Large margin nearest neighbor

k-NN 4: which distance function?

[http://bit.ly/k-NN] The nearest-neighbour algorithm is sensitive to the choice of distance function. Euclidean distance (L2) is a common choice, but it may lead to sub-optimal performance. We discuss Minkowski (p-norm) distance functions, which generalise the Euclidean distance, and can a

From playlist Nearest Neighbour Methods

StatsLearning Chapter 2 - part 2

From playlist ISLR Chapter 2: Statistical Learning

How to Compute a One Sided limit as x approaches from the right

In this video I will show you How to Compute a One Sided limit as x approaches from the right.

From playlist One-sided Limits

Given two similar triangles determine the values of x and y for the angles

👉 Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side

From playlist Similar Triangles

Convergence of nearest neighbor classification - Sanjoy Dasgupta

Members' Seminar Topic: Convergence of nearest neighbor classification Speaker: Sanjoy Dasgupta Affiliation: University of California, San Diego; Member, School of Mathematics Date: November 25, 2019 For more video please visit http://video.ias.edu

From playlist Mathematics

Dense Retrieval ❤ Knowledge Distillation

In this lecture we learn about the (potential) future of search: dense retrieval. We study the setup, specific models, and how to train DR models. Then we look at how knowledge distillation greatly improves the training of DR models and topic aware sampling to get state-of-the-art results.

From playlist Advanced Information Retrieval 2021 - TU Wien

Fundamental Machine Learning Algorithms - SVM & kNN

The code is accessible at https://github.com/sepinouda/Machine-Learning/

From playlist Machine Learning Course

Machine Learning Lecture 25 "Kernelized algorithms" -Cornell CS4780 SP17

Lecture Notes: http://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote13.html http://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote14.html

From playlist CORNELL CS4780 "Machine Learning for Intelligent Systems"

Using Bounds to Calculate Further Bounds

"Use lower and upper bounds within calculations to calculate a further lower/upper bound."

From playlist Number: Rounding & Estimation

What is similarity

👉 Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side

From playlist Similar Triangles

Some Recent Insights on Transfer Learning - Samory Kpotufe

Seminar on Theoretical Machine Learning Topic: Some Recent Insights on Transfer Learning Speaker: Samory Kpotufe Affiliation: Columbia University; Member, School of Mathematics Date: March 31, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

Using a set of points to determine if two triangles are similar to each other

👉 Learn how to determine whether two triangles are similar given the coordinate points of the vertices of the triangle. Two triangles are said to be equal when the corresponding angles of the triangles are congruent (equal) or when the corresponding side lengths are proportional. When give

From playlist Similar Triangles

How to write a proportion of lengths and corresponding angles for two triangles

👉 Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side

From playlist Similar Triangles

Machine Learning Lecture 17 "Regularization / Review" -Cornell CS4780 SP17

Lecture Notes: http://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote10.html

From playlist CORNELL CS4780 "Machine Learning for Intelligent Systems"

CSE 519 -- Lecture 26, Fall 2020

From playlist CSE 519 -- Fall 2020

Machine Learning Lecture 18 "Review Lecture II" -Cornell CS4780 SP17

From playlist CORNELL CS4780 "Machine Learning for Intelligent Systems"

Given an angle bisector find the missing length of similar triangles

👉 Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side

From playlist Similar Triangles

Introduction to Classification | Predictive Modeling and Machine Learning, Part 2

This video covers the basics of the most common machine learning classification models that you can tune to work with any number of predictor variables. Each has its advantages and disadvantages in terms of accuracy and training speed. The only way to know which one works best on a particu

From playlist Predictive Modeling and Machine Learning

Using Similarity and proportions to find the missing values

👉 Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side

From playlist Similar Triangles

From Classical Statistics to Modern ML: the Lessons of Deep Learning - Mikhail Belkin

Workshop on Theory of Deep Learning: Where next? Topic: From Classical Statistics to Modern ML: the Lessons of Deep Learning Speaker: Mikhail Belkin Affiliation: Ohio State University Date: October 16, 2019 For more video please visit http://video.ias.edu

From playlist Mathematics