National Institute of Technology, Kurukshetra

To develop the understanding of advanced algorithms.

To study the complexity of advanced algorithms.

Design new algorithms or modify existing ones for new applications and analyze the space & time efficiency of most algorithms.

Content

Apply basic concepts of approximation, randomization, and distributed computing in algorithmic contexts.
Design randomized parallel algorithms, approximation, and distributed algorithms that run fast or return the correct output with high probability.
Derive good upper bounds for the expected running time of advanced algorithms.
Apply the probabilistic method to show the existence of certain combinatorial objects.

Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein. Third Edition. MIT Press and PHI, 2010.
Algorithm Design and Applications by Michael T. Goodrich and Roberto Tamassia, John Wiley publication.
Randomized Algorithms by Rajeev Motwani, Prabhakar Raghavan, Cambridge University Press, 2014.
Probability and Computing: Randomized Algorithms and Probabilistic Analysis, by Mitzenmacher and Upfal, Cambridge University Press, 2nd edition, 2017.
The Design of Approximation Algorithms by David P. Williamson and David B. Shmoys, Cambridge University Press.
Algorithm Design by Jon Kleinberg, Eva Tardos by Pearson publications.