Oríon: A framework for distributed hyperparameter optimisation

I am the lead developer of Oríon, an open-source framework developed at Mila for distributed black-box optimization. Its purpose is to serve as a meta-optimizer for machine learning models and training, as well as a flexible experimentation platform for large-scale asynchronous optimization procedures.

Track: Generic logger backend for machine learning

Track is a generic logger backend developed at Mila that can serve as a bridge between different logging libraries for machine learning. The goal is to provide a backend for Oríon so that users can use their own logger without any modification and simply configure Oríon to use the proper bridge with Track.

Kleiṓ: Experiment management for machine learning

Kleiṓ is an experiment manager, a logging journal of all data describing your experiments. Its purpose is to provide an automatic tool to log extensive environment information, including a script’s code version, system specification, and script configuration.