Zhang, Fred

13 publications

ICLR 2025 ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip Tetlock

ICLR 2024 Adaptive Regret for Bandits Made Possible: Two Queries Suffice Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David Woodruff, Elad Hazan

NeurIPS 2024 Approaching Human-Level Forecasting with Language Models Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt

ICLR 2024 Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Fred Zhang, Neel Nanda

AISTATS 2023 Bayesian Strategy-Proof Facility Location via Robust Estimation Emmanouil Zampetakis, Fred Zhang

NeurIPS 2023 Constant Approximation for Individual Preference Stable Clustering Anders Aamand, Justin Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang

NeurIPS 2023 On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds David Woodruff, Fred Zhang, Samson Zhou

ICLR 2023 Robust Algorithms on Adaptive Inputs from Bounded Adversaries Yeshwanth Cherapanamjeri, Sandeep Silwal, David Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou

ICML 2022 Faster Fundamental Graph Algorithms via Learned Predictions Justin Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang

NeurIPS 2022 Optimal Query Complexities for Dynamic Trace Estimation David Woodruff, Fred Zhang, Richard Zhang

COLT 2020 A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang

NeurIPS 2020 Optimal Robustness-Consistency Trade-Offs for Learning-Augmented Online Algorithms Alexander Wei, Fred Zhang

NeurIPS 2020 Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization Sam Hopkins, Jerry Li, Fred Zhang