Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
University of Maryland
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
Ohio State University
Dense subgraph discovery
Google Research
Large-Scale Graph Mining
IBM T.J. Watson Research Center
Streaming Graph Partitioning in the Planted Partition Model
ACM Conference on Online Social Networks (COSNâ€™15)
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
Stanford University
Scalable Large Near-Clique Detection in Large-Scale Networks
Signals, Inference, and Networks (SINE) Seminar
University of Illinois Urbana-Champaign
Dense subgraph discovery
Data-driven Algorithmics
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015)
Dense subgraph discovery
Tutorial at 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015)
Scalable dense subgraph discovery
Random Structures and Algorithms (RSA), July ’15
Scalable dense subgraph discovery
International Symposium on Optimization (ISMP), July ’15
Space- and Time-Efficient Algorithms for Maintaining Dense Subgraphs on One-Pass Dynamic Streams
STOC 2015, June ’15
Scalable dense subgraph discovery
University of Cyprus, June ’15
Provably Fast Inference of Latent Features from Networks
24th International World Wide Web Conference (WWW 2015), May’15
The k-clique Densest Subgraph Problem
24th International World Wide Web Conference (WWW 2015), May’15
Algorithmic Analysis of Large Datasets
Universitat Pompeu Fabra, May ’15
Modern Data Mining Algorithms
Draper Laboratory, December ’14
Algorithmic Analysis of Large Datasets
SEAS Harvard University, November ’14
Youtube video
Algorithmic Analysis of Large Datasets (pptx)
Brown University, May ’14
Host: Philip Klein
Large-Scale Graph Mining
Imperial College London, May ’14
Host: Moez Draief
Algorithmic Analysis of Large Datasets
Google NYC, April ’14
Host: Vahab Mirrokni
Mathematical Techniques for Modeling and Analyzing Large Graphs (pdf)
Aalto Science Institute, January ’14, Helsinki
Modeling Intratumor Gene Copy Number Heterogeneity using Fluorescence in Situ Hybridization data (pptx, pdf)
WABI ’13, September ’13, Nice
Fennel: Streaming Graph Partitioning for Massive Scale Graphs (pdf)
MASSIVE ’13, September ’13, Nice
Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees (pptx, pdf)
KDD ’13, August ’13, Chicago
Mathematical and Algorithmic Analysis of Network and Biological data
Thesis Defense, Carnegie Mellon University, May 2013
Processing, Analyzing and Mining Big Graph Data
Machine learning lunch seminar, Carnegie Mellon University, April 2013
Video
Random Graphs and Complex Networks
Guest lecture, TELCOM2125: Network Science and Analysis
Host: Konstantinos Pelechrinis
April 2013
Mathematical and Algorithmic Analysis of Biological data and Networks
Abstract
Brown University, April 2013
Host: Eli Upfal
Fennel: Streaming Graph Partitioning for Massive Scale Graphs
Microsoft Research, Cambridge UK, November 2012
Host: Milan Vojnovic
On Certain Topics on Networks and Optimization: Theorems, Algorithms and Applications
Yahoo! Research Barcelona, Barcelona, August 2012
Host: Aris Gionis
On Certain Properties of Random Apollonian Networks (pptx, pdf)
WAW 2012, June 2012, Halifax
Triangle Counting and Vertex Similarity
Canadian Mathematical Society, December 2011, Toronto
Invited Speaker
High Degree Vertices, Eigenvalues and Diameter of Random Apollonian Networks
15th International Conference on Random Structures and Algorithms RSA 2011, Atlanta
Counting Triangles in Real-World Networks
SIAM Conference on Computational Science and Engineering (CSE11), Reno
Invited Speaker
Approximate Dynamic Programming using Halfspace Queries and Multiscale Monge Analysis (pptx)
SODA 2011, San Francisco
Approximate Dynamic Programming and Denoising aCGH data (pptx)
Machine Learning Seminar 2011, Carnegie Mellon University
Video
Efficient Triangle Counting via Degree-based Partitioning (pptx)
Machine Learning Seminar 2011, Carnegie Mellon University
Video
Approximate Dynamic Programming and Denoising aCGH data (pptx)
ACO Seminar 2011, Carnegie Mellon University
Efficient Triangle Counting via Degree-based Partitioning (pptx)
ACO Seminar 2011, Carnegie Mellon University
Efficient Triangle Counting via Degree-based Partitioning (pptx)
WAW 2010, Stanford University
The Determinant of Random Bernoulli Matrices
Discrete Math 21701, Carnegie Mellon University
Approximate Dynamic Programming
Carnegie Mellon University
Unmixing of Tumor States in aCGH data
Carnegie Mellon University
Data Mining with MapReduce: Graph and Tensor Algorithms with Applications
Master Thesis, Carnegie Mellon University
MACH: Fast Randomized Tensor Decompositions
SIAM Data Mining 2010, Columbus OH
Algorithms for Denoising aCGH Data
MLD Speaking Skills, Carnegie Mellon University
Welcome Talk (MLD Open House) (welcome.ppt)
MLD Open House, Carnegie Mellon University
Spectral Counting of Triangles in Power-Law Networks via Element-Wise Sparsification
ASONAM 2009, Athens
DOULION: Counting Triangles in Massive Graphs with a Coin
KDD 2009, Paris
Approximate Triangle Counting
Poster Presentation, Machine Learning Summer School 2009, Chicago
Basics of Spectral Graph Theory
Carnegie Mellon University, Paris
On Polygonal Numbers and Fermat's Conjecture
Additive Number Theory, Carnegie Mellon University
Graph Mining
Guest Lecture 15-826 Multimedia Databases and Data Mining (CMU)
Fast Counting of Triangles in Large Real Networks without counting: Algorithms and Laws (pps)
IEEE Data Mining (ICDM), 2008 Italy
Fast Counting of triangles in large networks: Algorithms and laws (ppt)
Theory Seminar of Rensselaer Polytechnic Institute
Host: Petros Drineas
Invited Talk
Two heads better than one: pattern discovery in time-evolving multi-aspect data (ppt)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
(ECML-PKDD 2008), 2008 Belgium