Comments (2)
2ce7001 makes progress on this. It still only benchmarks a fixed set of methods and a fixed data generating process (normal with equally correlated covariates).
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ece75cc allows for a choice of methods.
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Related Issues (17)
- batch learning needs update
- On the slope argument for the batch function
- Add routine to search heuristically for optimal rates for AI-SGD HOT 1
- lambda parameter in sgd not working HOT 5
- Modularity in sgd.R HOT 2
- Benchmark using svrg.update() vs putting the code directly inside sgd()
- Run experiments on covertype data HOT 1
- Use publication quality plotting tools instead of ggplot2
- Implement averaged implicit (aiSGD) in sgd.R
- Relevant datasets? HOT 3
- Averaged versions need to use larger learning rates. HOT 5
- Need separate folder/better naming for experiments.
- Remove need for defining sgd/batch in exp_normal_n5p2.R HOT 4
- Unit testing
- Reorganize functions.R and disperse functions over multiple files HOT 1
- Add signal-to-noise ratio for other GLMs in generate.data()
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