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Cmu Faloutsos published presentations and documents on DocSlides.

Construction Cost Estimating

Construction Cost Estimating

  • conchita-marotz
  • 0 Slides

Class . #8 . - Masonry. Prof. Ralph V. Locurcio, ...

FacingImbalancedDataRecommendationsfortheUseofPerformanceMetricsL

FacingImbalancedDataRecommendationsfortheUseofPerformanceMetricsL

  • alida-meadow
  • 100 Slides

laszlo.jeni@ieee.org , ftorre@cs.cmu.edu 2Universi...

FLORINA BALCAN

FLORINA BALCAN

  • trish-goza
  • 100 Slides

1 MARIA - Carnegie Mellon University Pittsburgh, P...

Causal Modeling of Observational Cost Data

Causal Modeling of Observational Cost Data

  • briana-ranney
  • 37 Slides

: A Ground-Breaking use of Directed Acyclic Grap...

Introduction to Computer Security

Introduction to Computer Security

  • karlyn-bohler
  • 64 Slides

David Brumley. dbrumley@cmu.edu. Carnegie Mellon ...

Automated Problem Diagnosis for Production Systems

Automated Problem Diagnosis for Production Systems

  • marina-yarberry
  • 15 Slides

Soila P. Kavulya. Scott Daniels (AT&T. ), . K...

Proxy

Proxy

  • giovanna-bartolotta
  • 25 Slides

Web . & Concurrency. Ian Hartwig. 15/18-213 -...

Dryplt

Dryplt

  • pamella-moone
  • 1 Slides

Electrical and Computer Engineering Department. C...

Proxy Recitation

Proxy Recitation

  • stefany-barnette
  • 37 Slides

Jeffrey Liu. Recitation 13: November . 23, 2015. ...

Pooh’s

Pooh’s

  • test
  • 29 Slides

. Enclyclopedia. (2007). Rating: fun . Think a...

The FroYo Effect: Using small incentives to achieve a

The FroYo Effect: Using small incentives to achieve a

  • danika-pritchard
  • 0 Slides

51% university-wide response rate. Office of Inst...

Stat-XFER: A General Framework for Search-based Syntax-driven MT

Stat-XFER: A General Framework for Search-based Syntax-driven MT

  • tawny-fly
  • 0 Slides

Alon Lavie. Language Technologies Institute. Carn...

Challenges in Public Safety and Security

Challenges in Public Safety and Security

  • vamput
  • 24 Slides

Cindy Smail, Loss Control Consultant. Marsh Risk C...

Rathijit SeN David A. Wood

Rathijit SeN David A. Wood

  • volatilenestle
  • 36 Slides

Reuse-based . Online Models for Caches. 6/20/2013....

Pati Kravetz Associate Director for Experiential Learning and Student Employment

Pati Kravetz Associate Director for Experiential Learning and Student Employment

  • bikershomemaker
  • 24 Slides

Agenda. Enhancing Student Success and Educational...

Master of Information Systems ManagementBIDAAccelerated Master146sP

Master of Information Systems ManagementBIDAAccelerated Master146sP

  • paige
  • 3 Slides

Eligibility Academic requirement CMU undergraduat...

Recitation Nov 9, 2022 Information Theory

Recitation Nov 9, 2022 Information Theory

  • beatrice
  • 9 Slides

Cover and Thomas. Lecture Material from Aarti Sing...

Speech Recognition with CMU Sphinx

Speech Recognition with CMU Sphinx

  • singh
  • 27 Slides

Srikar Nadipally. Hareesh . Lingareddy. What is Sp...

The Challenge of DNS and IP Mappings

The Challenge of DNS and IP Mappings

  • grace3
  • 60 Slides

By: Dr. T V Gopal, Professor, DCSE, CEG Campus, An...

15-744: Computer Networking

15-744: Computer Networking

  • mila-milly
  • 31 Slides

L-17 . DNS. This lecture. Domain Name System (DNS)...

CenterPiece Subgraphs Problem Denition and Fast Solutions Hanghang Tong Carnegie

CenterPiece Subgraphs Problem Denition and Fast Solutions Hanghang Tong Carnegie

  • phoebe-click
  • 10 Slides

cmuedu Christos Faloutsos Carnegie Mellon Universi...

Fast Random Walk with Restart and Its Applications Hanghang Tong Carnegie Mellon University htongcs

Fast Random Walk with Restart and Its Applications Hanghang Tong Carnegie Mellon University htongcs

  • faustina-dinatale
  • 10 Slides

cmuedu Christos Faloutsos Carnegie Mellon Universi...

Large Human Communication Networks Patterns and a UtilityDriven Generator Nan Du Christos Faloutsos Bai Wang Leman Akoglu Carnegie Mellon University Beijing University of Posts and Telecommunications

Large Human Communication Networks Patterns and a UtilityDriven Generator Nan Du Christos Faloutsos Bai Wang Leman Akoglu Carnegie Mellon University Beijing University of Posts and Telecommunications

  • tatiana-dople
  • 9 Slides

cmuedu wangbaibupteducn ABSTRACT Given a real and ...

Connection Subgraphs in Social Networks Christos Faloutsos Kevin S

Connection Subgraphs in Social Networks Christos Faloutsos Kevin S

  • ellena-manuel
  • 12 Slides

McCurley Andrew Tomkins Abstract connection subgr...

