Skip to content
@Optimization-AI

Optimization for Machine Learning and AI

OptMAI Lab at Texas A&M University directed by Professor Tianbao Yang

Pinned Loading

  1. LibAUC Public

    LibAUC: A Deep Learning Library for X-Risk Optimization

    Python 305 38

  2. DisCO Public

    Discriminative Constrained Optimization for Large Reasoning Models

    Python

  3. DRRho-CLIP Public

    Model steering for CLIP training

    Python

  4. DFT Public

    Discriminative Fine-tuning of LLMs without reward models and human preference data

    Python

  5. FastCLIP Public

    Distributed Optimization Infra for learning CLIP models

    Python 25 1

  6. SogCLR Public

    Stochastic Optimization for Global Contrastive Learning without Large Mini-batches

    Python 20 5

Repositories

Showing 10 of 15 repositories
  • DisCO Public

    Discriminative Constrained Optimization for Large Reasoning Models

    Python 0 MIT 0 0 0 Updated May 20, 2025
  • DRRho-CLIP Public

    Model steering for CLIP training

    Python 0 MIT 0 0 0 Updated May 19, 2025
  • DFT Public

    Discriminative Fine-tuning of LLMs without reward models and human preference data

    Python 0 0 0 0 Updated May 18, 2025
  • DistTempNet Public

    Distributed version of TempNet.

    Python 0 1 0 0 Updated Apr 20, 2025
  • FastCLIP Public

    Distributed Optimization Infra for learning CLIP models

    Python 25 MIT 1 0 0 Updated Oct 3, 2024
  • LibAUC Public

    LibAUC: A Deep Learning Library for X-Risk Optimization

    Python 305 MIT 38 0 0 Updated Sep 2, 2024
  • TempNet Public Forked from zhqiu/TempNet

    To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO

    Python 0 5 0 0 Updated Apr 9, 2024
  • NeurIPS2021_SOAP Public

    Official implementation of the paper "Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence" published on Neurips2021.

    Python 20 1 1 0 Updated Oct 9, 2023
  • ICML2023_LDR Public Forked from DixianZhu/LDR

    The official implementation from 'Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity' ICML2023

    Python 0 Apache-2.0 1 0 0 Updated Jun 6, 2023
  • ICML2023_FeDXL Public

    Official implementation of ICML 2023 paper "FeDXL: Provable Federated Learning for Deep X-Risk Optimization".

    Python 2 0 0 0 Updated May 30, 2023
View all repositories

People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages

Loading…

Most used topics

Loading…