Deep Learning with Yacine on MSN

Distributed RL training for LLM explained part 1

An introduction to distributed reinforcement learning for large language models covering core concepts, training setup, and ...

From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
Morning Overview on MSN

Graphene nanodrums identify bacteria by sound in early lab tests

Researchers at TU Delft and partner organizations have built graphene sensors small enough to detect the vibrations of a ...
Semiconductor Engineering

Rethinking Robotics Reinforcement Learning: A Practical Humanoid Training Workflow

A complete pipeline that can run on a single workstation to train a humanoid robot to walk over rough terrain.

Machine learning tracks methane emissions from orbit

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...
EurekAlert!

FedPD: personalized federated learning based on partial distillation

Sub-headline: HIT (Shenzhen) researchers develop FedPD to enhance personalized cross-architecture collaboration  Researchers ...
GitHub

Federated Learning under Distributed Concept Drift (FedDrift)

This repository is the source code for our paper: Federated Learning under Distributed Concept Drift (AISTATS'23). Federated Learning (FL) under distributed concept drift is a largely unexplored area.
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
financefeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
IEEE

Construction of Visual Knowledge Graph Based on Distributed Machine Learning Algorithms

In today's digital age, visual data is experiencing explosive growth. Images, videos and other visual information contain rich semantic knowledge. However, due to their massive volume and complexity, ...