Learn · An Introduction to Probability in Computing
Lecture 17 of 24Week 3
Tail Bounds I - Median via Sampling
Prof. John Augustine · IIT Madras
Credits and licence
- From
- An Introduction to Probability in Computing, IIT Madras (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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- Tweens profiles and older. How courses are placed
All the lectures
- Introduction to Probability - A box of chocolates
- Introduction to Probability - Axiomatic Approach to Probability Theory
- Introduction to Probability - Verifying Matrix Multipilication ( Statement,Algorithm & Independence )
- Introduction to Probability - Verifying Matrix Multipilication ( Correctness & Law of Total Probability )
- Introduction to Probability - How Strong is your Network?
- Introduction to Probability - How to Understand the World? Play with it!
- Tutorial 1
- Tutorial 2
- Discrete Random Variables - Basic Definitions
- Discrete Random Variables - Linearity of Expectation & Jensens Inequality
- Discrete Random Variables - Conditional Expectation I
- Discrete Random Variables - Conditional Expectation II
- Discrete Random Variables - Geometric Random Variables & Collecting Coupons
- Discrete Random Variables - Randomized Selection
- Tail Bounds I - Markov's Inequality
- Tail Bounds I - The Second Moment,Variance & Chebyshev's Inequality
- Tail Bounds I - Median via Sampling
- Tail Bounds I - Median via Sampling - Analysis
- Tail Bounds I - Moment Generating Functions and Chernoff Bounds
- Tail Bounds I - Parameter Estimation
- Tail Bounds I - Control Group Selection
- Applications of Tail Bounds - Routing in Sparse Networks
- Applications of Tail Bounds - Analysis of Valiant's Rounting
- Applications of Tail Bounds - Random Graphs