TexPoint manual before you delete this b...

Trade-offs in Explanatory

Trade-offs in Explanatory

  • lois-ondreau
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Model Learning . DCAP Meeting. Madalina Fite...

Avoiding Synchronization in Geometric

Avoiding Synchronization in Geometric

  • alida-meadow
  • 0 Slides

Multigrid. Erin . C. . Carson. 1. Samuel Williams...

A Step-Wise Approach to Elicit Triangular Distributions

A Step-Wise Approach to Elicit Triangular Distributions

  • liane-varnes
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Presented by:. Marc Greenberg. Cost Analysis Divi...

Strings Chapter 6 Python for Everybody

Strings Chapter 6 Python for Everybody

  • karlyn-bohler
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www.py4e.com. String Data Type. A string is a seq...

Iteration Looping in Java

Iteration Looping in Java

  • pasty-toler
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Tedious…. A better way. public void lines(. int...

Iterative Methods for Linear Systems

Iterative Methods for Linear Systems

  • test
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Goal is to solve the system . Can use direct or i...

Curriculum Vitae Management

Curriculum Vitae Management

  • olivia-moreira
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System . Taming . the CV Data Beast. Robert (Bob)...

Signal processing and Networking for Big Data

Signal processing and Networking for Big Data

  • giovanna-bartolotta
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Applications. Lecture 5. : Sparse optimization. Z...

Artificial Intelligence

Artificial Intelligence

  • conchita-marotz
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(CS 370D). L. Maram ALShablan. 1. Uninformed Sear...

Loop/Iteration structures & Booleans

Loop/Iteration structures & Booleans

  • luanne-stotts
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Iteration. Iteration just means we keep doing the...

On the Power of Belief Propagation:

On the Power of Belief Propagation:

  • yoshiko-marsland
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A Constraint Propagation Perspective. Rina . Dech...

On Abstraction Refinement for Program Analyses in

On Abstraction Refinement for Program Analyses in

  • jane-oiler
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Datalog. Xin Zhang. , Ravi . Mangal. , . Mayur. ...

Future of Computing II: What’s So Special About Big Learning?

Future of Computing II: What’s So Special About Big Learning?

  • min-jolicoeur
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. 15-213 / 18-213 / 15-513: Introduction to Comp...

Accessibility Add-in Microsoft Office 2007

Accessibility Add-in Microsoft Office 2007

  • phoebe-click
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The Problem . (in case you’ve forgotten). It is...

While loops Iteration We’ve seen many places where repetition is necessary in a problem.

While loops Iteration We’ve seen many places where repetition is necessary in a problem.

  • karlyn-bohler
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We’ve been using the for loop for that purpose....

Team Members: Sushant

Team Members: Sushant

  • briana-ranney
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Ahuja. . Cassio. . Caposso. . Sameep. . Mohta...

Iterative Methods for Linear Systems

Iterative Methods for Linear Systems

  • karlyn-bohler
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Goal is to solve the system . Can use direct or i...

Trade-offs in Explanatory

Trade-offs in Explanatory

  • mitsue-stanley
  • 0 Slides

Model Learning . DCAP Meeting. Madalina Fite...

Wavefield imaging and tomography with the energy norm

Wavefield imaging and tomography with the energy norm

  • kittie-lecroy
  • 0 Slides

Daniel Rocha & Paul Sava. Center for Wave Phe...

What’s So Special about

What’s So Special about

  • phoebe-click
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Big Learning?. A Distributed Systems Perspective....

What’s So Special about

What’s So Special about

  • tatiana-dople
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Big Learning?. A Distributed Systems Perspective....

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