Anchorage Daily NewsOpinion

Opinion: The $2.6 billion question is, who gets Willow’s oil money?

When royalties begin to flow from Willow, a 1976 deal could leave the state empty-handed — and set up a legal and political ...
IEEE

Adaptive Gradient Activation for Federated Learning on Consumer Electronic Devices

Abstract: Consumer electronic devices play a crucial role in modern life, enhancing connectivity, convenience, and productivity through a wide range of applications. Federated learning (FL) emerges as ...
Scientific Research Publishing

Ruder, S. (2016) An Overview of Gradient Descent Optimization Algorithms. arXiv Preprint.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Scientific Research Publishing

Vanishing Gradients in an Artificial Deep Neural Network: The Impact of Activation Functions and Optimization Techniques ()

Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
VentureBeat

New AI architecture delivers 100x faster reasoning than LLMs with just 1,000 training examples

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...
GitHub

The warning C4251 cannot be disabled in gradient_problem_solver.h file.

When this happens, it may be caused by the order of header file inclusion. Placing the "#include "ceres/iteration_callback.h" before the "#include "ceres/gradient_problem_solver.h" in "ceres.h" file ...
Frontiers

Quantized convolutional neural networks: a hardware perspective

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...
IEEE

A conjugate gradient method for solving unconstrained optimization problems

Abstract: For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is ...