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Wenshuo Guo
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2020 – today
- 2024
- [j2]Wenshuo Guo, Fang-Wei Fu:
Two modifications for Loidreau's code-based cryptosystem. Appl. Algebra Eng. Commun. Comput. 35(5): 647-665 (2024) - 2023
- [c21]Kush Bhatia, Wenshuo Guo, Jacob Steinhardt:
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. AISTATS 2023: 11149-11171 - [c20]Romil Bhardwaj, Kirthevasan Kandasamy, Asim Biswal, Wenshuo Guo, Benjamin Hindman, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback. OSDI 2023: 623-643 - [c19]Wenshuo Guo
, Nika Haghtalab
, Kirthevasan Kandasamy
, Ellen Vitercik
:
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. EC 2023: 816 - [i25]Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik:
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. CoRR abs/2302.09700 (2023) - [i24]Kush Bhatia, Wenshuo Guo, Jacob Steinhardt:
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. CoRR abs/2302.12349 (2023) - 2022
- [j1]Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael I. Jordan:
Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias. Trans. Mach. Learn. Res. 2022 (2022) - [c18]Wenshuo Guo, Fangwei Fu:
Cryptanalysis and Repair of a Gabidulin Code Based Cryptosystem from ACISP 2018. ACISP 2022: 189-205 - [c17]Wenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback. AISTATS 2022: 6200-6224 - [c16]Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady:
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. AISTATS 2022: 6357-6386 - [c15]Wenshuo Guo, Fangwei Fu:
McEliece-Type Encryption Based on Gabidulin Codes with No Hidden Structure. Inscrypt 2022: 108-126 - [c14]Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan:
Partial Identification with Noisy Covariates: A Robust Optimization Approach. CLeaR 2022: 318-335 - [c13]Wenshuo Guo, Michael I. Jordan, Ellen Vitercik:
No-Regret Learning in Partially-Informed Auctions. ICML 2022: 8039-8055 - [c12]Wenshuo Guo, Michael I. Jordan, Angela Zhou:
Off-Policy Evaluation with Policy-Dependent Optimization Response. NeurIPS 2022 - [i23]Wenshuo Guo, Michael I. Jordan, Ellen Vitercik:
No-Regret Learning in Partially-Informed Auctions. CoRR abs/2202.10606 (2022) - [i22]Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan:
Partial Identification with Noisy Covariates: A Robust Optimization Approach. CoRR abs/2202.10665 (2022) - [i21]Wenshuo Guo, Michael I. Jordan, Angela Zhou:
Off-Policy Evaluation with Policy-Dependent Optimization Response. CoRR abs/2202.12958 (2022) - [i20]Sai Praneeth Karimireddy, Wenshuo Guo, Michael I. Jordan:
Mechanisms that Incentivize Data Sharing in Federated Learning. CoRR abs/2207.04557 (2022) - [i19]Wenshuo Guo, Fangwei Fu:
McEliece-type encryption based on Gabidulin codes with no hidden structure. IACR Cryptol. ePrint Arch. 2022: 1166 (2022) - 2021
- [c11]Wenshuo Guo, Michael I. Jordan, Tianyi Lin:
A Variational Inequality Approach to Bayesian Regression Games. CDC 2021: 795-802 - [c10]Wenshuo Guo, Karl Krauth, Michael I. Jordan, Nikhil Garg:
The Stereotyping Problem in Collaboratively Filtered Recommender Systems. EAAMO 2021: 6:1-6:10 - [c9]Celestine Mendler-Dünner, Wenshuo Guo, Stephen Bates, Michael I. Jordan:
Test-time Collective Prediction. NeurIPS 2021: 13719-13731 - [c8]Wenshuo Guo, Michael I. Jordan, Emmanouil Zampetakis
:
Robust Learning of Optimal Auctions. NeurIPS 2021: 21273-21284 - [i18]Wenshuo Guo, Michael I. Jordan, Tianyi Lin:
A Variational Inequality Approach to Bayesian Regression Games. CoRR abs/2103.13509 (2021) - [i17]Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael I. Jordan:
