(ML 14.3) Markov chains (discrete-time) (part 2)
Definition of a (discrete-time) Markov chain, and two simple examples (random walk on the integers, and a oversimplified weather model). Examples of generalizations to continuous-time and/or continuous-space. Motivation for the hidden Markov model.
From playlist Machine Learning
(ML 18.4) Examples of Markov chains with various properties (part 1)
A very simple example of a Markov chain with two states, to illustrate the concepts of irreducibility, aperiodicity, and stationary distributions.
From playlist Machine Learning
(ML 18.5) Examples of Markov chains with various properties (part 2)
More examples of (discrete) Markov chains, to illustrate the concepts of irreducibility, aperiodicity, and stationary distributions.
From playlist Machine Learning
(ML 14.2) Markov chains (discrete-time) (part 1)
Definition of a (discrete-time) Markov chain, and two simple examples (random walk on the integers, and a oversimplified weather model). Examples of generalizations to continuous-time and/or continuous-space. Motivation for the hidden Markov model.
From playlist Machine Learning
Markov Chains Clearly Explained! Part - 1
Let's understand Markov chains and its properties with an easy example. I've also discussed the equilibrium state in great detail. #markovchain #datascience #statistics For more videos please subscribe - http://bit.ly/normalizedNERD Markov Chain series - https://www.youtube.com/playl
From playlist Markov Chains Clearly Explained!
Prob & Stats - Markov Chains (27 of 38) Absorbing Markov Chain: Stable Matrix=? Ex. 2
Visit http://ilectureonline.com for more math and science lectures! In this video I will find the stable transition matrix (4x4) in an absorbing Markov chain. Next video in the Markov Chains series: http://youtu.be/u89Sd514EDI
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Prob & Stats - Markov Chains: Method 2 (30 of 38) Basics***
Visit http://ilectureonline.com for more math and science lectures! In this video I will demonstrate the basics of method 2 of solving Markov chain problems. Next video in the Markov Chains series:
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Absorption probabilities in finite Markov chains
Code discussed in this video: https://gist.github.com/Nikolaj-K/f660de8cec4551cfb879479470625e20 Wikipedia: https://en.wikipedia.org/wiki/Absorbing_Markov_chain How's life?
From playlist Programming
Markov Chains: n-step Transition Matrix | Part - 3
Let's understand Markov chains and its properties. In this video, I've discussed the higher-order transition matrix and how they are related to the equilibrium state. #markovchain #datascience #statistics For more videos please subscribe - http://bit.ly/normalizedNERD Markov Chain ser
From playlist Markov Chains Clearly Explained!
Regenerative sequences and processes and MCMC by Krishna Athreya
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Regularized Functional Inequalities and Applications to Markov Chains by Pierre Youssef
PROGRAM: TOPICS IN HIGH DIMENSIONAL PROBABILITY ORGANIZERS: Anirban Basak (ICTS-TIFR, India) and Riddhipratim Basu (ICTS-TIFR, India) DATE & TIME: 02 January 2023 to 13 January 2023 VENUE: Ramanujan Lecture Hall This program will focus on several interconnected themes in modern probab
From playlist TOPICS IN HIGH DIMENSIONAL PROBABILITY
Regenerative Stochastic Processes by Krishna Athreya
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
The Poisson boundary: a qualitative theory (Lecture 2) by Vadim Kaimanovich
Program Probabilistic Methods in Negative Curvature ORGANIZERS: Riddhipratim Basu, Anish Ghosh and Mahan Mj DATE: 11 March 2019 to 22 March 2019 VENUE: Madhava Lecture Hall, ICTS, Bangalore The focal area of the program lies at the juncture of three areas: Probability theory o
From playlist Probabilistic Methods in Negative Curvature - 2019
Localization schemes: A framework for proving mixing bounds for Markov chains - Ronen Eldan
Computer Science/Discrete Mathematics Seminar II Topic: Localization schemes: A framework for proving mixing bounds for Markov chains Speaker: Ronen Eldan Affiliation: von Neumann Fellow, School of Mathematics Date: March 15, 2022 Two recent and seemingly-unrelated techniques for proving
From playlist Mathematics
The Poisson boundary: a qualitative theory by Vadim Kaimanovich
Program Probabilistic Methods in Negative Curvature ORGANIZERS: Riddhipratim Basu, Anish Ghosh and Mahan Mj DATE: 11 March 2019 to 22 March 2019 VENUE: Madhava Lecture Hall, ICTS, Bangalore The focal area of the program lies at the juncture of three areas: Probability theory o
From playlist Probabilistic Methods in Negative Curvature - 2019
On a local Lyapunov function for the McKean-Vlasov dynamics by Rajesh Sundaresan
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Cécile Mailler : Processus de Pólya à valeur mesure
Résumé : Une urne de Pólya est un processus stochastique décrivant la composition d'une urne contenant des boules de différentes couleurs. L'ensemble des couleurs est usuellement un ensemble fini {1, ..., d}. A chaque instant n, une boule est tirée uniformément au hasard dans l'urne (noton
From playlist Probability and Statistics
Prob & Stats - Markov Chains (8 of 38) What is a Stochastic Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a stochastic matrix. Next video in the Markov Chains series: http://youtu.be/YMUwWV1IGdk
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Martin Boundaries of Random Walks on Relatively Hyperbolic Groups by Debanjan Nandi
PROGRAM : ERGODIC THEORY AND DYNAMICAL SYSTEMS (HYBRID) ORGANIZERS : C. S. Aravinda (TIFR-CAM, Bengaluru), Anish Ghosh (TIFR, Mumbai) and Riddhi Shah (JNU, New Delhi) DATE : 05 December 2022 to 16 December 2022 VENUE : Ramanujan Lecture Hall and Online The programme will have an emphasis
From playlist Ergodic Theory and Dynamical Systems 2022