Selected talks:

• Shannon 100th birth anniversary, Oct. 2016, The dual geometry of Shannon information and its applications slides video
• MLSS 2015, Computational Information Geometry for Machine Learning (2h27m video)

Overview of results:

• Bregman proximity queries
• Centroids and statistical centroids
• Clustering (hard clustering) and learning mixtures (soft clustering)

Introductory papers:

• Cramer-Rao Lower Bound and Information Geometry, Connected at Infinity II: On the work of Indian mathematicians (R. Bhatia and C.S. Rajan, Eds.), special volume of Texts and Readings In Mathematics (TRIM), Hindustan Book Agency, 2013
   
  
• Pattern learning and recognition on statistical manifolds: An information-geometric review, In International Workshop on Similarity-Based Pattern Recognition (pp. 1-25). Springer Berlin Heidelberg.

Short memo notes:

• α-centroids and α-barycenters of probability measures (note)
• Legendre transformation and information geometry (note)
• Limits from l'Hôpital rule: Shannon entropy as limit cases of Rényi and Tsallis entropies (note)
• Harris-Stephens' combined corner/edge detector (note