Lectures related to Multi-arm Bandits

Confidence Intervals: Student, Asymptotic Wald

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Optimality in Statistical Inference

Delves into the duality between confidence intervals and hypothesis tests, emphasizing the importance of precision and accuracy in estimation.

Statistical Inference: Approximate Critical Values and Confidence Intervals

Covers the construction of confidence intervals and approximate critical values in statistical inference.

VaR Model Evaluation

Discusses Monte Carlo VaR accuracy, confidence intervals, backtesting, and multivariate distributions.

Estimation and Confidence Intervals

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Statistical Models: Basics & Applications

Covers statistical concepts like probability, estimation, hypothesis testing, and confidence intervals for mathematicians.

Stable Laws and Limit Theorems

Explores stable laws, limit theorems, and random variable properties.

Generalization Error

Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.

Interspike Intervals & Renewal Processes MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores interspike intervals, renewal processes, and escape noise experiments in neuronal dynamics.

Interval Estimation: Method of Moments

Covers the method of moments for estimating parameters and constructing confidence intervals based on empirical moments matching distribution moments.

Concept of Proof in Mathematics

Delves into the concept of proof in mathematics, emphasizing the importance of evidence and logical reasoning.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Multi-arm Bandits: Exploration vs Exploitation

Explores the balance between exploration and exploitation in multi-arm bandit algorithms.

Uncertainty and Significant Figures

Explains confidence intervals, margin of error, pivots, and significant figures in statistical estimation.

Fourier Series: Understanding Periodicity and Coefficients

Explores t-periodic functions in Fourier series, discussing intervals, propositions, and variable changes for coefficient calculation and series convergence.

Understanding Statistics & Experimental Design

Explores t-tests, confidence intervals, ANOVA, and hypothesis testing in statistics, emphasizing the importance of avoiding false discoveries and understanding the logic behind statistical tests.

Integral Change of Variable Formula

Explores the integral change of variable formula and its applications in calculus.

Concentration Inequalities

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Multi-arm Bandits: Upper Confidence Bound

Covers the Upper Confidence Bound algorithm for multi-arm bandits.

Composition of Applications in Mathematics

Explores the composition of applications in mathematics and the importance of understanding their properties.