Fred Zhang - RankMe

34 papers A* 16A 1Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics. CoRR Carter Blum, Katja Filippova, Ann Yuan, Asma Ghandeharioun, Julian Zimmert, Fred Zhang, Jessica Hoffmann, Tal Linzen, Martin Wattenberg, Lucas Dixon, Mor Geva
2025	A*	`conf`	ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities. ICLR Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip Tetlock
2024	A*	`conf`	Adaptive Regret for Bandits Made Possible: Two Queries Suffice. ICLR Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan
2024	J	`jnl`	Adaptive Regret for Bandits Made Possible: Two Queries Suffice. CoRR Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan
2024	A*	`conf`	Approaching Human-Level Forecasting with Language Models. NeurIPS Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt
2024	J	`jnl`	Approaching Human-Level Forecasting with Language Models. CoRR Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt
2024	J	`jnl`	ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities. CoRR Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip E. Tetlock
2024	A*	`conf`	Towards Best Practices of Activation Patching in Language Models: Metrics and Methods. ICLR Fred Zhang, Neel Nanda
2023	A	`conf`	Bayesian Strategy-Proof Facility Location via Robust Estimation. AISTATS Emmanouil Zampetakis, Fred Zhang
2023	A*	`conf`	Constant Approximation for Individual Preference Stable Clustering. NeurIPS Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	J	`jnl`	Constant Approximation for Individual Preference Stable Clustering. CoRR Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
2023	J	`jnl`	Minimum Cut and Minimum ACM Trans. Algorithms Kyle Fox, Debmalya Panigrahi, Fred Zhang
2023	A*	`conf`	On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS David P. Woodruff, Fred Zhang, Samson Zhou
2023	A*	`conf`	Online Prediction in Sub-linear Space. SODA Binghui Peng, Fred Zhang
2023	A*	`conf`	Privately Estimating a Gaussian: Efficient, Robust, and Optimal. STOC Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang
2023	A*	`conf`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR David P. Woodruff, Fred Zhang, Samson Zhou
2023	J	`jnl`	Towards Best Practices of Activation Patching in Language Models: Metrics and Methods. CoRR Fred Zhang, Neel Nanda
2022	A*	`conf`	Faster Fundamental Graph Algorithms via Learned Predictions. ICML Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	J	`jnl`	Faster Fundamental Graph Algorithms via Learned Predictions. CoRR Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
2022	J	`jnl`	Online Prediction in Sub-linear Space. CoRR Binghui Peng, Fred Zhang
2022	A*	`conf`	Optimal Query Complexities for Dynamic Trace Estimation. NeurIPS David P. Woodruff, Fred Zhang, Richard Zhang
2022	J	`jnl`	Optimal Query Complexities for Dynamic Trace Estimation. CoRR David P. Woodruff, Fred Zhang, Qiuyi Zhang
2022	J	`jnl`	Privately Estimating a Gaussian: Efficient, Robust and Optimal. CoRR Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang
2020	A*	`conf`	A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates. COLT Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang
2020	A*	`conf`	Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. NeurIPS Alexander Wei, Fred Zhang
2020	J	`jnl`	Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. CoRR Alexander Wei, Fred Zhang
2020	A*	`conf`	Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. NeurIPS Samuel B. Hopkins, Jerry Li, Fred Zhang
2020	J	`jnl`	Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. CoRR Samuel B. Hopkins, Jerry Li, Fred Zhang
2019	J	`jnl`	A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates. CoRR Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang
2019	A*	`conf`	Minimum Cut and Minimum k-Cut in Hypergraphs via Branching Contractions. SODA Kyle Fox, Debmalya Panigrahi, Fred Zhang
2019	A*	`conf`	SGD on Neural Networks Learns Functions of Increasing Complexity. NeurIPS Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Benjamin L. Edelman, Fred Zhang, Boaz Barak
2019	J	`jnl`	SGD on Neural Networks Learns Functions of Increasing Complexity. CoRR Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Benjamin L. Edelman, Fred Zhang, Boaz Barak