Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

AI reasoning does not necessarily require spending huge amounts on frontier models. Instead, smaller models can yield ...
InfoQ

Google Researchers Propose Bayesian Teaching Method for Large Language Models

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Randy Shoup discusses the "Velocity ...
Search Engine Land

Inspiring examples of responsible and realistic vibe coding for SEO

Vibe coding is a new way to create software using AI tools such as ChatGPT, Cursor, Replit, and Gemini. It works by describing to the tool what you want in plain language and receiving written code in ...
IEEE

Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search

Abstract: In many applications, ranging from logistics to engineering, a designer is faced with a sequence of optimization tasks for which the objectives are in the form of black-box functions that ...
MD&M East

The Year Medtronic Set an Example for Supply Chain Optimization

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...
TCTMD

Case Examples of Bayesian Study Designs Used to Accelerate Assessments of Device Safety and Efficacy in SHD

Receive the the latest news, research, and presentations from major meetings right to your inbox. TCTMD ® is produced by the Cardiovascular Research Foundation ® (CRF). CRF ® is committed to igniting ...
C&EN

Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...
GitHub

CDM-PSL: Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models

CDM-PSL (Composite Diffusion Model-Based Pareto Set Learning) is a novel algorithm designed to address the challenges of expensive multi-objective Bayesian optimization (EMOBO). While MOBO has shown ...
ecommercefastlane

Marketing Mix Modeling Optimization: A Data-Driven Strategy For Ecommerce Growth

Marketing mix modeling optimization isn’t just a buzzword—it’s becoming one of the most dependable ways for e-commerce professionals to make smarter decisions. Marketing Mix Modeling (MMM) blends data ...
marktechpost

GraphIC: A Novel Machine Learning Approach that Leverages Graph-based Representations of Reasoning Processes Coupled with Bayesian Networks (BNs) to Select In-Context Examples ...

In-context learning (ICL) enables LLMs to adapt to new tasks by including a few examples directly in the input without updating their parameters. However, selecting appropriate in-context examples ...