Learn With Jay on MSNOpinion

Momentum optimizer explained for faster deep learning training

In this video, we will understand in detail what is Momentum Optimizer in Deep Learning. Momentum Optimizer in Deep Learning ...
Learn With Jay on MSNOpinion

Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...
Security Boulevard

NDSS 2025 – DLBox: New Model Training Framework For Protecting Training Data

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National ...

New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs

By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" ...
Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
Devdiscourse

Why deep learning is becoming essential for sustainable finance forecasting

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment

B, an open-source AI coding model trained in four days on Nvidia B200 GPUs, publishing its full reinforcement-learning stack as Claude Code hype underscores the accelerating race to automate software ...
AlphaGalileo

From time series to a single snapshot: A smarter way to track wheat growth in real time

A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...
Tech Xplore on MSN

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
EurekAlert!

Maize-IRNet: a deep-learning “field scorer” for tassel anthers and ear seed set

A research team has developed an AI-based approach to streamline the evaluation of maize haploid fertility restoration, a key bottleneck in double haploid (DH) breeding.