- 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.
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>.