Appfl

What's Changed
* Data readiness report generation by kaveenh in https://github.com/APPFL/APPFL/pull/163
* Fix Issue 164 by Zilinghan in https://github.com/APPFL/APPFL/pull/165
* Make dr_metrics optional by Zilinghan in https://github.com/APPFL/APPFL/pull/168
* Major updates to docs by kibaekkim in https://github.com/APPFL/APPFL/pull/172
* Easy installation of SZ compressor using `appfl-install-compressor` by Zilinghan

New Contributors
* kaveenh made their first contribution in https://github.com/APPFL/APPFL/pull/163

**Full Changelog**: https://github.com/APPFL/APPFL/compare/v0.4.1...v0.4.2

What's Changed
- Integrate authenticators (`NaiveAuthenticator` and `GlobusAuthenticator`) for gRPC communication protocol for secure federation 162
- Add documentations for authentication designs
- Add documentations for asynchronous FL algorithms

**Full Changelog**: https://github.com/APPFL/APPFL/compare/v0.4.0...v0.4.1

What's Changed
- Add four variants of lossy compressors (SZ2, SZ3, SZx, ZFP) to improve FL communication efficiency 155 from grantwilkins
- Resolve file system race condition for globus compute 158 from yim0331
- Resolve `invalid load key` error for MPI communicator in https://github.com/APPFL/APPFL/commit/d5f2573beb86e816746b5180d1e692f90630335b by Zilinghan

Resolve a new bug `ModuleNotFoundError: No module named 'appfl.comm.globus_compute.utils'`

What's Changed
In summary, this is a minor release mainly with the focus on resolving the problem that `appfl.comm` is not in the current released version, together with few other minor changes with details below

- Rename the package from Argonne Privacy-Preserving Federated Learning to **_Advanced_** Privacy-Preserving Federated Learning 154
- Resolve the device error when using DP on GPU 150
- Resolve `appfl.comm ModuleNotFoundError` 156

What's Changed
In summary, this is a release of a major change of the APPFL repository with the refactor of the codebase and the addition of several new capabilities. In details:
* Add examples on CELEBA and FEMNIST datasets with a new MPI communicator for large models by yim0331
* Add asynchronous FL algorithms [FedAsync](https://arxiv.org/pdf/1903.03934.pdf), [FedBuffer](https://proceedings.mlr.press/v151/nguyen22b/nguyen22b.pdf), and [FedCompass](https://arxiv.org/pdf/2309.14675.pdf) by Zilinghan and ShellyRiver
* Add example for personalized FL by shourya01
* Add globus compute (formerly funcX) as a communicator by Zilinghan and hthieu166
* Allow use to use custom loss and custom evaluation metric in the FL experiments by Zilinghan
* Document improvements by Zilinghan and minseok-ryu