The Dynamic Ads optimization initiative represents a paradigm shift in how advertising platforms approach vertical-specific ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively ...

In retail and logistics, IoT helps track items in real-time, manage stock, and even prevent theft or damage. Worker safety is ...

Machine learning didn’t disappear — it embedded itself. These seven competencies define what marketers must architect, govern and measure for 2026.

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

The quantum sector is shifting from speculative science to a commercial race, with hardware, software, and investment pipelines all accelerating at once. Instead of distant promises, companies and ...

Abstract: In practical applications, the simultaneous optimization of numerous design parameters in time-consuming multi-objective optimization experiments is recognized as a significant bottleneck ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

Abstract: A combinatorial optimization problem is a problem finding an optimal combination of variables that maximizes or minimizes an objective function while satisfying given constraints. Such ...

College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...