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ORCIDNikolaos Tsilivis 0002
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- affiliation: New York University, Center for Data Science
Other persons with the same name
- Nikos Tsilivis 0001
![[0000-0002-4757-6352]](/https://anthro-https-dblp.org/img/orcid-mark.12x12.png "0000-0002-4757-6352")
(aka: Nikolaos Tsilivis 0001) — National Technical University of Athens, School of Electrical and Computer Engineering, Greece
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2020 – today
- 2026
[j3]Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe:
On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds. Trans. Mach. Learn. Res. 2026 (2026)- [i15]Nirmit Joshi, Roey Magen, Nathan Srebro, Nikolaos Tsilivis, Gal Vardi:
Learning to Think from Multiple Thinkers. CoRR abs/2604.24737 (2026) - [i14]Nikolaos Tsilivis, Nirmit Joshi, Marko Medvedev, Julia Kempe, Nati Srebro:
Learning through Internalization. CoRR abs/2606.20937 (2026) - 2025
- [c4]Nikolaos Tsilivis, Gal Vardi, Julia Kempe:
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. ICLR 2025 - [i13]Nikolaos Tsilivis, Eran Malach, Karen Ullrich, Julia Kempe:
How Reinforcement Learning After Next-Token Prediction Facilitates Learning. CoRR abs/2510.11495 (2025) - [i12]Karen Ullrich, Jingtong Su, Claudia Shi, Arjun Subramonian, Amir Bar, Ivan Evtimov, Nikolaos Tsilivis, Randall Balestriero, Julia Kempe, Mark Ibrahim:
OpenApps: Simulating Environment Variations to Measure UI-Agent Reliability. CoRR abs/2511.20766 (2025) - 2024
- [j2]Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe:
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks. Trans. Mach. Learn. Res. 2024 (2024) - [j1]Jingtong Su, Ya Shi Zhang, Nikolaos Tsilivis, Julia Kempe:
On the Robustness of Neural Collapse and the Neural Collapse of Robustness. Trans. Mach. Learn. Res. 2024 (2024) - [c3]Nikolaos Tsilivis, Natalie Frank, Nati Srebro, Julia Kempe:
The Price of Implicit Bias in Adversarially Robust Generalization. NeurIPS 2024 - [c2]Ezra Edelman, Nikolaos Tsilivis, Benjamin L. Edelman, Eran Malach, Surbhi Goel:
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. NeurIPS 2024 - [i11]Benjamin L. Edelman, Ezra Edelman, Surbhi Goel, Eran Malach, Nikolaos Tsilivis:
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains. CoRR abs/2402.11004 (2024) - [i10]Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe:
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks. CoRR abs/2404.19640 (2024) - [i9]Nikolaos Tsilivis, Natalie Frank, Nathan Srebro, Julia Kempe:
The Price of Implicit Bias in Adversarially Robust Generalization. CoRR abs/2406.04981 (2024) - [i8]Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe:
On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds. CoRR abs/2410.16073 (2024) - [i7]Nikolaos Tsilivis, Gal Vardi, Julia Kempe:
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. CoRR abs/2410.22069 (2024) - 2023
- [i6]William Merrill, Nikolaos Tsilivis, Aman Shukla:
A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks. CoRR abs/2303.11873 (2023) - [i5]Francesco Cagnetta, Deborah Oliveira, Mahalakshmi Sabanayagam, Nikolaos Tsilivis, Julia Kempe:
Kernels, Data & Physics. CoRR abs/2307.02693 (2023) - [i4]Jingtong Su, Ya Shi Zhang, Nikolaos Tsilivis, Julia Kempe:
On the Robustness of Neural Collapse and the Neural Collapse of Robustness. CoRR abs/2311.07444 (2023) - 2022
- [c1]Nikolaos Tsilivis, Julia Kempe:
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? NeurIPS 2022 - [i3]William Merrill, Nikolaos Tsilivis:
Extracting Finite Automata from RNNs Using State Merging. CoRR abs/2201.12451 (2022) - [i2]Nikolaos Tsilivis, Jingtong Su, Julia Kempe:
Can we achieve robustness from data alone? CoRR abs/2207.11727 (2022) - [i1]Nikolaos Tsilivis, Julia Kempe:
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? CoRR abs/2210.05577 (2022)
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