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  1. © २०२५ राष्ट्रीय प्रौद्योगिकी संस्थान कुरुक्षेत्र। सर्वाधिकार सुरक्षित।

    CSTC302 Randomized Algorithm and Probabilistic Analysis

    आवश्यकताएँ:

    इस कोर्स के लिए कोई आवश्यकता नहीं

    कोर्स प्रकृति: TC
    उद्देश्य:
  1. To develop the understanding of advanced algorithms.
  2. To study the complexity of advanced algorithms.
  3. Design new algorithms or modify existing ones for new applications and analyze the space & time efficiency of most algorithms.
  4. समान कोर्स:

    समन्वयक

    Dr. Sushil Kumar Madan
    Dr. Sushil Kumar Madan

    Professor

    skmadan@nitkkr.ac.in

    9416292144

    सामग्री

    ChariotHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorse

    परिणाम

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

    संदर्भ पुस्तकें

    1. Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein. Third Edition. MIT Press and PHI, 2010.

    2. Algorithm Design and Applications by Michael T. Goodrich and Roberto Tamassia, John Wiley publication.

    3. Randomized Algorithms by Rajeev Motwani, Prabhakar Raghavan, Cambridge University Press, 2014.

    4. Probability and Computing: Randomized Algorithms and Probabilistic Analysis, by Mitzenmacher and Upfal, Cambridge University Press, 2nd edition, 2017.

    5. The Design of Approximation Algorithms by David P. Williamson and David B. Shmoys, Cambridge University Press.

    6. Algorithm Design by Jon Kleinberg, Eva Tardos by Pearson publications.