2 papers
cs.LG2024
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization
Amey Agrawal, Sameer Reddy, Satwik Bhattamishra +4
With the increase in the scale of Deep Learning (DL) training workloads in terms of compute resources and time consumption, the likelihood of encountering in-training failures rise…
cs.HC2024
Beyond Following: Mixing Active Initiative into Computational Creativity
Zhiyu Lin, Upol Ehsan, Rohan Agarwal +3
Generative Artificial Intelligence (AI) encounters limitations in efficiency and fairness within the realm of Procedural Content Generation (PCG) when human creators solely drive a…