Lectures related to Parameter Estimation for Spike Times

Optimization Techniques: Convexity in Machine Learning

Covers optimization techniques in machine learning, focusing on convexity and its implications for efficient problem-solving.

The Hidden Convex Optimization Landscape of Deep Neural Networks

Explores the hidden convex optimization landscape of deep neural networks, showcasing the transition from non-convex to convex models.

Specification of the deterministic part MOOC: Introduction to Discrete Choice Models

Explores the Box-Cox transform for modeling non-linear relationships between variables.

Optimisation in Energy Systems

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Optimization Methods: Convexity and Gradient Descent

Explores optimization methods, including convexity, gradient descent, and non-convex minimization, with examples like maximum likelihood estimation and ridge regression.

Box-Cox Transform

Explores the Box-Cox transform for investigating nonlinear specifications in models using a parameter lambda.

Gradient Descent Methods

Covers gradient descent methods for convex and nonconvex problems, including smooth unconstrained convex minimization, maximum likelihood estimation, and examples like ridge regression and image classification.

Convex Optimization Log in to Mediaspace to watch this video

Introduces convex optimization, focusing on the importance of convexity in algorithms and optimization problems.

KKT for convex problems and Slater's CQ Log in to Mediaspace to watch this video

Covers the KKT conditions and Slater's condition in convex optimization problems.

Optimization Techniques: Convexity and Algorithms in Machine Learning Log in to Mediaspace to watch this video

Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.

Conjugate Duality: Understanding Convex Optimization Log in to Mediaspace to watch this video

Explores conjugate duality in convex optimization, covering weak and supporting hyperplanes, subgradients, duality gap, and strong duality conditions.

Conjugate Duality: Envelope Representations and Subgradients Log in to Mediaspace to watch this video

Explores envelope representations, subgradients, and the duality gap in convex optimization.

Convex Optimization Tutorial: KKT Conditions Log in to Mediaspace to watch this video

Explores KKT conditions in convex optimization, covering dual problems, logarithmic constraints, least squares, matrix functions, and suboptimality of covering ellipsoids.

KKT and Convex Optimization Log in to Mediaspace to watch this video

Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.

Linear Models for Classification: Logistic Regression and SVM Log in to Mediaspace to watch this video

Covers linear models for classification, focusing on logistic regression and support vector machines.

Optimal Transport: Rockafellar Theorem Log in to Mediaspace to watch this video

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Convex Optimization: Dual Cones Log in to Mediaspace to watch this video

Explores dual cones, generalized inequalities, SDP duality, and KKT conditions in convex optimization.

Convex Sets: Mathematical Optimization Log in to Mediaspace to watch this video

Introduces convex optimization, covering convex sets, solution concepts, and efficient numerical methods in mathematical optimization.

Convex Optimization: Conjugate Duality Log in to Mediaspace to watch this video

Explores envelope representations, subgradients, conjugate functions, duality gap, and strong duality in convex optimization.

Convex Optimization: Theory and Applications Log in to Mediaspace to watch this video

Explores convex optimization theory, covering local and global minima, convex functions, and applications in various fields.