This is the third of five posts in the Risks from Learned Optimization Sequence based on the paper “Risks from Learned Optimization in Advanced Machi…| www.alignmentforum.org
Breakthroughs in machine learning are rapidly changing science and society, yet our fundamental understanding of this technology has lagged far behind. Indeed, one of the central tenets of the field, the bias-variance trade-off, appears to be at odds with the observed behavior of methods used in the modern machine learning practice. The bias-variance trade-off implies that a model should balance under-fitting and over-fitting: rich enough to express underlying structure in data, simple enough...| arXiv.org
This is the fourth of five posts in the Risks from Learned Optimization Sequence based on the paper “Risks from Learned Optimization in Advanced Mach…| www.alignmentforum.org
This is the second of five posts in the Risks from Learned Optimization Sequence based on the paper “Risks from Learned Optimization in Advanced Mach…| www.alignmentforum.org
Double descent is a puzzling phenomenon in machine learning where increasing model size/training time/data can initially hurt performance, but then i…| www.alignmentforum.org
Suppose that we use the universal prior for sequence prediction, without regard for computational complexity. I think that the result is going to be really weird, and that most people don’t a…| Ordinary Ideas