An important aspect in software engineering is the ability to distinguish between premature, unnecessary, and necessary ...
Professional mathematicians have been stunned by the progress amateurs have made in solving long-standing problems with the assistance of AI tools, and say it could lead to a new way of doing mathemat ...
Quantum computers could rapidly solve complex problems that would take the most powerful classical supercomputers decades to ...
FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the ...
By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...
They are effectively wagering that addressing specific optimization challenges today holds more value than the promise of ...
The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...
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: Real-world production scenarios often involve multiobjective optimization problems with intricate constraints. Although there has been a growing interest in multiobjective problems with ...
A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...
In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback