LightR

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LightR Sub-pages:
Version History

This page is under construction. For recent activities, see Version History.


Design principle
Strategy light, machine learning heavy
Central goal
Learned models -> learned systems
Planned experiments
Towards deep learning:
Multiple hand-tuned danger models -> Expert model & gate model
Hand-crafted features with naive KNN -> Search-based sequence model
Offline pre-training & online fine-tuning of everything above.
Towards differentiable programming:
Directly optimizing prior probability of getting hit (max escape angle, distancing and multi-wave risk fusion)
Per-instance level optimization of the above (Pareto frontier)
List-wise modeling of targeting & surfing