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2020 – today
- 2024
[c15]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. ICLR 2024- [c14]Fred Zhang, Neel Nanda:
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods. ICLR 2024 - [i15]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. CoRR abs/2401.09278 (2024) - [i14]Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt:
Approaching Human-Level Forecasting with Language Models. CoRR abs/2402.18563 (2024) - [i13]Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip E. Tetlock:
ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities. CoRR abs/2409.19839 (2024) - 2023
- [j1]Kyle Fox
, Debmalya Panigrahi, Fred Zhang:
Minimum Cut and Minimum k-Cut in Hypergraphs via Branching Contractions. ACM Trans. Algorithms 19(2): 13:1-13:22 (2023) - [c13]Emmanouil Zampetakis, Fred Zhang:
Bayesian Strategy-Proof Facility Location via Robust Estimation. AISTATS 2023: 4196-4208 - [c12]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR 2023 - [c11]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. NeurIPS 2023 - [c10]David P. Woodruff, Fred Zhang, Samson Zhou:
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS 2023 - [c9]Binghui Peng, Fred Zhang:
Online Prediction in Sub-linear Space. SODA 2023: 1611-1634 - [c8]Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang:
Privately Estimating a Gaussian: Efficient, Robust, and Optimal. STOC 2023: 483-496 - [i12]David P. Woodruff, Fred Zhang, Samson Zhou:
Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR abs/2303.01709 (2023) - [i11]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR abs/2304.07413 (2023) - [i10]Fred Zhang, Neel Nanda:
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods. CoRR abs/2309.16042 (2023) - [i9]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. CoRR abs/2309.16840 (2023) - 2022
- [c7]Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang:
Faster Fundamental Graph Algorithms via Learned Predictions. ICML 2022: 3583-3602 - [c6]David P. Woodruff, Fred Zhang, Richard Zhang:
Optimal Query Complexities for Dynamic Trace Estimation. NeurIPS 2022 - [i8]Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang:
Faster Fundamental Graph Algorithms via Learned Predictions. CoRR abs/2204.12055 (2022) - [i7]Binghui Peng, Fred Zhang:
Online Prediction in Sub-linear Space. CoRR abs/2207.07974 (2022) - [i6]David P. Woodruff, Fred Zhang, Qiuyi Zhang:
Optimal Query Complexities for Dynamic Trace Estimation. CoRR abs/2209.15219 (2022) - [i5]Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang:
Privately Estimating a Gaussian: Efficient, Robust and Optimal. CoRR abs/2212.08018 (2022) - 2020
- [c5]Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang:
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates. COLT 2020: 2598-2612 - [c4]Samuel B. Hopkins, Jerry Li, Fred Zhang:
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. NeurIPS 2020 - [c3]Alexander Wei, Fred Zhang:
Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. NeurIPS 2020 - [i4]Samuel B. Hopkins, Jerry Li, Fred Zhang:
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. CoRR abs/2007.15839 (2020) - [i3]Alexander Wei, Fred Zhang:
Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. CoRR abs/2010.11443 (2020)
2010 – 2019
- 2019
- [c2]Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Benjamin L. Edelman, Fred Zhang, Boaz Barak:
SGD on Neural Networks Learns Functions of Increasing Complexity. NeurIPS 2019: 3491-3501 - [c1]Kyle Fox, Debmalya Panigrahi, Fred Zhang:
Minimum Cut and Minimum k-Cut in Hypergraphs via Branching Contractions. SODA 2019: 881-896 - [i2]Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Benjamin L. Edelman, Fred Zhang, Boaz Barak:
SGD on Neural Networks Learns Functions of Increasing Complexity. CoRR abs/1905.11604 (2019) - [i1]Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang:
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates. CoRR abs/1908.04468 (2019)
Coauthor Index
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