Radical empiricism and machine learning research
نویسندگان
چکیده
منابع مشابه
Machine-Learning Research
The last five years have seen an explosion in machine-learning research. This explosion has many causes: First, separate research communities in symbolic machine learning, computational learning theory, neural networks, statistics, and pattern recognition have discovered one another and begun to work together. Second, machine-learning techniques are being applied to new kinds of problem, includ...
متن کاملRadical Empiricism: Empirical Modelling and the nature of knowing
This paper explores connections between Radical Empiricism (RE), a philosophic attitude developed by William James at the beginning of the 20 century, and Empirical Modelling (EM), an approach to computerbased modelling that has been developed by the author and his collaborators over a number of years. It focuses in particular on how both RE and EM promote a perspective on the nature of knowing...
متن کاملReproducible Research Pattern Recognition and Machine Learning
This is a course on Reproducible Research (RR) [1] for research engineers working with software applications in Pattern Recognition (PR) and Machine Learning (ML) [2]. It motivates and explains concepts behind RR, an increasing trend in scientific publications in this niche, its implications and tools for implementing it on an individual or group levels. It is a hands-on course in the sense stu...
متن کاملApplying machine learning in accounting research
Quite often, in order to derive meaningful insights, accounting researchers have to analyze large bodies of text. Usually, this is done manually by several human coders, which makes the process time consuming, expensive, and often neither replicable nor accurate. In an attempt to mitigate these problems, we perform a feasibility study investigating the applicability of computer-aided content an...
متن کاملPylearn2: a machine learning research library
Pylearn2 is a machine learning research library. This does not just mean that it is a collection of machine learning algorithms that share a common API; it means that it has been designed for flexibility and extensibility in order to facilitate research projects that involve new or unusual use cases. In this paper we give a brief history of the library, an overview of its basic philosophy, a su...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Causal Inference
سال: 2021
ISSN: 2193-3685,2193-3677
DOI: 10.1515/jci-2021-0006