Lectures related to Decision theory

Decisions under Risk and Uncertainty: Behavioral Economics Insights

Delves into decision-making under risk, bounded rationality, prospect theory, and framing, with insights from behavioral economics.

Decision Theory: Risk and Inference

Explores decision theory, risk functions, and inference in statistical analysis.

Statistical Theory: Cramér-Rao Bound & Hypothesis Testing

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Ingredients of choice theory

Covers the theoretical foundations of choice theory and its key components for decision making.

Introduction to Supervised Learning and Decision Theory

Covers supervised learning, decision theory, risk minimization, and goal achievement.

Choice Theory: Theoretical Foundations

Covers the theoretical foundations of choice theory, decision makers, alternatives, attributes, decision rules, utility, and behavioral assumptions.

Statistical Theory: Decision Theory Framework

Explores the Decision Theory Framework in Statistical Theory, viewing statistics as a random game with key concepts like admissibility, minimax rules, and Bayes rules.

Likelihood Ratio Test: Detection & Estimation

Covers the likelihood ratio test for detection and estimation in statistical analysis.

Discriminant Analysis: Bayes Rule

Covers the Bayes discriminant rule for allocating individuals to populations based on measurements and prior probabilities.

Classification Detection

Covers binary hypothesis testing and decision functions in specific scenarios.

Decision Theory: Risk and Hypothesis Testing

Covers decision theory, risk functions, and hypothesis testing in statistical inference.

Bayesian Decision Theory: Utility, Risk, and Classification

Covers Bayesian decision theory, cost functions, classification, and decision rules.

SAT Solver: Optimization Techniques

Explores optimization techniques in SAT solvers and their application in Sudoku solving.

Detection & Estimation

Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.

Factored Representations: Planning Efficiency

Explores factored representations for planning, focusing on reducing complexity and improving efficiency through separate feature modeling.

Introduction to Convexity

Introduces the key concepts of convexity and its applications in different fields.

Boolean Satisfiability Problem: Solving Techniques

Explores the Boolean Satisfiability Problem and the Davis-Putnam-Logemann-Loveland algorithm, along with modern SAT solvers and efficient solving techniques.

Maximum Likelihood Estimation

Covers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.

Decision Tree Classification

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

Sexing Guppy Fish: Bayesian Inference and Decision Rules

Covers the sexing of guppy fish using Bayesian inference and decision rules.