Classes

Class offered at Syracuse EECS:

1. 1. CIS 563: Intro to Data Science (every Fall) – Graduate Level
      • Sample Topics: Classification, Clustering, Large-Scale Hashing, Dimensionality Reduction, Mining Time-Series, Mining Data Streams, Mining Graphs
   2. CIS 700: Social Media Mining (Springs) – Graduate Level
      • Sample Topics: Network Measures, Network Models (Data-Driven and Model-based), Community Analysis, Information Diffusion, Influence and Homophily
   3. CIS 700: Spectral Graph Theory (Springs) – Graduate Level
      • • Sample Topics: Spectral theory, Laplacian and Graph Drawing, known spectrums, Cauchy’s Interlacing Theorem, Graph coloring, Isoperimetric Ratio, Conductance, Cheeger Constant, cuts, random walks and rates of convergence, Expanders and bounds, Effective resistance, sparsifications
   4. CIS 700:  Machine Learning with Graphs (Springs) – Graduate Level
      • • Sample Topics: Spectral theory, Laplacian and Graph Drawing, known spectrums, Cauchy’s Interlacing Theorem, Graph coloring, Isoperimetric Ratio, Conductance, Cheeger Constant, cuts, random walks and rates of convergence, Expanders and bounds, Effective resistance, sparsifications