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Journal Articles
- 2022
[j1]Jelena Diakonikolas, Puqian Wang:
Potential Function-Based Framework for Minimizing Gradients in Convex and Min-Max Optimization. SIAM J. Optim. 32(3): 1668-1697 (2022)
Conference and Workshop Papers
- 2024
- [c4]Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas:
Robustly Learning Single-Index Models via Alignment Sharpness. ICML 2024 - 2023
- [c3]Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis:
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. COLT 2023: 2211-2239 - [c2]Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas:
Robustly Learning a Single Neuron via Sharpness. ICML 2023: 36541-36577 - [c1]Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis:
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. NeurIPS 2023
Informal and Other Publications
- 2024
- [i5]Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas:
Robustly Learning Single-Index Models via Alignment Sharpness. CoRR abs/2402.17756 (2024) - 2023
- [i4]Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas:
Robustly Learning a Single Neuron via Sharpness. CoRR abs/2306.07892 (2023) - [i3]Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis:
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. CoRR abs/2306.16352 (2023) - [i2]Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis:
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. CoRR abs/2307.08438 (2023) - 2021
- [i1]Jelena Diakonikolas, Puqian Wang:
Potential Function-based Framework for Making the Gradients Small in Convex and Min-Max Optimization. CoRR abs/2101.12101 (2021)
Coauthor Index
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