Frequency Domain Interpretation of Sampling
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Analysis of the effect of sampling a continuous-time signal in the frequency domain through use of the Fourier transform.
From playlist Sampling and Reconstruction of Signals
Statistics - Types of sampling
This video will show you the many ways that you could sample. Remember to look for those small differences such as if you are breaking things into groups first. For more videos visit http://www.mysecretmathtutor.com
From playlist Statistics
Quantization and Coding in A/D Conversion
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Real sampling systems use a limited number of bits to represent the samples of the signal, resulting in quantization of the signal amplitude t
From playlist Sampling and Reconstruction of Signals
What is multistage sampling? Examples, including real life examples. Advantages and disadvantages. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creator-spring.com/listing/sam
From playlist Sampling
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Overview of non probability sampling; advantages and disadvantages, types. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creator-spring.com/listing/sampling-in-statistics
From playlist Sampling
An overview of the most popular sampling methods used in statistics. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creator-spring.com/listing/sampling-in-statistics
From playlist Sampling
MixUp augmentation for image classification - Keras Code Examples
This video explains another awesome Keras Code Example, this time implementing a cutting-edge technique for Data Augmentation. In my view, what makes MixUp so interesting is that it can be applied in data domains outside of images and Computer Vision. Say for NLP or Physiological data, it
From playlist Keras Code Examples
Reconstruction and the Sampling Theorem
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Analysis of the conditions under which a continuous-time signal can be reconstructed from its samples, including ideal bandlimited interpolati
From playlist Sampling and Reconstruction of Signals
mixup: Beyond Empirical Risk Minimization (Paper Explained)
Neural Networks often draw hard boundaries in high-dimensional space, which makes them very brittle. Mixup is a technique that linearly interpolates between data and labels at training time and achieves much smoother and more regular class boundaries. OUTLINE: 0:00 - Intro 0:30 - The prob
From playlist Papers Explained
AI Weekly Update - June 16th, 2021 (#35!)
Content Links Below: Generative Models as a Data Source for Multi-View Representation Learning: https://arxiv.org/pdf/2106.05258.pdf Learning to See by Looking at Noise: https://arxiv.org/pdf/2106.05963.pdf Knowledge Distillation: A Good Teacher is Patient and Consistent: https://arxiv.org
From playlist AI Research Weekly Updates
High-frequency Component Helps Explain the Generalization of Convolutional Neural Networks | AISC
For slides and more information on the paper, visit https://ai.science/e/high-frequency-component-helps-explain-the-generalization-of-convolutional-neural-networks--HVAyCyALo5x54CyWLPXv Speaker: Haohan Wang; Host: Ali El-Sharif Motivation: Computer Vision implementations based on Convol
From playlist Explainability and Ethics
Research Methods 1: Sampling Techniques
In this video, I discuss several types of sampling: random sampling, stratified random sampling, cluster sampling, systematic sampling, and convenience sampling. The figures presented are adopted/adapted from: https://www.pngkey.com/detail/u2y3q8q8e6o0u2t4_population-and-sample-graphic-de
From playlist Research Methods
Manifold Mixup: Better Representations by Interpolating Hidden States
Standard neural networks suffer from problems such as un-smooth classification boundaries and overconfidence. Manifold Mixup is an easy regularization technique that rectifies these problems. It works by interpolating hidden representations of different data points and then train them to p
From playlist Deep Learning Architectures
DSI | Simultaneous Feature Selection and Outlier Detection Using Mixed-Integer Programming
Simultaneous Feature Selection and Outlier Detection Using Mixed-Integer Programming with Optimality Guarantees Biomedical research is increasingly data rich, with studies comprising ever growing numbers of features. The larger a study, the higher the likelihood that a substantial portion
From playlist DSI Virtual Seminar Series
David Heckerman, Microsoft - Stanford Big Data 2015
Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.
From playlist Big Data in Biomedicine Conference 2015
Efficiently Learning Mixtures of Gaussians - Ankur Moitra
Efficiently Learning Mixtures of Gaussians Ankur Moitra Massachusetts Institute of Technology January 18, 2011 Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We provide a polynomial-time algorithm for this proble
From playlist Mathematics
EM Algorithm In Machine Learning | Expectation-Maximization | Machine Learning Tutorial | Edureka
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training ** This Edureka video on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model. Follo
From playlist Machine Learning Algorithms in Python (With Demo) | Edureka
What is a Sampling Distribution?
Intro to sampling distributions. What is a sampling distribution? What is the mean of the sampling distribution of the mean? Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creat
From playlist Probability Distributions
Optimal Mixing of Glauber Dynamics: Entropy Factorization via High-Dimensional Expan - Zongchen Chen
Computer Science/Discrete Mathematics Seminar I Topic: Optimal Mixing of Glauber Dynamics: Entropy Factorization via High-Dimensional Expansion Speaker: Zongchen Chen Affiliation: Georgia Institute of Technology Date: February 22, 2021 For more video please visit http://video.ias.edu
From playlist Mathematics