Multi-Source Causal Inference Using Control Variates. CoRR abs/2103.16689 (2021) - [i16]Wenshuo Guo, Fangwei Fu:
Two modifications for Loidreau's code-based cryptosystem. CoRR abs/2104.02254 (2021) - [i15]Wenshuo Guo, Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Online Learning of Competitive Equilibria in Exchange Economies. CoRR abs/2106.06616 (2021) - [i14]Celestine Mendler-Dünner, Wenshuo Guo, Stephen Bates, Michael I. Jordan:
Test-time Collective Prediction. CoRR abs/2106.12012 (2021) - [i13]Wenshuo Guo, Karl Krauth, Michael I. Jordan, Nikhil Garg:
The Stereotyping Problem in Collaboratively Filtered Recommender Systems. CoRR abs/2106.12622 (2021) - [i12]Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya Muthukumar, Ashwin Pananjady:
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. CoRR abs/2106.14866 (2021) - [i11]Wenshuo Guo, Fangwei Fu:
Expanded Gabidulin Codes and Their Application to Cryptography. CoRR abs/2107.01610 (2021) - [i10]Wenshuo Guo, Fangwei Fu:
Semilinear transformations in coding theory and their application to cryptography. CoRR abs/2107.03157 (2021) - [i9]Wenshuo Guo, Michael I. Jordan, Manolis Zampetakis:
Robust Learning of Optimal Auctions. CoRR abs/2107.06259 (2021) - [i8]Wenshuo Guo, Fangwei Fu:
Polynomial-Time Key Recovery Attack on the Lau-Tan Cryptosystem Based on Gabidulin Codes. CoRR abs/2112.15466 (2021) - [i7]Wenshuo Guo, Fangwei Fu:
Two modifications for Loidreau's code-based cryptosystem. IACR Cryptol. ePrint Arch. 2021: 440 (2021) - [i6]Wenshuo Guo, Fangwei Fu:
Expanded Gabidulin Codes and Their Application to Cryptography. IACR Cryptol. ePrint Arch. 2021: 906 (2021) - 2020
- [c7]Wenshuo Guo, Nhat Ho, Michael I. Jordan:
Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter. AISTATS 2020: 2088-2097 - [c6]Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht:
Neural Kernels Without Tangents. ICML 2020: 8614-8623 - [c5]Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Lutong Wang, Wenshuo Guo:
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models. NeurIPS 2020 - [c4]Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan:
Robust Optimization for Fairness with Noisy Protected Groups. NeurIPS 2020 - [i5]Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan:
Robust Optimization for Fairness with Noisy Protected Groups. CoRR abs/2002.09343 (2020) - [i4]Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht:
Neural Kernels Without Tangents. CoRR abs/2003.02237 (2020) - [i3]Wenshuo Guo, Mihaela Curmei, Serena Lutong Wang, Benjamin Recht, Michael I. Jordan:
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty. CoRR abs/2007.05647 (2020) - [i2]Karl Krauth, Sarah Dean, Alex Zhao, Wenshuo Guo, Mihaela Curmei, Benjamin Recht, Michael I. Jordan:
Do Offline Metrics Predict Online Performance in Recommender Systems? CoRR abs/2011.07931 (2020)
2010 – 2019
- 2019
- [i1]Wenshuo Guo, Nhat Ho, Michael I. Jordan:
Accelerated Primal-Dual Coordinate Descent for Computational Optimal Transport. CoRR abs/1905.09952 (2019) - 2017
- [c3]Wenshuo Guo, Juntao Wang
, Kwok Yip Szeto:
Spin Model of Two Random Walkers in Complex Networks. COMPLEX NETWORKS 2017: 555-566 - [c2]Wenshuo Guo, Kwok Yip Szeto:
Minimization of Systemic Risk for Directed Network Using Genetic Algorithm. EvoApplications (1) 2017: 3-16 - [c1]Juntao Wang
, Wenshuo Guo, Kwok Yip Szeto:
Optimization of financial network stability by genetic algorithm. WI 2017: 517-524
Coauthor Index
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last updated on 2024-08-22 19:43 CEST by the dblp team
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