Information theory | Entropy and information
In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable given that the value of another random variable is known. Here, information is measured in shannons, nats, or hartleys. The entropy of conditioned on is written as . (Wikipedia).
Using a tree diagram to find the conditional probability
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
How to find the conditional probability from a tree diagram
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Finding the conditional probability from a tree diagram
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Learn to find the or probability from a tree diagram
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Using a contingency table to find the conditional probability
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Determining the conditional probability from a contingency table
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Finding the conditional probability from a two way frequency table
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
How to find the probability of consecutive events
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Equidistribution of Measures with High Entropy for General Surface Diffeomorphisms by Omri Sarig
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
Topics in Combinatorics lecture 11.1 --- Subadditivity of entropy and Shearer's lemma
A useful rule that is satisfied by entropy is that if X_1,...,X_n are random variables, then H[X_1,...,X_n] is at most H[X_1]+...+H[X_n]. Shearer's lemma is a generalization of this, where one compares H[X_1,...,X_n] by a suitable weighted average of joint entropies of the form H[X_i : i i
From playlist Topics in Combinatorics (Cambridge Part III course)
Entropy accumulation - O. Fawzi - Workshop 2 - CEB T3 2017
Omar Fawzi / 23.10.17 Entropy accumulation We ask the question whether entropy accumulates, in the sense that the operationally relevant total uncertainty about an n-partite system A=(A1,…An) corresponds to the sum of the entropies of its parts Ai. The Asymptotic Equipartition Property i
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
General strong polarization - Madhu Sudan
Computer Science/Discrete Mathematics Seminar I Topic: Locally symmetric spaces: pp-adic aspects Speaker: General strong polarization Affiliation: Harvard University Date: December 4, 2017 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Harmonic Measures and Poisson Boundaries for Random Walks on Groups (Lecture 3) by Giulio Tiozzo
PROGRAM: PROBABILISTIC METHODS IN NEGATIVE CURVATURE ORGANIZERS: Riddhipratim Basu (ICTS - TIFR, India), Anish Ghosh (TIFR, Mumbai, India), Subhajit Goswami (TIFR, Mumbai, India) and Mahan M J (TIFR, Mumbai, India) DATE & TIME: 27 February 2023 to 10 March 2023 VENUE: Madhava Lecture Hall
From playlist PROBABILISTIC METHODS IN NEGATIVE CURVATURE - 2023
Nexus Trimester - Iftach Haitner (Tel Aviv University) - Leo Reyzin (Boston University) 2/3
Computational Analogues of Entropy 2/3 Iftach Haitner (Tel Aviv University) Leo Reyzin (Boston University) MArch 21, 2016 Abstract: If you see a cryptographic hash of my password, how can I quantify your uncertainty about the password? Entropy – a traditional measure of uncertainty – is
From playlist Nexus Trimester - 2016 - Secrecy and Privacy Theme
How to find the conditional probability from a contingency table
👉 Learn how to find the conditional probability of an event. Probability is the chance of an event occurring or not occurring. The probability of an event is given by the number of outcomes divided by the total possible outcomes. Conditional probability is the chance of an event occurring
From playlist Probability
Nexus Trimester - Terence Chan (University of South Australia) - 1
Fundamental aspects of information inequalities 1/3 Terence Chan (University of South Australia) February 25, 2016 Abstract: Information inequalities are very important tools and are often needed to characterise fundamental limits and bounds in many communications problems such as data t
From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme
David Sutter: "A chain rule for the quantum relative entropy"
Entropy Inequalities, Quantum Information and Quantum Physics 2021 "A chain rule for the quantum relative entropy" David Sutter - IBM Zürich Research Laboratory Abstract: The chain rule for the conditional entropy allows us to view the conditional entropy of a large composite system as a
From playlist Entropy Inequalities, Quantum Information and Quantum Physics 2021