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CHANGELOG.md

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  • Features

  • Changes

  • Bugs

v0.2.2 (2014-12-5)

SHA: 83a71512e6a4aa553866e4301ef11f172d485e23

  • Features

    • Added startup message to REST server including tips for OSX users (#400)
    • Added GPU support to cpp_wrappers.expected_improvement.multistart_expected_improvement_optimization; requires max_num_threads == 1 until future multi-GPU support (#368)
    • Added the COBYLA optimizer to the expected improvement optimization class. (#370)
    • OptimizerParameter struct members now directly readable/writeable from Python; added EqualityComparisonMixin (#138)
    • C++ GradientDescentParameters object now stores num_steps_averaged (but does not use it yet) (#391)
    • conda build system for MOE (#417)
  • Changes

    • Switched from testify to py.test - http://pytest.org/ (#36)
    • [cleanup] Moved bandits into their own sub directories (#375)
    • Supply PYTHON_LIBRARY and PYTHON_INCLUDE_DIR vars to cmake automatically in setup.py (#412)
    • Added warning when colander version is out of date (#413)
  • Bugs

    • Fixed UCB1 and UCB1-tuned algorithm confidence bound calculation (#432)

v0.2.1 (2014-09-22)

SHA: ab6f959c11a0cacbed6dad618fe6ffed71092116

  • Features

    • Implemented BLA (Bayesian Learning Automaton). (#373)
    • Connected GPU functions to multistart gradient descent optimizer. (#270)
  • Changes

  • Bugs

    • variance in a sample arm was dropped in _make_bandit_historical_info_from_params. (#385)
    • SampleArm's __add__ and __str__ were broken. (#387)
    • Specifying max_num_threads on GPU compute paths caused a segfault (#394)

v0.2.0 (2014-08-15)

SHA: 8201917e3f9b47b8edd8039ea3278ef8631b0f2a

  • Features

    • Added multi-armed bandit endpoint. (#255)
      • Implemented epsilon-greedy. (#255)
      • Implemented epsilon-first. (#335)
      • Implemented UCB1. (#354)
      • Implemented UCB1-tuned. (#366)
    • Added support for the L-BFGS-B optimizer. (#296)
    • Added GPU implementation for q,p-EI and its gradient computation. (#219)
      • Speed up GPU functions by redesign of memory allocation. (#297)
  • Changes

    • Split up old schemas.py file into schemas/ directory with several subfiles (#291)
    • Improved Dockerfile, reducing Docker-based install times substantially, https://hub.docker.com/u/yelpmoe/ (#332)
      • Created min_reqs docker container which is a snapshot of all MOE third-party requirements
      • Created latest, which tracks the latest MOE build
      • Started releasing docker containers for each tagged MOE release (currently just v0.1.0)
    • GradientDescentOptimization (C++) no longer has a separate next_points output (#186)
    • LogLikelihood evaluate at point list and latin hypercube search now return status dicts like every other optimizer (#189)
      • status dicts also a little more informative/standardized now
    • Update C++ autodoc tools to handle the new gpu directory (#353)
    • Added __version__ to moe/__init__.py (#353)
  • Bugs

    • Throw exceptions (C++) if num_multistarts or num_random_samples is 0 (#345)
    • combined_example endpoint was not passing kwargs through so users could not change the default server (#356)
      • fix sometimes dropped general kwargs (#358)
    • mean_var_of_gp_from_historic_data was also not passing kwargs (#359)

v0.1.0 (2014-07-29)

SHA: 5fef1d242cc8b6e0d6443522f8ba73ba743607de

  • Features

    • initial open source release