1. |
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Introduction. Probability axioms and random variables |
PDF/PMF and CDF |
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Introduction. Probability axioms and random variables |
PDF/PMF and CDF |
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2. |
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Function of random variables Definitions of convergence |
Convergence in probability, convergence with probability 1, convergence in distribution |
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Function of random variables Definitions of convergence |
Convergence in probability, convergence with probability 1, convergence in distribution |
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3. |
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Useful inequalities and law of large numbers. Central limit theorem |
Markov inequality, Chebyshev
inequality, Chernoff bound |
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Useful inequalities and law of large numbers. Central limit theorem |
Markov inequality, Chebyshev
inequality, Chernoff bound |
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4. |
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Bernoulli process and Poisson process |
Definitions and properties of Bernoulli and Poisson processes |
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Bernoulli process and Poisson process |
Definitions and properties of Bernoulli and Poisson processes |
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5. |
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Discrete-time Markov chains and steady-state behavior |
Definition, state transition probability, Markov property |
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6. |
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Mixing time and midterm review |
Role of second largest eigenvalues and midterm review |
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7. |
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M/M/1 queues |
Poisson arrival and exponential service, analysis of waiting times |
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M/M/1 queues |
Poisson arrival and exponential service, analysis of waiting times |
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8. |
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M/G/1 queues and Pollaczek- Khinchin formula |
Definition of M/G/1 queue and derivation of Pollaczek-Khinchin
formula |
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M/G/1 queues and Pollaczek- Khinchin formula |
Definition of M/G/1 queue and derivation of Pollaczek-Khinchin
formula |
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9. |
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Estimation theory and Expectation- Maximization (EM) algorithm |
Bayesian estimation, expectation maximization |
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Estimation theory and Expectation- Maximization (EM) algorithm |
Bayesian estimation, expectation maximization |
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10. |
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Hidden Markov models (HMM) |
Modeling uncertain pheonomena using hidden Markov models |
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Hidden Markov models (HMM) |
Modeling uncertain pheonomena using hidden Markov models |
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11. |
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Counting processes and Renewal processes |
Definition of counting and renewal processes, and analysis |
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Counting processes and Renewal processes |
Definition of counting and renewal processes, and analysis |
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12. |
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Randomized algorithms |
Applications of probability and
stochastic processes to randomized algorithms |
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Randomized algorithms |
Applications of probability and
stochastic processes to randomized algorithms |
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13. |
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Randomized algorithms and course review |
Applications of probability and
stochastic processes to randomized algorithms |
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Randomized algorithms and course review |
Applications of probability and
stochastic processes to randomized algorithms |
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