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Online Social Networks and Media
Online Social Networks and Media
by lindy-dunigan
Absorbing Random Walks. Link Prediction. Why does...
Testing the Cluster Structure of Graphs
Testing the Cluster Structure of Graphs
by pasty-toler
Christian Sohler. joint work with Artur Czumaj an...
Time series and error
Time series and error
by trish-goza
analysis . M. . A. Floyd. Massachusetts Institute...
Review Copyright 1997 by the American Psychological Association, Inc.
Review Copyright 1997 by the American Psychological Association, Inc.
by marina-yarberry
Exemplar-Based Random Walk Model of Speeded Classi...
1 Motivation
1 Motivation
by celsa-spraggs
Bluetooth-based malware is a continuing threat. E...
Efficient and Effective Local
Efficient and Effective Local
by lois-ondreau
Algorithms. for . Analyzing Massive Graphs. Yubao...
Error analysis
Error analysis
by myesha-ticknor
T. A. . Herring M. . A. . Floyd. Massach...
Error Models
Error Models
by olivia-moreira
Lecture 06. Thomas Herring. tah@mit.edu. . Issue...
Markov Chains Mixing Times
Markov Chains Mixing Times
by liane-varnes
Lecture 5. Omer . Zentner. 30.11.2016. Agenda . N...
Asset Price Bubbles
Asset Price Bubbles
by sherrill-nordquist
Anna . Scherbina. (2013). “Asset Price Bubbles...
Time series and error analysis with
Time series and error analysis with
by tatyana-admore
FOGMEx. (. tsfit. /. tsview. ), CATS and Hector....
Reverse Topk Search using Random Walk with Restart Adams Wei Yu Nikos Mamoulis Hao Su School of Computer Science Carnegie Mellon University Department of Computer Science The University of Hong Ko
Reverse Topk Search using Random Walk with Restart Adams Wei Yu Nikos Mamoulis Hao Su School of Computer Science Carnegie Mellon University Department of Computer Science The University of Hong Ko
by trish-goza
cmuedu nikoscshkuhk haosucsstanfordedu ABSTRACT Wi...
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
by faustina-dinatale
cmuedu Christos Faloutsos Carnegie Mellon Universi...
DATA MINING
DATA MINING
by olivia-moreira
LECTURE . 13. Absorbing Random walks. Coverage. A...
The Random Walk
The Random Walk
by phoebe-click
14 April 2015 Mapping the World's Prices 2015 ____...
Relevant Subgraph Extraction
Relevant Subgraph Extraction
by olivia-moreira
Longin Jan Latecki. Based on :. P. . Dupont. , J....
Graph Data Mining with Map-Reduce
Graph Data Mining with Map-Reduce
by liane-varnes
Nima Sarshar, Ph.D.. INTUIT . Inc. ,. Nima_sarsha...
MARKET EFFICIENCY
MARKET EFFICIENCY
by trish-goza
By: ELROY . DIMSON AND MASSOUD . MUSSAVIAN. Marma...
Chapter
Chapter
by tatyana-admore
12. Nonstationary Time Series Data and Cointegra...
Understanding the
Understanding the
by test
. Economics Nobel Prize 2013. Lasse . Heje. Ped...
Time series and error analysis
Time series and error analysis
by yoshiko-marsland
M. A. Floyd. Massachusetts Institute of Technolog...
Chapter 25: Joint Densities
Chapter 25: Joint Densities
by wilson
http://www.alexfb.com/cgi-bin/twiki/view/PtPhysics...
Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis
Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis
by leah
Junbo. Ma, . Xiaofeng. Zhu, . Defu. Yang, . Jia...
Probability in EECS Jean Walrand – EECS – UC Berkeley
Probability in EECS Jean Walrand – EECS – UC Berkeley
by tracy
Kalman. Filter. Kalman. Filter: Overview. Overvi...
Stave Assembly (A random walk through stave construction)
Stave Assembly (A random walk through stave construction)
by iris
Outline. I got asked to think of specifications fo...
Scaling At t ributed Network Embedding to Massive Graphs
Scaling At t ributed Network Embedding to Massive Graphs
by vivian
by: R. Yang. ,. . J. Shi. ,. . X. Xiao. ,. . Y....
Graph diffusion for network–based applications
Graph diffusion for network–based applications
by garcia
Sushmita Roy. sroy@biostat.wisc.edu. Computational...
Grouping What is grouping?
Grouping What is grouping?
by min-jolicoeur
K-means. Input: set of data points, k. Randomly p...
Brownian Motion for Financial Engineers
Brownian Motion for Financial Engineers
by test
Brownian motion. Wiener processes. A process. A p...
Social Media Recommendation based on People and Tags
Social Media Recommendation based on People and Tags
by liane-varnes
(SIGIR2010). IBM Research Lab. Ido. . Guy,Naama....
Relevant Subgraph Extraction
Relevant Subgraph Extraction
by ellena-manuel
Longin Jan Latecki. Based on :. P. . Dupont. , J....
Nearly-Linear Time Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs
Nearly-Linear Time Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs
by tawny-fly
Richard Peng. Georgia Tech. In collaboration with...
This Talk 1) Node embeddings
This Talk 1) Node embeddings
by tawny-fly
Map nodes to low-dimensional . embeddings. .. 2) ...
Benefits of Urban Farming
Benefits of Urban Farming
by lindy-dunigan
Econ2505. (Environmental Economics). Wei Li. Prof...
Error analysis T. A. Herring M
Error analysis T. A. Herring M
by giovanna-bartolotta
. A. . Floyd. Massachusetts Institute of Technolo...
Time series and error analysis with
Time series and error analysis with
by celsa-spraggs
FOGMEx. (. tsfit. /. tsview. ), CATS and Hector....
Time series and error
Time series and error
by liane-varnes
analysis . M. . A. Floyd. Massachusetts Institute...
Asset Price Bubbles
Asset Price Bubbles
by celsa-spraggs
Anna . Scherbina. (2013). “Asset Price Bubbles...