Qiuyi (Richard) Zhang

Affiliations:
  • Google Brain, Pittsburgh, PA, USA
  • University of California at Berkeley, Department of Mathematics, CA, USA
  • Princeton University, NJ, USA


According to our database1, Qiuyi (Richard) Zhang authored at least 23 papers between 2017 and 2023.

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Bibliography

2023
Computing Approximate 𝓁<sub>p</sub> Sensitivities.
CoRR, 2023

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products.
CoRR, 2023

Robust Algorithms on Adaptive Inputs from Bounded Adversaries.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Optimal Query Complexities for Dynamic Trace Estimation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Learning Universal Hyperparameter Optimizers with Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Leveraging Initial Hints for Free in Stochastic Linear Bandits.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021
Using Constrained-INC for Large-Scale Gene Tree and Species Tree Estimation.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Optimal Sketching for Trace Estimation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Learning the gravitational force law and other analytic functions.
CoRR, 2020

Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Span Recovery for Deep Neural Networks with Applications to Input Obfuscation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Gradientless Descent: High-Dimensional Zeroth-Order Optimization.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Fast Algorithms for Interior Point Methods.
PhD thesis, 2019

Constrained incremental tree building: new absolute fast converging phylogeny estimation methods with improved scalability and accuracy.
Algorithms Mol. Biol., 2019

Optimal sequence length requirements for phylogenetic tree reconstruction with indels.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Regularized Weighted Low Rank Approximation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Solving Empirical Risk Minimization in the Current Matrix Multiplication Time.
Proceedings of the Conference on Learning Theory, 2019

Using INC Within Divide-and-Conquer Phylogeny Estimation.
Proceedings of the Algorithms for Computational Biology - 6th International Conference, 2019

2018
New Absolute Fast Converging Phylogeny Estimation Methods with Improved Scalability and Accuracy.
Proceedings of the 18th International Workshop on Algorithms in Bioinformatics, 2018

Convergence Results for Neural Networks via Electrodynamics.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017
Forbidden directed minors and Kelly-width.
Theor. Comput. Sci., 2017

Electron-Proton Dynamics in Deep Learning.
CoRR, 2017


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