Class schedule

Date Description Slides  HW/Project
Thu. 01/19 Introductions, class organization, networks, context, examples Block 1  
Tue. 01/24 Graphs, digraphs, degrees, movement, strong and weak connectivity Block 2a  
Thu. 01/26 Families, algebraic graph theory, data structures and algorithms
Tue. 01/31 Inference, models, point and set estimates, hypothesis testing Block 2b  
Thu. 02/02 Tutorials on inference about a mean and linear regression    
Fri. 02/03 Graph visualization, stages of network mapping, mapping Science Block 3a  
Tue. 02/07 Large graph visualization, k-core decomposition, Internet mapping    
Thu. 02/09 Degree distributions, Erdos-Renyi random graphs and power laws Block 3b HW1 due
Tue. 02/14 Traveling to GSP Workshop - No class    
Thu. 02/16 Traveling to GSP Workshop - No class    
Tue. 02/21 Visualizing and fitting power laws, preferential attachment    
Thu. 02/23 Closeness, betweeness and eigenvector centrality measures Block 3c Proposal
Fri. 02/24 Web search, hubs and authorities, Markov chains review  
Tue. 02/28 PageRank, fluid and graph random walk models, distributed algorithms    
Thu. 03/02 Cohesive subgroups, clustering, connectivity, assortativity mixing Block 3d  
Fri. 03/03 Strength of weak ties, community structure in networks Block 4a  
Fri. 03/03 Girvan-Newmann method, hierarchical clustering, modularity    
Tue. 03/07 Traveling to ICASSP'17 - No class    
Thu. 03/09 Traveling to ICASSP'17 - No class    
Tue. 03/14 Spring break - No class    
Thu.  03/16 Spring break - No class    
Tue. 03/21 Modularity optimization, graph cuts, spectral graph partitioning    
Thu. 03/23 Sampling, Horvitz-Thompson estimation, graph sampling designs Block 4b HW2 due
Tue. 03/28 Network estimation of totals, groups size, degree distributions
Thu. 03/30 Random graph models, model-based estimation, significance, motifs Block 4c Prog. Report
Tue. 04/04 Small-world,  preferential attachment and copying models    
Thu. 04/06 Exponential random graph models, construction and estimation    
Tue. 04/11 Topology inference, link prediction, scoring and classification Block 4d  
Thu. 04/13 Inference of association networks, tomographic inference    
Tue. 04/18 Nearest-neighbor prediction of processes, Markov random fields Block 5a  
Thu. 04/20 Graph kernel-regression, kernel design, protein function prediction   HW3 due
Tue. 04/25 Diseases and the networks that transmit them, epidemic modeling Block 5b  
Thu. 04/27 Network flow data, routing and traffic matrices, gravity models Block 5c  
Tue. 05/02 Traffic matrix estimation, network flow costs, network kriging
Fri. 05/05 In-class student project presentations Presentation