5 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
ZipNN: Lossless Compression for AI Models
Moshik Hershcovitch, Andrew Wood, Leshem Choshen +7
With the growth of model sizes and the scale of their deployment, their sheer size burdens the infrastructure requiring more network and more storage to accommodate these. While th…
Lossless and Near-Lossless Compression for Foundation Models
Moshik Hershcovitch, Leshem Choshen, Andrew Wood +4
With the growth of model sizes and scale of their deployment, their sheer size burdens the infrastructure requiring more network and more storage to accommodate these. While there…
MPP: Model Performance Predictor
Sindhu Ghanta, Sriram Subramanian, Lior Khermosh +5
Operations is a key challenge in the domain of machine learning pipeline deployments involving monitoring and management of real-time prediction quality. Typically, metrics like ac…
ML Health: Fitness Tracking for Production Models
Sindhu Ghanta, Sriram Subramanian, Lior Khermosh +5
Deployment of machine learning (ML) algorithms in production for extended periods of time has uncovered new challenges such as monitoring and management of real-time prediction qua…