Communications of the ACMOpinion

Rolling in the Deep of Cognitive and AI Biases

To address AI bias at its roots, we must understand the human heuristics that shape it. Unlike prior frameworks that focus ...
Bangkok Post

In-Depth: How to "Survive" Using AI in Trading? Navigating the Era of Machine-Dominated Markets

In today’s modern financial landscape, markets are increasingly driven by automated systems rather than traditional intuitive ...
Devdiscourse

Clean energy boom creates chaos AI is now rushing to fix

A new review finds that AI is no longer being treated simply as a technical add-on for solar and wind prediction, but ...
Frontiers

Adaptive multi-mode locomotion for bipedal wheel-legged robots via sparse mixture-of-experts deep reinforcement learning

The bipedal wheel-legged robot combines the high energy efficiency of wheeled movement with the terrain adaptability of legged locomotion. However, achieving a smooth transition between these two ...
IEEE

Adaptive Reinforcement Learning-Driven Digital Twin for Multi-Objective and Multi-Machine Process Optimization

Abstract: Achieving efficient and scalable multi-objective process optimization in the semiconductor industry poses significant challenges due to the complexity of multi-machine and multi-product ...
Frontiers

Hybrid optimization of interpretable ensemble machine learning for petrophysical property prediction from well logs

Unconventional reservoirs, including shale gas, tight oil, and coalbed methane formations, have emerged as vital contributors to global energy security, accounting for a substantial portion of the ...
Hosted on MSN

Exponential moving averages in deep learning explained

Exponentially Weighted Moving Average or Exponential Weighted Average is a very important concept to understand Optimization in Deep Learning. It means that as we move forward, we simultaneously ...
IEEE

Adaptive Learning Rate Algorithm for Accelerated Convergence in Deep Neural Networks

Abstract: Training deep neural networks is difficult by the erratic and slow convergence of constant learning rate techniques. Conventional optimization methods cannot consistently adapt to changing ...
Hosted on MSN

Deep learning optimization: Major optimizers simplified

In this video, we will understand all major Optimization in Deep Learning. We will see what is Optimization in Deep Learning and why do we need them in the first place. Optimization in Deep Learning ...
Business Wire

Pathway to Deliver New Class of Adaptive and Continuously Learning AI Systems with AWS and NVIDIA Technologies

Pathway’s post-transformer architecture BDH integrated with NVIDIA AI and AWS cloud infrastructure Pathway model’s continuous learning, efficiency, and live observability is powered by NVIDIA AI ...