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Gurobi / gurobi-machinelearning

Formulate trained predictors in Gurobi models
https://gurobi-machinelearning.readthedocs.io/
Apache License 2.0
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Bump xgboost from 2.0.3 to 2.1.1 #329

Closed dependabot[bot] closed 3 months ago

dependabot[bot] commented 4 months ago

Bumps xgboost from 2.0.3 to 2.1.1.

Release notes

Sourced from xgboost's releases.

2.1.1 Patch Release

The 2.1.1 patch release make the following bug fixes:

In addition, it contains several enhancements:

Full Changelog: https://github.com/dmlc/xgboost/compare/v2.1.0...v2.1.1

Additional artifacts:

You can verify the downloaded packages by running the following command on your Unix shell:

echo "<hash> <artifact>" | shasum -a 256 --check

eddbc5200b7c5210f2b8974b9d2a0328a30753416bfb81fdaf5040f4f7abb222  xgboost-2.1.1.tar.gz
3ba5a6e0c609bd5cc0a667d83c57457c06778bece50863e58c8bc1b4eb415fc6  xgboost_r_gpu_linux_2.1.1.tar.gz

Experimental binary packages for R with CUDA enabled

  • xgboost_r_gpu_linux_2.1.1.tar.gz: Download

Source tarball

Release 2.1.0 stable

2.1.0 (2024 Jun 20)

We are thrilled to announce the XGBoost 2.1 release. This note will start by summarizing some general changes and then highlighting specific package updates. As we are working on a new R interface, this release will not include the R package. We'll update the R package as soon as it's ready. Stay tuned!

Networking Improvements

An important ongoing work for XGBoost, which we've been collaborating on, is to support resilience for improved scaling and federated learning on various platforms. The existing networking library in XGBoost, adopted from the RABIT project, can no longer meet the feature demand. We've revamped the RABIT module in this release to pave the way for future development. The choice of using an in-house version instead of an existing library is due to the active development status with frequent new feature requests like loading extra plugins for federated learning. The new implementation features:

  • Both CPU and GPU communication (based on NCCL).
  • A reusable tracker for both the Python package and JVM packages. With the new release, the JVM packages no longer require Python as a runtime dependency.
  • Supports federated communication patterns for both CPU and GPU.
  • Supports timeout. The high-level interface parameter is currently hard-coded to 30 minutes, which we plan to improve.

... (truncated)

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