New AI capabilities help DBAs move from performance visibility to performance resolution--turning slow queries into actionable index recommendations in minutes HOUSTON, March 19, 2026 /PRNewswire/ -- ...
Abstract: Recent advances in recommendation systems have highlighted the critical importance of data quality in model performance. In this paper, we propose a reinforcement learning based data weight ...
DoiT, a global leader in enterprise-grade FinOps and CloudOps solutions, is acquiring SELECT, a data optimization company purpose-built to help organizations gain visibility and control over data ...
Center for Rare Earth and Inorganic Functional Materials, School of Materials Science and Engineering & National Institute for Advanced Materials, Nankai University, Tianjin 300350, China ...
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology ...
Transformer models pre-trained on self-supervised tasks and fine-tuned on downstream objectives have achieved remarkable results across a variety of domains. However, fine-tuning these models for ...
Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...
Since the development of the first database management systems (DBMSs) over five decades ago, DBMSs have become the foundation of modern data-intensive applications. However, deploying and maintaining ...
Abstract: In the areas of database performance optimization research, researchers have proposed many optimization methods and theories, most of them are on the database itself and database environment ...
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