Jun 23, 2022 · Motivated by this, we present the first trial in this paper to optimize this new metric. The critical challenge along this course lies in the ...

To address this issue, we propose a generic framework to construct surrogate optimization problems, which supports efficient end-to-end training with deep ...

Jun 30, 2023 · The critical challenge along this course lies in the difficulty of per- forming gradient-based optimization with end-to-end stochastic training, ...

To address this issue, we propose a generic framework to construct surrogate optimization problems, which supports efficient end-to-end training with deep ...

A generic framework to construct surrogate optimization problems, which supports efficient end-to-end training with deep learning, is proposed and ...

Jun 23, 2022 · The Area Under the ROC Curve (AUC) is a crucial metric for machine learning, which evaluates the average performance over all possible True ...

Jun 23, 2022 · Abstract—The Area Under the ROC Curve (AUC) is a crucial metric for machine learning, which evaluates the average performance over all ...

This is an official PyTorch code for our accepted paper "When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC" in ...

Inspired by this fact, we present the first trial to optimize the TPAUC metric with an end-to-end framework. The major challenge of this task is that the ...

Jul 18, 2021 · How to optimize TPAUC (AUC with FPR upper bound and a TPR lower bound) in an end-to-end manner? A Bi-level reformulation of ERM framework for ...