By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...
Floating Fleet AI, a leading provider of AI-driven solutions for private aviation, today announced the addition of Norbert ...
QuoteIQ, a CRM platform built for mobile and field service businesses, has announced the launch of Route Density, a new ...
Tessellations aren’t just eye-catching patterns—they can be used to crack complex mathematical problems. By repeatedly ...
Oil and gas companies are under increasing pressure to boost efficiency, cut costs, and meet sustainability goals without sacrificing reliability. In this webinar, Rockwell Automation experts will ...
Abstract: Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational ...
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: Recently, neural combinatorial optimization (NCO) methods have been prevailing for solving multiobjective combinatorial optimization problems (MOCOPs). Most NCO methods are based on the ...
We present OPT-BENCH, a benchmark comprising 20 machine learning tasks and 10 NP problems, specifically designed to assess large language models’ (LLMs) ability to solve problems with large search ...
Palo Alto, California-based D-Wave Quantum Inc. claims to be the first company that sells computers that leverage quantum effects in their operation. The company recently demonstrated how its quantum ...
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