Costeffective Outbreak Detection in Networks Jure Leskovec Carnegie Mellon University Andreas Krause Carnegie Mellon University Carlos Guestrin Carnegie Mellon University Christos Faloutsos Carnegie

Costeffective Outbreak Detection in Networks Jure Leskovec Carnegie Mellon University Andreas Krause Carnegie Mellon University Carlos Guestrin Carnegie Mellon University Christos Faloutsos Carnegie

  • alida-meadow
  • 10 Slides

We present a general methodology for near optimal...

Fast BestEffort Pattern Matching in Large Attributed G

Fast BestEffort Pattern Matching in Large Attributed G

  • debby-jeon
  • 10 Slides

cmuedu Christos Faloutsos Tina EliassiRad Lawrence...

Node Similarity, Graph Similarity and Matching:

Node Similarity, Graph Similarity and Matching:

  • briana-ranney
  • 63 Slides

Theory and Applications. Danai Koutra (CMU). Tina...

ADAGE: A software package for analyzing

ADAGE: A software package for analyzing

  • pasty-toler
  • 100 Slides

graph evolution Mary McGlohon, Christos Faloutsos ...

Network Topology

Network Topology

  • tatyana-admore
  • 12 Slides

Julian Shun. On Power-Law Relationships of the In...

Making Diffusion Work for You

Making Diffusion Work for You

  • natalia-silvester
  • 77 Slides

B. Aditya Prakash. Computer Science. Virginia Tec...

Dynamical Processes on Large Networks

Dynamical Processes on Large Networks

  • test
  • 0 Slides

B. . Aditya. . Prakash. http://www.cs.cmu.edu/~b...

HADIFastDiameterEstimationandMininginMassiveGraphswithHadoopUKang3Char

HADIFastDiameterEstimationandMininginMassiveGraphswithHadoopUKang3Char

  • obrien
  • 26 Slides

KeywordsdiametergraphhadoopSymbolDe2nitionGagraphn...

AEG Automatic Exploit Generation Thanassis Avgerinos Sang Kil Cha Brent Lim Tze Hao and David Brumley Carnegie Mellon University Pittsburgh PA thanassis sangkilc brentlim dbrumley cmu

AEG Automatic Exploit Generation Thanassis Avgerinos Sang Kil Cha Brent Lim Tze Hao and David Brumley Carnegie Mellon University Pittsburgh PA thanassis sangkilc brentlim dbrumley cmu

  • cheryl-pisano
  • 18 Slides

edu Abstract The automatic exploit generation chal...

TIE Principled Reverse Engineering of Types in Binary Programs JongHyup Lee Thanassis Avgerinos and David Brumley Carnegie Mellon University jonglee thanassis dbrumley cmu

TIE Principled Reverse Engineering of Types in Binary Programs JongHyup Lee Thanassis Avgerinos and David Brumley Carnegie Mellon University jonglee thanassis dbrumley cmu

  • conchita-marotz
  • 18 Slides

edu Abstract A recurring problem in security is re...

AdjacencyF aithfulness and Conserv ativ Causal Inference Joseph Ramsey eter Spirtes Departmen of Philosoph Carnegie Mellon Univ ersit Pittsburgh jdramsey psz andrew

AdjacencyF aithfulness and Conserv ativ Causal Inference Joseph Ramsey eter Spirtes Departmen of Philosoph Carnegie Mellon Univ ersit Pittsburgh jdramsey psz andrew

  • pasty-toler
  • 8 Slides

cmu e du Jiji Zhang Division of Humanities and So ...

An Analysis of Private Browsing Modes in Modern Browsers Gaurav Aggarwal Elie Bursztein Stanford University Collin Jackson CMU Dan Boneh Stanford University Abstract We study the security and privacy

An Analysis of Private Browsing Modes in Modern Browsers Gaurav Aggarwal Elie Bursztein Stanford University Collin Jackson CMU Dan Boneh Stanford University Abstract We study the security and privacy

  • jane-oiler
  • 15 Slides

We 64257rst pro pose a clean de64257nition of the...

Introduction to Coding Theory CMU Spring Notes GilbertVarshamov bound January Lecturer Venkatesan Guruswami Scribe Venkatesan Guruswami Asymptotically good codes and GilbertVarshamov bound We beg

Introduction to Coding Theory CMU Spring Notes GilbertVarshamov bound January Lecturer Venkatesan Guruswami Scribe Venkatesan Guruswami Asymptotically good codes and GilbertVarshamov bound We beg

  • test
  • 5 Slides

Suppose we are interested in ary codes not necess...

Introduction to Coding Theory CMU Spring Notes List

Introduction to Coding Theory CMU Spring Notes List

  • pamella-moone
  • 10 Slides

Now we turn to list decoding arbitrary received w...

Which Edges Matter Aayush Bansal RI CMU aayushbcmu

Which Edges Matter Aayush Bansal RI CMU aayushbcmu

  • pasty-toler
  • 8 Slides

edu Adarsh Kowdle Microsoft adkowdlemicrosoftcom D...

AN EARLYHISTORYOF HINDSIGHT RESEARCHBaruchFischhoffThefirststudiesofhi

AN EARLYHISTORYOF HINDSIGHT RESEARCHBaruchFischhoffThefirststudiesofhi

  • faustina-dinatale
  • 5 Slides

AddresscorrespondencetoBaruchFischhoff,Departmento...

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