"binary classification" Papers
17 papers found
A No Free Lunch Theorem for Human-AI Collaboration
Kenny Peng, Nikhil Garg, Jon Kleinberg
AAAI 2025paperarXiv:2411.15230
5
citations
Balancing Positive and Negative Classification Error Rates in Positive-Unlabeled Learning
Ximing Li, Yuanchao Dai, Bing Wang et al.
NEURIPS 2025poster
Efficient PAC Learning for Realizable-Statistic Models via Convex Surrogates
Shivani Agarwal
NEURIPS 2025poster
Estimating Model Performance Under Covariate Shift Without Labels
Jakub Białek, Juhani Kivimäki, Wojciech Kuberski et al.
NEURIPS 2025posterarXiv:2401.08348
6
citations
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Binghui Li, Zhixuan Pan, Kaifeng Lyu et al.
ICLR 2025posterarXiv:2410.10322
On Agnostic PAC Learning in the Small Error Regime
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas
NEURIPS 2025spotlightarXiv:2502.09496
Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
Yufan Li, Pragya Sur
NEURIPS 2025spotlightarXiv:2502.15131
Provable weak-to-strong generalization via benign overfitting
David Wu, Anant Sahai
ICLR 2025posterarXiv:2410.04638
14
citations
QuanDA: Quantile-Based Discriminant Analysis for High-Dimensional Imbalanced Classification
Qian Tang, Yuwen Gu, Boxiang Wang
NEURIPS 2025poster
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model
Kaito Takanami, Takashi Takahashi, Ayaka Sakata
NEURIPS 2025posterarXiv:2501.16226
2
citations
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis et al.
ICML 2024poster
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets
Magzhan Gabidolla, Arman Zharmagambetov, Miguel Carreira-Perpinan
ICML 2024poster
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
Elvis Dohmatob
ICML 2024poster
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
Martin Mihelich, François Castagnos, Charles Dognin
ICML 2024poster
Positive and Unlabeled Learning with Controlled Probability Boundary Fence
Changchun Li, Yuanchao Dai, Lei Feng et al.
ICML 2024poster
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
ICML 2024posterarXiv:2307.06887
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
ICML 2024posterarXiv:2305.16817