Technology Networks

Predictive Modeling for Compound Prioritization

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...
Psychology TodayOpinion

Why Algorithms Show Us What We Claim Not to Want

Why do algorithms keep showing us content we claim not to want? The answer isn’t manipulation—it’s conflict between our ...

Social media’s next evolution: user-controlled algorithms

Social media feeds are becoming more customizable as platforms like Threads, Instagram, and TikTok introduce tools that let ...
Engadget

Spotify’s new Taste Profile feature lets users fine-tune their algorithm’s recommendations

You're responsible for your own Spotify algorithm now. On stage at SXSW, Spotify's co-CEO, Gustav Söderström, announced the Taste Profile feature, which allows users to personally customize exactly ...
Engadget

Meta turned Threads algorithm complaints into an official feature

Threads users have been complaining about its recommendation algorithm pretty much since the beginning of the platform. At some point, this turned into a meme, with users writing posts jokingly ...
Frontiers

Evolutionary algorithm-optimized feature fusion for accurate classification of shredded tobacco using multi-sensor data

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...
Digital Trends

Instagram is finally giving you an easy way to teach its algorithm what you like

What’s happened? Instagram is testing a new feature that gives users more control over the type of content they see on the platform. Why is this important? Instagram’s algorithm plays a major role in ...
C&EN

SOH Estimation Based on Multisource Feature Extraction and SSA-LSTM Algorithm

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
Nature

An IoT intrusion detection framework based on feature selection and large language models fine-tuning

The rapid proliferation of Internet of Things (IoT) devices has significantly expanded the network attack surface, necessitating the deployment of advanced AI (artificial intelligence)-based intrusion ...
Nature

Grey wolf optimizer with self-repulsion strategy for feature selection

Feature selection is one of the most critical steps in big data analysis. Accurately extracting correct features from massive data can effectively improve the accuracy of big data processing ...
IEEE

A Surrogate-Assisted Multi-Phase Ensemble Feature Selection Algorithm With Particle Swarm Optimization in Imbalanced Data

Abstract: Feature selection based on evolutionary algorithm (EA) is an effective dimension reduction technology. However, existing EAs still constrained by high computational cost and easy-to-local ...
IEEE

Two-Stage Hybrid Feature Selection: Integrating ACO Algorithms With a Statistical Ensemble Technique for EV Demand Prediction

Abstract: This paper presents a novel hybrid algorithm combining Ant Colony Optimization (ACO) and multi-model ensemble feature selection techniques to enhance the accuracy of Support Vector ...