Главная
Study mode:
on
You
History
Saved
In progress 0 courses
compleat 0 courses
#Art & Design #Adobe #ChatGPT #GitHub

#Implicit Regularization

Showing: 12 courses
University of Central Florida

Understanding Deep Learning Requires Rethinking Generalization

0 rewiews
Explore deep learning generalization, examining regularization techniques, randomization tests, and neural network expressivity to challenge conventional understanding and improve model performance.
Add to list
15 Lesons
40 minutes
On-Demand
Free-Video
Fields Institute

Beyond Lazy Training for Over-parameterized Tensor Decomposition

0 rewiews
Explore over-parameterization in tensor decomposition, comparing lazy training and gradient descent approaches. Discover how gradient descent can leverage low-rank data structure beyond lazy training regimes.
Add to list
17 Lesons
37 minutes
On-Demand
Free-Video
Yannic Kilcher

Training More Effective Learned Optimizers, and Using Them to Train Themselves - Paper Explained

0 rewiews
Explores a novel approach to machine learning optimization using neural networks, discussing its architecture, training process, and potential to revolutionize model training through self-improvement and generalization.
Add to list
15 Lesons
54 minutes
On-Demand
Free-Video
Hausdorff Center for Mathematics

Generalization in Deep Learning Through the Lens of Implicit Rank Minimization

0 rewiews
Explores implicit regularization in deep learning through matrix and tensor factorizations, revealing tendencies towards low ranks. Discusses implications for generalization and potential improvements in neural network design.
Add to list
24 Lesons
41 minutes
On-Demand
Free-Video
Alan Turing Institute

Benign Overfitting - Peter Bartlett, UC Berkeley

0 rewiews
Explore benign overfitting in machine learning, focusing on linear regression, deep networks, and statistical implications. Gain insights into effective rank, regularization, and future research directions.
Add to list
17 Lesons
42 minutes
On-Demand
Free-Video
Alan Turing Institute

Big Data Is Low Rank - Madeleine Udell, Cornell University

0 rewiews
Explore big data's low-rank structure, generalized low-rank models, and their applications in machine learning. Learn about dimensionality reduction, autoML, and latent variable models for efficient data analysis.
Add to list
17 Lesons
46 minutes
On-Demand
Free-Video
Simons Institute

Implicit Regularization I

0 rewiews
Explore implicit regularization in deep learning, covering boosting, complexity control, optimization landscapes, and stochastic gradient descent for effective model training.
Add to list
13 Lesons
1 hour 17 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Implicit and Explicit Regularization in Deep Neural Networks

0 rewiews
Explores implicit and explicit regularization in deep neural networks, connecting learning algorithms to H-infinity control and explaining convergence behavior in over-parametrized models, offering insights into generalization abilities.
Add to list
20 Lesons
37 minutes
On-Demand
Free-Video
Simons Institute

Implicit Regularization II

0 rewiews
Explore implicit regularization in deep learning, focusing on advanced concepts and their impact on model performance and generalization.
Add to list
1 Lesons
1 hour 23 minutes
On-Demand
Free-Video
Alan Turing Institute

Implicit Regularization for General Norms and Errors - Lorenzo Rosasco, MIT

0 rewiews
Explores implicit regularization in optimization methods, focusing on stability in estimation processes for non-Euclidean norms and non-quadratic errors, with emphasis on accelerated techniques.
Add to list
1 Lesons
41 minutes
On-Demand
Free-Video
Georgia Tech Research

Random Initialization and Implicit Regularization in Nonconvex Statistical Estimation - Lecture 2

0 rewiews
Explore nonconvex optimization in statistical estimation, focusing on gradient descent's convergence to optimal solutions without explicit regularization or careful initialization.
Add to list
16 Lesons
48 minutes
On-Demand
Free-Video
MITCBMM

Towards Understanding the Implicit Regularization Effect of SGD

0 rewiews
Explore the implicit regularization effect of Stochastic Gradient Descent, uncovering its impact on optimization and generalization in machine learning models.
Add to list
1 Lesons
1 hour 14 minutes
On-Demand
Free-Video