{"total":14,"rows":[{"id":"2202.01331","title":"Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions","created":"2022-02-02","cited_by_count":31,"area":null},{"id":"2205.08078","title":"Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers","created":"2022-05-17","cited_by_count":30,"area":null},{"id":"2301.12554","title":"Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing","created":"2023-01-29","cited_by_count":18,"area":null},{"id":"2402.02263","title":"MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers","created":"2024-02-03","cited_by_count":16,"area":null},{"id":"2402.03625","title":"Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time","created":"2024-02-06","cited_by_count":11,"area":null},{"id":"2411.01088","title":"CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks","created":"2024-11-02","cited_by_count":4,"area":null},{"id":"2206.12169","title":"AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems","created":"2022-06-24","cited_by_count":3,"area":null},{"id":"2311.15165","title":"Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off","created":"2023-11-26","cited_by_count":2,"area":null},{"id":"2411.06848","title":"Generative Feature Training of Thin 2-Layer Networks","created":"2024-11-11","cited_by_count":2,"area":null},{"id":"2208.07464","title":"An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models","created":"2022-08-15","cited_by_count":1,"area":null},{"id":"2401.13624","title":"Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint","created":"2024-01-24","cited_by_count":1,"area":null},{"id":"2408.15969","title":"Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems","created":"2024-08-28","cited_by_count":0,"area":null},{"id":"2505.05740","title":"Deep-ICE: the first globally optimal algorithm for minimizing 0-1 loss in two-layer ReLU and maxout networks","created":"2025-05-09","cited_by_count":0,"area":null},{"id":"2606.19652","title":"Convex training of Lipschitz-regularized shallow neural networks","created":"2026-06-17","cited_by_count":0,"area":null}],"next_cursor":null}