0.3.10 - 2020-05-29

With this release we integrate a new tuning library, SMAC, with our benchmarking process. A new
leaderboard including this library has been generated. The following two tuners from this library
have been added:

• SMAC4HPO: Bayesian optimization using a Random Forest model of pyrfr.
• HB4AC: Uses Successive Halving for proposals.

Internal improvements

• Renamed btb_benchmark/tuners to btb_benchmark/tuning_functions.
• Ready to use tuning functions from btb_benchmark/tuning_functions.

Resolved Issues

• Issue #195: Integrate SMAC for benchmarking.