Robohub

Gradient-based planning for world models at longer horizons

GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1 ...
IEEE

Enhancing Privacy-Preserved Iris Recognition in Consumer Electronics: A Soft Actor-Critic and GAN-Based Digital Forensic Framework With Bayesian Hyperparameter Optimization

Abstract: The widespread deployment of iris recognition (IR) systems in consumer electronics has raised pressing concerns related to digital forensics, biometric integrity, and user privacy. This ...

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 — ...

Neural network speeds tuning of attosecond light pulses for physics experiments

Researchers from Skoltech and the Shanghai Institute of Optics and Fine Mechanics have developed an approach that helps ...
Frontiers

Enhanced Recovery and Perioperative Optimization in Gastrointestinal and Hepatopancreatobiliary Cancer Surgery

Enhanced Recovery After Surgery (ERAS) programs have changed perioperative care in gastrointestinal (GI) and hepatopancreatobiliary (HPB) oncology by ...
Hosted on MSN

AI and analytics reshape home security with proactive threat detection

Advances in AI, IoT, and predictive analytics are enabling home security systems to shift from reactive alerts to proactive threat prevention. Research shows that refining anomaly detection for ...
IEEE

Hyperparameter Tuning of Classification Algorithms with a Hyper-Heuristic Framework - the Nested Markov Hyper-Tuner

Abstract: Hyper-heuristic methods have recently attracted research interest due to their effectiveness in solving optimization problems. Hyperparameter optimization (or tuning) is an essential task in ...