On the consistency of auc optimization

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August undefined, 2024

Webis whether the optimization of surrogate losses is consistent with AUC. 1.1. Our Contribution We ﬁrst introduce the generalized calibration for AUC optimization based on minimizing the pairwise surrogate losses, and ﬁnd that the generalized cal-ibration is necessary yet insuﬃcient for AUC consistency. For example, hinge

Learning With Multiclass AUC: Theory and Algorithms - PubMed

Web只有满足一致性，我们才可以替换。高老师的这篇文章On the Consistency of AUC Pairwise Optimization就证明了哪些替代损失函数是满足一致性的。通过替换不同的损失函数， … Web18 de set. de 2024 · Moreover, because of the high complexity of the AUC optimization, many efforts have been devoted to developing efficient algorithms, such as batch and online learnings (Ying, Wen, and Lyu 2016;Gu ... did musk fire the view cast

On the Consistency of AUC Pairwise Optimization

Webwith AUC, as will be shown by Theorem 1 (Section 4). In contrast, loss functions such as hinge loss are proven to be inconsistent with AUC (Gao & Zhou, 2012). As aforementioned, the classical online setting can-not be applied to one-pass AUC optimization because, even if the optimization problem of Eq. (2) has a closed Web10 de mai. de 2024 · We develop the Data Removal algorithm for AUC optimization (DRAUC), and the basic idea is to adjust the trained model according to the removed data, rather than retrain another model again from ... WebTo optimize AUC, many learning approaches have been developed, most working with pairwise surro-gate losses. Thus, it is important to study the AUC consistency based on … did musk fire the view

Data Removal from an AUC Optimization Model SpringerLink

Large-scale Robust Deep AUC Maximization: A New Surrogate …

WebAUC optimization on graph data, which is ubiquitous and important, is seldom studied. Different from regular data, AUC optimization on graphs suffers from not only the class imbalance but also topology imbalance. To solve the complicated imbalance problem, we propose a unified topology-aware AUC optimization framework. Web8. One-pass AUC optimization W. Gao, R. Jin, S. Zhu, and Z. Zhou 2013 153 ICML [47] 9. Efficient AUC optimization for classification T. Calders and S. Jaroszewicz 2007 128 PKDD [19] 10. Stochastic online AUC maximization Y. Ying, L. … did musk create teslaWebWe refer to the method minimizing the PU-AUC risk as PU-AUC optimization. We will theoretically investigate the superiority of RPU in Sect. 4.1. To develop a semi-supervised AUC optimization method later, we also consider AUC optimization form negative and unlabeled data, which can be regarded as a mirror of PU-AUC optimization. did musk delete his twitter account

"Web30 de set. de 2024 · Recently, there is considerable work on developing efficient stochastic optimization algorithms for AUC maximization. However, most of them focus on the least square loss which may be not the best option in practice. The main difficulty for dealing with the general convex loss is the pairwise nonlinearity w.r.t. the sampling distribution … " - On the consistency of auc optimization

On the consistency of auc optimization

On the consistency of AUC pairwise optimization Proceedings of …

Web6 de dez. de 2024 · Deep AUC Maximization (DAM) is a new paradigm for learning a deep neural network by maximizing the AUC score of the model on a dataset. Most previous … WebIn this section, we ﬁrst propose an AUC optimization method from positive and unlabeled data and then extend it to a semi-supervised AUC optimization method. 3.1 PU-AUC Optimization In PU learning, we do not have negative data while we can use unlabeled data drawn from marginal density p(x) in addition to positive data: X U:= fxU k g n U k=1 ...

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WebAUC (Area Under ROC Curve) has been an impor-tant criterion widely used in diverse learning tasks. To optimize AUC, many learning approaches have been developed, most … Web1 de jan. de 2024 · Request PDF On Jan 1, 2024, Zhenhuan Yang and others published Stochastic AUC optimization with general loss Find, read and cite all the research you need on ResearchGate

WebAUC directly since such direct optimization often leads to NP-hard problem. Instead, surrogate loss functions are usually optimized, such as exponential loss [FISS03, RS09] … Web30 de set. de 2024 · Recently, there is considerable work on developing efficient stochastic optimization algorithms for AUC maximization. However, most of them focus on the …

Web18 de jul. de 2024 · Classification: Check Your Understanding (ROC and AUC) Explore the options below. This is the best possible ROC curve, as it ranks all positives above all negatives. It has an AUC of 1.0. In practice, … Web5 de dez. de 2016 · It is shown that AUC optimization can be equivalently formulated as a convex-concave saddle point problem and a stochastic online algorithm (SOLAM) is …

Web23 de jun. de 2015 · To optimize AUC, many learning approaches have been developed, most working with pairwise surrogate losses. Thus, it is important to study the AUC consistency based on minimizing pairwise surrogate losses. In this paper, we introduce the generalized calibration for AUC optimization, and prove that it is a necessary condition …

Web1 de jul. de 2016 · In this work, we focus on one-pass AUC optimization that requires going through training data only once without having to store the entire training dataset. ... Z. … did musk fire twitter ceoWeb1 de jul. de 2016 · AUC consistency is defined on all measurable functions as in the work of [1], [31], [36]. An interesting problem is to study AUC consistency on linear function spaces for further work. Gao and Zhou [19] gave a sufficient condition and a necessary condition for AUC consistency based on minimizing pairwise surrogate losses, but it … did musk finally buy twitterWeb3 de ago. de 2012 · Based on the previous analysis, we present a new sufficient condition for AUC consistency, and the detailed proof is deferred to Section 6.4. Theorem 2. The … did musk found paypalWebfor AUC optimization the focus is mainly on pairwise loss, as the original loss is also deﬁned this way and consistency results for pairwise surrogate losses are available as well [27]. While these approaches can signiﬁcantly increase scalability [28], for very large datasets their sequential nature can still be problematic. did musk have to buy twitterWeb2 de ago. de 2012 · AUC is an important performance measure and many algorithms have been devoted to AUC optimization, mostly by minimizing a surrogate convex loss on a … did musk have to buy the resla nameWeb只有满足一致性，我们才可以替换。高老师的这篇文章On the Consistency of AUC Pairwise Optimization就证明了哪些替代损失函数是满足一致性的。通过替换不同的损失函数，可以得到不同的目标式，从而进行求解。关于怎么求解AUC的文章也有很多，比如说： did musk get the vaccineWeb3 de ago. de 2012 · Thus, the consistency of AUC is crucial; however, it has been almost untouched before. In this paper, we provide a sufficient condition for the asymptotic consistency of learning approaches based on surrogate loss functions. Based on this result, we prove that exponential loss and logistic loss are consistent with AUC, but … did musk invent anything