Class schedule - Spring 2023

Date Description Slides  HW/Project
Mon. 01/11 Traveling to DARPA QuICC kick-off meeting - No class    
Fri. 01/13 Introductions, class organization, networks, context, examples Block 1  
Mon. 01/16 Martin Luther King Jr. Day - No class    
Wed. 01/18 Traveling to McGill Bellairs Workshop - No class    
Mon. 01/23 Graphs, digraphs, degrees, movement, strong and weak connectivity Block 2a  
Wed. 01/25 Families, algebraic graph theory, data structures and algorithms    
Fri. 01/27 Inference, models, point and set estimates, hypothesis testing Block 2b  
Mon. 01/30 Tutorials on inference about a mean and linear regression    
Wed. 02/01 Graph visualization, stages of network mapping, mapping Science Block 3a  
Mon. 02/06 Large graph visualization, k-core decomposition, Internet mapping    
Wed. 02/8 Degree distributions, Erdos-Renyi random graphs and power laws Block 3b HW1 due
Mon. 02/13 Visualizing and fitting power laws, preferential attachment    
Wed. 02/15 Closeness, betweeness and eigenvector centrality measures Block 3c  
Mon. 02/20 Web search, hubs and authorities, Markov chains review    
Wed. 02/22 PageRank, fluid and graph random walk models, distributed algorithms  
Mon. 02/27 Cohesive subgroups, clustering, connectivity, assortativity mixing Block 3d  
Wed. 03/01 Strength of weak ties, community structure in networks Block 4a Proposal
Mon. 03/06 Spring Break - No class    
Wed. 03/08 Spring Break - No class    
Mon. 03/13 Girvan-Newmann method, hierarchical clustering, modularity    
Wed. 03/15 Modularity optimization, graph cuts, spectral graph partitioning    
Mon. 03/20 Sampling, Horvitz-Thompson estimation, graph sampling designs Block 4b  
Wed. 03/22 Network estimation of totals, groups size, degree distributions   HW2 due
Mon. 03/27 Random graph models, model-based estimation, significance, motifs Block 4c  
Wed. 03/29 Small-world,  preferential attachment and copying models    
Mon. 04/03 Exponential random graph models, construction and estimation   Prog. Report
Wed. 04/05 Topology inference, link prediction, scoring and classification Block 4d  
Mon. 04/10 Inference of association networks, tomographic inference    
Wed. 04/12 Nearest-neighbor prediction of processes, Markov random fields Block 5a  
Mon. 04/17 Graph kernel-regression, kernel design, protein function prediction  
Wed. 04/19 Diseases and the networks that transmit them, epidemic modeling Block 5b HW3 due
Mon. 04/24 Network flow data, routing and traffic matrices, gravity models Block 5c  
Wed. 04/26 Traffic matrix estimation, network flow costs, network kriging    
TBD In-class student project presentations   Presentation