google-deepmind/wtos_agglabels_uai25

google-deepmind/wtos_agglabels_uai25

Language: Python

License: Apache-2.0

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Created: 2025-06-26T21:09:15Z

Pushed: 2025-06-26T21:12:06Z

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README:

wtos_agglabels_uai25

This repository accompanies the publication

> Weak to Strong Learning from Aggregate Labels. > *UAI 2025 (Main Conference Poster)*

There are independent directories for each dataset defined in the paper:

• Real contains preprocessing scripts and model training scripts for the UCI

experiments discussed in the paper.

• Synthetic contains preprocessing scripts and model training scripts for

the synthetic experiments discussed in the paper.

Installation

• Install XManager
• Install

Docker

• (Optional, Recommended) Make a virtual environment: `cd python -m venv

.venv source .venv/bin/activate`

• Run pip install -r requirements.txt from w2s/ folder

• Run the following: docker volume create boosting

Usage

Setup for Real:

• Download the UCI Heart, Australian, Adult datasets from the following links:
• Save Heart as a csv file wtos_agglabels_uai25/w2s/data/heart.csv
• Save Australian as a csv file wtos_agglabels_uai25/w2s/data/australian.csv
• Save Adult as a csv file wtos_agglabels_uai25/w2s/data/adult.csv

Launch:

• Define the dataset to be use in Real/xm_launch.py and other hyperparameters

as well.

• To create and save cross-validation splits set save_dataloader_cv to True.
• Run .venv/bin/xmanager launch Real/xm_launch.py

Setup for Synthetic:

Launch:

• Define the dataset to be use in Synthetic/xm_launch.py and other

hyperparameters as well.

• To create and save 15-fold cross-validation splits set save_dataloader_cv

to True.

• Run .venv/bin/xmanager launch Synthetic/xm_launch.pyfrom w2s folder.

Citing this work

@inproceedings{
makhija2025weak,
title={Weak to Strong Learning from Aggregate Labels},
author={Yukti Makhija and Rishi Saket},
booktitle={The 41st Conference on Uncertainty in Artificial Intelligence},
year={2025},
url={https://openreview.net/forum?id=VYNTQXski0}
}

License and disclaimer

Copyright 2025 Google LLC

All software is licensed under the Apache License, Version 2.0 (Apache 2.0); you may not use this file except in compliance with the Apache 2.0 license. You may obtain a copy of the Apache 2.0 license at: https://www.apache.org/licenses/LICENSE-2.0

All other materials are licensed under the Creative Commons Attribution 4.0 International License (CC-BY). You may obtain a copy of the CC-BY license at: https://creativecommons.org/licenses/by/4.0/legalcode

Unless required by applicable law or agreed to in writing, all software and materials distributed here under the Apache 2.0 or CC-BY licenses are distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the licenses for the specific language governing permissions and limitations under those licenses.

This is not an official Google product.