Matrix Calculus version1, version2  and version3

Lesson 2. Spectral Characterization of Graphs
               Graph power in Wolfram Mathworld
               Cheeger inequality proofs (Miceli)
               Ernesto Estrada's Homepage and Estrada Index (Wikipedia). 

               Estrada Videolecture at S+SSPR'10. 
               Yeast Interactome Project Homepage

Lesson 3. Graph Cuts and Normalized Cuts
               MATLAB Normalized Cuts Segmentation Code
               
Lesson 4. Heat Kernel and Diffusion Processes
               Taylor expansions of exponentials
               Talk on Birkhoff Complexity in ICPR'08
               Talk on Flow Complexity in Gbr'09

               Videos in MOV: Illustrating Flow complexity in small line and star graphs                

Lesson 5. Regularization Kernels and Kernel Evaluation.

Lesson 6. Graph Embedding.
               MANIfold Learning MATdemo LAB
               Link to original paper on ISOMAP

Lesson 7. The Random Walker. 

               Graph Analysis Toolbox and Random Walker implementation at Leo Grady webpage. 

               Videloecture of Leo Grady at Gbr'07. 

Lesson 8. Selection of Spectral Features

MATLAB CODE:

Graph Theory and Aplications (GTA) Version 0. Developed by Miguel Angel Lozano and Francisco Escolano (University of Alicante) 
Graph Theory and Aplications (GTA) Version 1. Developed by Miguel Angel Lozano and Francisco Escolano (University of Alicante)
Graph Theory and Aplications (GTA) Version 2. Developed by Miguel Angel Lozano and Francisco Escolano (University of Alicante)
 

Lesson 1. Practice on Graph Spectra. PracLesson1Exer.m, PracLesson1bExer.m
Lesson 2. Graph Characterization. PracLesson2Exer.m
                MAT file with interactomes. Lesson2.mat and practice on Estrada Index PracLesson2bExer.m
Lesson 3. Practice in Graph Cuts Lesson3Exer.m        
Lesson 4. Practice in Heat Kernels and Diffusion Processes Lesson4Exer.m    
Lesson 5. Practice in Regularization Kernels Lesson5Exer.m    and extension  Lesson5ExerB.m
Lesson 6. Practice in Graph Embedding Lesson6Exer.m 

Lesson 7. Practice in The Random Walker Lesson7Exer.m