Mathematical foundation for ensemble machine learning and ensemble portfolio analysisdoi:10.2139/ssrn.3243974Eugene Pinsky
The Stanford's Machine Learning Course gave me a solid mathematical foundation for Machine Learning! Here are my problem set solutions for the course. - AlmeidaAlin3/Learning_ML
Provides a comprehensive mathematical foundation of data science. Includes all the main aspects of programming in R. Contains complete practical examples with R. Updated and corrected new edition. Author / Editor information Prof. Dr. Frank Emmert-Streib,Tampere University, Finnland Frank Emmert...
Code for the Paper "MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts".For more details, please refer to the project page with dataset exploration and visualization tools: https://mathvista.github.io/.🔔 If you have any questions or suggestions, please don't ...
The column generation is the foundation of the branch and price. The principle of the column generation method has been widely studied and used in recent years with great success on a wide range of problems (scheduling, vehicle routing, cutting stock, etc.) (Desaulniers et al., 2005). Thi...
The intersection of mathematics and Artificial Intelligence (AI) has long been pivotal in advancing cognitive computing and machine learning. Traditional mathematics provides the structural foundation upon which AI algorithms are built, enabling tasks ranging from data processing to complex decision-making....
The development of CoT-Influx involved the creation of a specialized math reasoning dataset, MRD3, featuring problems that span over a wide range of difficulty levels and reasoning steps. This dataset is the foun...
foundation, even though type theories are among the most thoroughly developed logical foundations (in particular with well developed computer proof software systems). Instead, mathematicians write in a kind ofcommon mathematical language(CML) (sometimes called amathematical vernacular), for a number of ...
LLMs stands for Large Language Models. These are advanced machine learning models that are trained to comprehend massive volumes of text data and generate natural language. Examples of LLMs include GPT-3 (Generative Pre-trained Transformer 3) a...
Tensors form the foundation of modern machine learning systems. They are come in various flavors of type, rank, and shape. You can manipulate numerical tensors via tensor operations (such as addition, tensor product, or element-wise multiplication), which can be interpreted as encoding geometric...