About
A Python package for hill climbing optimization of user-supplied objective functions, with simulated annealing and parallel replica exchange. Designed for flexible multi-objective optimization with multi-column dataset support.
Key Highlights
- ▸ Published flexible optimization library supporting simulated annealing and parallel replica exchange
- ▸ Objective-agnostic design allows drop-in use across diverse ML and research problems
Technologies
optimization python library simulated-annealing research
Roles
ml-engineer researcher