arXiv Machine Learning By Ziyuan Huang, Lina Alkarmi, Mingyan Liu

Multi-Level Strategic Classification: Incentivizing Improvement through Promotion and Relegation Dynamics

Read the original on arXiv Machine Learning →

arXiv:2602. 11439v3 Announce Type: replace Abstract: Strategic classification studies the problem where self-interested individuals or agents manipulate their response to obtain favorable decision outcomes made by classifiers, typically turning to dishonest actions when they are less costly than genuine efforts.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 9

Beyond Rational Illusion: Behaviorally Realistic Strategic Classification

arXiv:2605. 19674v2 Announce Type: replace Abstract: Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes.

By Xinpeng Lv, Yunxin Mao, Renzhe Xu, Chunyuan Zheng, Yikai Chen, Haoxuan Li, Yang Shi, Jinxuan Yang, Zhouchen Lin, Yuanlong Chen, Yuanxing Zhang, Shaowu Yang, Wenjing Yang, Haotian Wang
arXiv Machine Learning
Jun 29

Non-Linear Strategic Classification Made Practical

arXiv:2606. 28204v1 Announce Type: cross Abstract: Algorithmic developments in Strategic Classification have been mostly limited to linear classifiers in settings where the best response has a closed-form solution or can be easily approximated.

By Jack Geary, Boyan Gao, Henry Gouk