Interesting Engineering on MSN4d
Researchers unlock new potential in Newton’s method, 300 years after its creation
Their work extends Newton’s method to efficiently handle the broadest class of functions yet, pushing the centuries-old ...
IEEE6d
Low-Latency and Energy-Efficient Federated Learning over Cell-Free Networks: A Trade-off Analysis
We solve these problems using a combination of Brent’s method, coordinate gradient descent, the bisection method, and Sequential Quadratic Programming (SQP) with BFGS updates. Numerical results ...
GitHub2d
Saving memory using gradient-checkpointing
Additional explanation of computation graphs, memory usage, and gradient computation strategies, can be found in the blog post accompanying our package. import tensorflow as tf import ...
IEEE4d
Deep Diffusion Gradients Leakage in Federated Learning
Abstract: In federated learning (FL), multiple clients train a global model by sharing gradients. Since the client data remains locally, federated learning is considered privacy-safe. Although ...
GitHub4d
multivariate-linear-regression
This repository is a related to all about Machine Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques ...