Machine Learning 机器学习代写

CS861: Theoretical Foundations of Machine Learning Lecture 9 – 25/09/2023 University of Wisconsin–Madison, Fall 2023 Lecture 09: Hypothesis testing and Le Cam’s method Lecturer: Kirthevasan Kandasamy Scribed by: Haoyue Bai, Ying Fu Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only …

CS861: Theoretical Foundations of Machine Learning Lecture 9 25 09 2023 Univer Read More »

CS861: Theoretical Foundations of Machine Learning Lecture 8 – 09/22/2023 University of Wisconsin–Madison, Fall 2023 Lecture 08: Introduction to Minimax Optimality Lecturer: Kirthevasan Kandasamy Scribed by: Xindi Lin, Zhihao Zhao Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the …

CS861: Theoretical Foundations of Machine Learning Lecture 8 09 22 2023 Univer Read More »

CS861: Theoretical Foundations of Machine Learning Lecture 3 – 09/11/2023 University of Wisconsin–Madison, Fall 2023 Lecture 03: Introduction to Radamacher complexity Lecturer: Kirthevasan Kandasamy Scribed by: Justin Kiefel, Albert Dorador Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the …

CS861: Theoretical Foundations of Machine Learning Lecture 3 09 11 2023 Univer Read More »

CS861: Theoretical Foundations of Machine Learning Lecture 13 – 10/04/2023 University of Wisconsin–Madison, Fall 2023 Lecture 13: Varshamov-Gilbert lemma, Nonparametric regression Lecturer: Kirthevasan Kandasamy Scribed by: Elliot Pickens, Yuya Shimizu Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the …

CS861: Theoretical Foundations of Machine Learning Lecture 13 10 04 2023 Unive Read More »