Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

1 code implementation • 27 Mar 2024 • Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan

We find that current state-of-the-art empirical techniques offer sub-optimal performance on these practical, non-decomposable performance objectives.

Fairness imbalanced classification

Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics

1 code implementation • 28 Apr 2023 • Harsh Rangwani, Shrinivas Ramasubramanian, Sho Takemori, Kato Takashi, Yuhei Umeda, Venkatesh Babu Radhakrishnan

Using the proposed CSST framework, we obtain practical self-training methods (for both vision and NLP tasks) for optimizing different non-decomposable metrics using deep neural networks.