Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Probability Theory: Markov's Theorem
Graph Chatbot
Related lectures (34)
Probability and Statistics
Covers topics related to probability and statistics, including finding specific values and significant events.
Generalization Error
Explores tail bounds, information bounds, and maximal leakage in the context of generalization error.
Probability and Statistics: Fundamental Theorems
Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.
Probability and Statistics: Independence and Conditional Probability
Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.
Variance and Covariance: Properties and Examples
Explores variance, covariance, and practical applications in statistics and probability.
Conditional Probability: Prediction Decomposition
Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.
Probability and Statistics
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
All of Probability: LLN, CLT, Chernoff and PAC bound
Covers the Law of Large Numbers, Central Limit Theorem, Chernoff bounds, and PAC bounds in probability theory.
Probability and Statistics
Introduces key concepts in probability and statistics, illustrating their application through various examples and emphasizing the importance of mathematical language in understanding the universe.
Probabilistic Methods in Combinatorics
Log in to Mediaspace to watch this video
Covers probabilistic methods in combinatorics, monochromatic edges, 2-colorable graphs, and good 2-colorings.
Poisson Paradigm: Qualitative / Quantitative
Log in to Mediaspace to watch this video
Covers the Poisson Paradigm, including the First/Second Moment Method and Martingales, discussing dependency graphs and Chernoff bounds.
Poisson Paradigm: Dependency Measures
Log in to Mediaspace to watch this video
Explores the Poisson Paradigm and dependency measures in ordered pairs and graphs.
Interlacing Polynomials
Log in to Mediaspace to watch this video
Explores interlacing polynomials, real rooted theorems, and pseudo-probabilistic methods in polynomial analysis.
Martingales: More Theory
Log in to Mediaspace to watch this video
Explores the theory of martingales, including conditional expectations, Chernoff bounds, and Azuma's inequality.
Graph Theory: Girth and Independence
Log in to Mediaspace to watch this video
Covers girth, independence, probability, union bound, sets, and hypergraph recoloring.
Martingales and Conditional Expectations
Log in to Mediaspace to watch this video
Explores Brun's Sieve, Martingales, and Conditional Expectations in probability theory.
Expander Graphs: Properties and Eigenvalues
Log in to Mediaspace to watch this video
Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.
Pseudorandomness: Theory and Applications
Log in to Mediaspace to watch this video
Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.
Interlacing Families and Ramanujan Graphs
Log in to Mediaspace to watch this video
Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.
Percolation Theory: FKG Inequality
Log in to Mediaspace to watch this video
Explores the FKG inequality in percolation theory and the reverse FKG theorem.
Previous
Page 1 of 2
Next
