Computer vision and machine learning tasks can be modelled as the inference problems in an MRF-MAP formulation and can be reduced to minimizing a submodular function.
Input to the Most Navigable Path (MNP) problem consists of the following: (a) a road network represented as a directed graph, where each edge is associated with numeric attributes of cost and “navigability score” values; (b) a source and a destination and; (c) a budget value which denotes the maximum permissible cost of the solution.
Talk by Prof. Zubair Shafiq, University of California, Davis on "Online Privacy"
CS Faculty Seminar Series: Talk by Prof. Pushpendra Singh, IIITD on "HCI research", June 11, 4-5 pm
CS Faculty Seminar Series: Talk by Prof. Suman Banerjee, University of Wisconsin-Madison on "Edge Computing"
Talk by Dr. Soma Biswas, IISC on "Image and Video Analysis"
CSE Talk: Enabling Provable Security at Scale
CS Faculty Seminar Series: Talk by Prof. Mukesh Mohania, IIITD on "Blockchain for Education", June 18, 4-5 pm
CSE_Talk: Formal Proofs in Mathematics --- a Personal Perspective
Talk by Dr. Swadhin Pradhan, UT Austin on IoT and Networks