I've spent the last few months preparing for and applying for data science jobs. It's possible the data science world may reject me and my lack of both experience and a credential above a bachelors degree, in which case I'll do something else. Regardless of what lies in store for my future, I think I've…
Have you ever wondered how will the machine learning frameworks of the '20s look like? In this essay, I examine the directions AI research might take and the requirements they impose on the tools at our disposal, concluding with an overview of what I believe to be the two strong candidates: `JAX` and `S4TF`.
Machine Learning Summer School (MLSS) is a course about modern methods of statistical machine learning and inference. It presents topics which are at the cor...
- ARM Research
- Hound: Causal Learning for Datacenter-scale Straggler Diagnosis
- Adaptive Resource Management for Mobile CMPs through Self-awareness
- On-the-fly deterministic binary filters and other on-going work in Machine Learning Systems
- Managed Modularity for Deep Neural Networks
Turning procedural and structural knowledge into programs has established methodologies, but what about turning knowledge into probabilistic models? I explore a few examples of what such a process could look like.
My name is Daniel Holden. I'm a researcher at Ubisoft Montreal using Machine Learning for character animation and other applications. I'm also a Digital Artist and Writer. My interests are Computer Graphics, Game Development, Theory of Computation, and Programming Languages.
This post discusses the benefits of full-stack data science generalists over narrow functional specialists. The later will help you execute and bring process...
M. Lindvall, and J. Molin. (2020)cite arxiv:2001.07455Comment: Accepted for presentation in poster format for the ACM CHI'19 Workshop <Emerging Perspectives in Human-Centered Machine Learning>.