chore: Prepare v0.15.0 release (#743)

- Add SDMGradWeighting to README
- Bump version to v0.15.0 in pyproject.toml
- Add [0.15.0] section in changelog

Author: ValerianRey

CHANGELOG.md

@@ -8,6 +8,8 @@ changelog does not include internal changes that do not affect the user.
 
 ## [Unreleased]
 
+## [0.15.0] - 2026-06-15
+
 ### Added
 
 - Added `SDMGradWeighting` from

README.md

@@ -242,6 +242,7 @@ TorchJD provides many existing aggregators from the literature, listed in the fo
 | [NashMTL](https://torchjd.org/stable/docs/aggregation/nash_mtl#torchjd.aggregation.NashMTL)                | -                                                                                                                      | [Multi-Task Learning as a Bargaining Game](https://arxiv.org/pdf/2202.01017)                                                                                         |
 | [PCGrad](https://torchjd.org/stable/docs/aggregation/pcgrad#torchjd.aggregation.PCGrad)                    | [PCGradWeighting](https://torchjd.org/stable/docs/aggregation/pcgrad#torchjd.aggregation.PCGradWeighting)              | [Gradient Surgery for Multi-Task Learning](https://arxiv.org/pdf/2001.06782)                                                                                         |
 | [Random](https://torchjd.org/stable/docs/aggregation/random#torchjd.aggregation.Random)                    | [RandomWeighting](https://torchjd.org/stable/docs/aggregation/random#torchjd.aggregation.RandomWeighting)              | [Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning](https://arxiv.org/pdf/2111.10603)                                              |
+| - | [SDMGradWeighting](https://torchjd.org/stable/docs/aggregation/sdmgrad#torchjd.aggregation.SDMGradWeighting) | [Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms](https://arxiv.org/pdf/2305.18409) |
 | [Sum](https://torchjd.org/stable/docs/aggregation/sum#torchjd.aggregation.Sum)                             | [SumWeighting](https://torchjd.org/stable/docs/aggregation/sum#torchjd.aggregation.SumWeighting)                       | -                                                                                                                                                                    |
 | [Trimmed Mean](https://torchjd.org/stable/docs/aggregation/trimmed_mean#torchjd.aggregation.TrimmedMean)   | -                                                                                                                      | [Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates](https://proceedings.mlr.press/v80/yin18a/yin18a.pdf)                                      |
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "torchjd"
-version = "0.14.0"
+version = "0.15.0"
 description = "Library for Jacobian Descent with PyTorch."
 readme = "README.md"
 authors = [