Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Q&A: Algorithm achieves near end-to-end genome assembly without ultra-long DNA sequencing

Haoyu Cheng, Ph.D., assistant professor of biomedical informatics and data science at Yale School of Medicine, has developed a new algorithm capable of building complete human genomes using standard ...
Frontiers

Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler

Genome assembly remains an unsolved problem, and de novo strategies (i.e., those run without a reference) are relevant but computationally complex tasks in genomics. Although de novo assemblers have ...
Scientific Research Publishing

Zhou, Q., Zhang, D., Liu, H. and He, Y. (2024) KCS-YOLO: An Improved Algorithm for Traffic Light Detection under Low Visibility Conditions. Machines, 12, Article 557.

ABSTRACT: Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle ...
Frontiers

A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
intelligentcio

Infleqtion unveils Contextual Machine Learning, powering AI breakthroughs with NVIDIA CUDA-Q and quantum-inspired algorithms

CML unlocks AI’s full potential with enhanced pattern recognition, prediction and real-time decision-making for defense, autonomous systems and next-gen computing. Infleqtion, a global leader in ...
eLife

Q-learning with temporal memory to navigate turbulence

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...
IEEE

A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios

Abstract: This paper studies a deep reinforcement learning technique for distributed resource allocation among cognitive radios operating under an underlay dynamic spectrum access paradigm which does ...
marktechpost

Meta AI Introduces MR.Q: A Model-Free Reinforcement Learning Algorithm with Model-Based Representations for Enhanced Generalization

Reinforcement learning (RL) trains agents to make sequential decisions by maximizing cumulative rewards. It has diverse applications, including robotics, gaming, and automation, where agents interact ...