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Judy Qiu xqiu@indiana.edu

Judy Qiu xqiu@indiana.edu

  • kittie-lecroy
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http. ://. SALSA. hpc.indiana.edu. . School of ...

Failover Clustering: What's new in Windows Server 2012 R2

Failover Clustering: What's new in Windows Server 2012 R2

  • calandra-battersby
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John Marlin. Senior Support Escalation Engineer. ...

Core Methods in Educational

Core Methods in Educational

  • faustina-dinatale
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Data Mining. HUDK4050. Fall 2015. Quick question....

Als je opbrengst niet alleen af hangt van je eigen keuzes

Als je opbrengst niet alleen af hangt van je eigen keuzes

  • test
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Speltheorie. Vanuit een opbrengstenmatrix. Twee ...

Stressing Out: Bitcoin “Stress Testing”

Stressing Out: Bitcoin “Stress Testing”

  • alida-meadow
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K. haled. . Baqer. , Danny . Yuxing. Huang, Dam...

Failover Clustering: Pro Troubleshooting in Windows Server 2008 R2

Failover Clustering: Pro Troubleshooting in Windows Server 2008 R2

  • test
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John Marlin. Senior Support Escalation Engineer. ...

Distributional Semantic Models

Distributional Semantic Models

  • kittie-lecroy
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in Lexical Typology:. Constructing a typological ...

Recommending Similar Items

Recommending Similar Items

  • briana-ranney
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at Large Scale. Jay . Katukuri. Merchandising Tea...

Online Social Networks and Media

Online Social Networks and Media

  • faustina-dinatale
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Graph Partitioning (cuts, spectral clustering, de...

Clustered data - grids Aksel Thomsen

Clustered data - grids Aksel Thomsen

  • lois-ondreau
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Erik Sommer. Clustered data - grids. Aksel Thomse...

Why do we want a good ratio anyway?

Why do we want a good ratio anyway?

  • ellena-manuel
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. Approximation stability and proxy objectives. ...

Old core : The horizon of Herodotus

Old core : The horizon of Herodotus

  • faustina-dinatale
  • 0 Slides

Europe as Eastern-Mediterranean coastlands. The C...

MSMESB: Explain What It Means: Communication, Visualization, Presentation and Storytelling for Ana

MSMESB: Explain What It Means: Communication, Visualization, Presentation and Storytelling for Ana

  • natalia-silvester
  • 0 Slides

Results. Visualization . of Textual . Data Storyt...

Quantum II (PHYS 4410)

Quantum II (PHYS 4410)

  • myesha-ticknor
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Lecture . 10. Degenerate perturbation theory. H...

Machine Learning Overview

Machine Learning Overview

  • yoshiko-marsland
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Tamara Berg. CS 560 Artificial Intelligence. Many...

Clustering Ensembles Using Ant Algorithms

Clustering Ensembles Using Ant Algorithms

  • liane-varnes
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Javad. . Azimi. , Paul Cull, . Xiaoli. Fern. ...

Computational and Communication Complexity in Massively Parallel

Computational and Communication Complexity in Massively Parallel

  • tatiana-dople
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Computation. Grigory. . Yaroslavtsev. (Indiana U...

Core Methods in Educational

Core Methods in Educational

  • tatiana-dople
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Data Mining. EDUC545-010. Spring2017. Discussion ...

Generalized Principal Component Analysis

Generalized Principal Component Analysis

  • liane-varnes
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René Vidal. Center for Imaging Science. Institut...

Finding Hidden Intelligence with Predictive Analysis of Data Mining

Finding Hidden Intelligence with Predictive Analysis of Data Mining

  • myesha-ticknor
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Rafal Lukawiecki. Strategic Consultant, Project B...

Near-Optimal LP Rounding for Correlation Clustering

Near-Optimal LP Rounding for Correlation Clustering

  • conchita-marotz
  • 0 Slides

Grigory. . Yaroslavtsev. http://grigory.us. . W...

Towards an Extractive Summarization System Using Sentence Vectors and Clustering

Towards an Extractive Summarization System Using Sentence Vectors and Clustering

  • marina-yarberry
  • 0 Slides

John . Cadigan. , David Ellison, Ethan Roday. Sys...

CSE-473/573 Dimensionality Reduction

CSE-473/573 Dimensionality Reduction

  • debby-jeon
  • 0 Slides

Devansh Arpit. Motivation. Abundance of data. Req...

Clustering Linear and Nonlinear Manifolds

Clustering Linear and Nonlinear Manifolds

  • faustina-dinatale
  • 0 Slides

René Vidal. Center for Imaging Science. Institut...

Wine Clustering Ling Lin

Wine Clustering Ling Lin

  • yoshiko-marsland
  • 0 Slides

Contents. Motivation. Data. Dimension. ality. . ...

BMC - Technologies &

BMC - Technologies &

  • aaron
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Approaches with SP2013. Bill Baer. Senior Product...

Maria- Florina Balcan 10/17/2016

Maria- Florina Balcan 10/17/2016

  • natalia-silvester
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Clustering. . Unsupervised Learning. Clustering, ...

Wine Clustering Ling Lin

Wine Clustering Ling Lin

  • kittie-lecroy
  • 0 Slides

Contents. Motivation. Data. Dimension. ality. . ...

Introduction to Data Mining

Introduction to Data Mining

  • myesha-ticknor
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12-. 1. Data mining is a rapidly growing field of...

Clock Clustering and IO Optimization for 3D Integration

Clock Clustering and IO Optimization for 3D Integration

  • debby-jeon
  • 0 Slides

Samyoung Bang*, Kwangsoo Han. ‡. ,. Andrew B. ....

Clustering (3) Center-based algorithms

Clustering (3) Center-based algorithms

  • kittie-lecroy
  • 0 Slides

Fuzzy . k. -means. Self-organizing maps. Evaluati...

Data Mining Applications

Data Mining Applications

  • lois-ondreau
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in Robotics Engineering. Blink . Sakulkueakulsuk....

bias to small & dense cluster

bias to small & dense cluster

  • alida-meadow
  • 0 Slides

. observed for . average association. . in ...

Guang can Liu Robust Subspace Clustering in High Dimension:

Guang can Liu Robust Subspace Clustering in High Dimension:

  • debby-jeon
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A Deterministic Result. 1. st. Annual Workshop o...

Algorithms for NP-hard Optimization Problems

Algorithms for NP-hard Optimization Problems

  • test
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and Cluster Analysis. Dissertation Defense. Nan L...

Introduction to Graph

Introduction to Graph

  • pamella-moone
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Cluster Analysis. Outline. Introduction to Cluste...

Scaleable Entity Resolution

Scaleable Entity Resolution

  • conchita-marotz
  • 0 Slides

Kunho Kim. Why We Need Entity Resolution?. Why We...

3.1 Clustering Finding a good clustering of the points is a fundamental

3.1 Clustering Finding a good clustering of the points is a fundamental

  • kittie-lecroy
  • 0 Slides

issue in . computing a representative simplicial ...

Parallel Deterministic Annealing Clustering and its Application

Parallel Deterministic Annealing Clustering and its Application

  • myesha-ticknor
  • 0 Slides

to . LC-MS Data Analysis.  . October 7 2013. . ...

Chapter 9 Classification and

Chapter 9 Classification and

  • test
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Clustering. Classification and Clustering. Classi...

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