Related Issues (20)
- Add more examples
- Research other optimization algorithms
- Adaptive batch sizing
- Add an SBT build
- Allow an optimizer run to continue where it left off
- User configurable parallelism for non-spark implementation
- Integrate with MLlib
- Allow user to specify their own StopStrategy function
- Add random sampling of combinations for RandomSearch HOT 1
- Exhaustive iteration of combinations for Grid Search
- Add subset sampling for RandomSearch hyperparameters
- Allow user to specify cache size before training HOT 1
- Allow VWProcess to accept samples through InputStream. This will by redirected into that process' standard input
- Bake in clean way of minimizing / maximization of other metrics in objective functions
- Add README.md for vw module. Document the supported use cases
- Refactor OptimizerState and OptimizeResult
- Add readme for VW module HOT 8
- --cb parameter must be specified when generating cache file HOT 1
- Refactor VW cache distribution HOT 1
- Ability for a sampler to depend on previous parameter's values HOT 2
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