TMCnet

MicroAlgo Inc. Develops Optimal Precise Quantum Query Algorithm Based on Sum-of-Squares Representation Form of Boolean Functions

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the proposal of a new approach to solving the Boolean function query problem. This framework starts from the ...

Scientists leverage AI to optimize glass formulas for liquid radioactive waste

Scientists have used the power of AI to analyze and predict the conversion of liquid radioactive waste into solid glass waste ...

New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...
Hosted on MSN

How AI is reshaping student life and learning

AI is becoming a core part of higher education, transforming how students study, research, and engage with coursework. From AI tutors like UT Sage to advanced research assistants, these tools promise ...

WRD wants to do for language learning what GPS did for navigation — remove the thinking

WRD’s own research, published on the app’s website, shows that users following this approach reach the same levels of ...
TMCnet

MicroAlgo Inc. Develops Quantum Algorithm Technology for Feedforward Neural Networks to Drive Neural Network Revolution

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced that they have developed a set of quantum algorithms for feedforward neural networks, breaking through the performance ...
IEEE

A Multiobjective Evolutionary Algorithm Based on Bipopulation With Uniform Sampling for Neural Architecture Search

Abstract: Neural architecture search (NAS) automates neural network design, improving efficiency over manual approaches. However, efficiently discovering high-performance neural network architectures ...
IEEE

Deep Reinforcement Learning-Assisted Automated Operator Portfolio for Constrained Multi-Objective Optimization

Abstract: Constrained multi-objective optimization problems (CMOPs) are of great significance in the context of practical applications, ranging from scientific to engineering domains. Most existing ...