Christopher Liaw

Most-cited papers

Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks
P. Bartlett, Nick Harvey, Christopher Liaw, Abbas Mehrabian
2017Journal of machine learning research584 citations
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Nearly-tight VC-dimension bounds for piecewise linear neural networks
Nick Harvey, Christopher Liaw, Abbas Mehrabian
2017Annual Conference Computational Learning Theory192 citations
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Tight Analyses for Non-Smooth Stochastic Gradient Descent
Nicholas J. A. Harvey, Christopher Liaw, Y. Plan, Sikander Randhawa
2018Annual Conference Computational Learning Theory189 citations
Semantic Scholar
A simple tool for bounding the deviation of random matrices on geometric sets
Christopher Liaw, Abbas Mehrabian, Y. Plan, R. Vershynin
2016arXiv.org82 citations Open access
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Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
H. Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw +2 more
2018Neural Information Processing Systems69 citations
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Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes
H. Ashtiani, S. Ben-David, Nicholas J. A. Harvey, Christopher Liaw +2 more
2017Journal of the ACM61 citations
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Private and polynomial time algorithms for learning Gaussians and beyond
H. Ashtiani, Christopher Liaw
2021Annual Conference Computational Learning Theory55 citations
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Greedy and Local Ratio Algorithms in the MapReduce Model
Nicholas J. A. Harvey, Christopher Liaw, Paul Liu
2018ACM Symposium on Parallelism in Algorithms and Architectures45 citations Open access
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Simple and optimal high-probability bounds for strongly-convex stochastic gradient descent
Nicholas J. A. Harvey, Christopher Liaw, Sikander Randhawa
2019arXiv.org41 citations
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Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
Jamil Arbas, H. Ashtiani, Christopher Liaw
2023International Conference on Machine Learning36 citations Open access
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Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta +1 more
2020AAAI Conference on Artificial Intelligence33 citations Open access
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Optimal anytime regret with two experts
Nicholas J. A. Harvey, Christopher Liaw, E. Perkins, Sikander Randhawa
2020Mathematical Statistics and Learning22 citations Open access
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Efficiency of Non-Truthful Auctions in Auto-bidding: The Power of Randomization
Christopher Liaw, Aranyak Mehta, Andrés Perlroth
2023The Web Conference21 citations Open access
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Efficiency of non-truthful auctions under auto-bidding
Christopher Liaw, Aranyak Mehta, Andrés Perlroth
2022arXiv.org17 citations Open access
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Privately Learning Mixtures of Axis-Aligned Gaussians
Ishaq Aden-Ali, H. Ashtiani, Christopher Liaw
2021Neural Information Processing Systems17 citations
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Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
Nicholas J. A. Harvey, Christopher Liaw, Tasuku Soma
2020Neural Information Processing Systems17 citations
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The Value of Information Concealment
Hu Fu, Christopher Liaw, Pin-Yan Lu, Zhihao Gavin Tang
2017ACM-SIAM Symposium on Discrete Algorithms14 citations Open access
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Improved Online Learning Algorithms for CTR Prediction in Ad Auctions
Zhe Feng, Christopher Liaw, Zixin Zhou
2024International Conference on Machine Learning11 citations
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The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue
Hu Fu, Christopher Liaw, Sikander Randhawa
2019ACM Conference on Economics and Computation11 citations Open access
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Continuous Prediction with Experts' Advice
V. S. Portella, Christopher Liaw, Nicholas J. A. Harvey
2022Journal of machine learning research9 citations Open access
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The Power of Two-Sided Recruitment in Two-Sided Markets
Yang Cai, Christopher Liaw, Aranyak Mehta, Ming-Fei Zhao
2023Symposium on the Theory of Computing5 citations Open access
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Tight Load Balancing Via Randomized Local Search
P. Berenbrink, Peter Kling, Christopher Liaw, Abbas Mehrabian
2017IEEE International Parallel and Distributed Processing Symposium5 citations Open access
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Settling the Sample Complexity for Learning Mixtures of Gaussians
H. Ashtiani, S. Ben-David, Nicholas J. A. Harvey, Christopher Liaw +2 more
20175 citations
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Approximation Schemes for Covering and Packing in the Streaming Model
Christopher Liaw, Paul Liu, R. Reiss
2017Canadian Conference on Computational Geometry4 citations
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Rainbow Hamilton cycles and lopsidependency
Nicholas J. A. Harvey, Christopher Liaw
2017Discrete Mathematics3 citations Open access
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User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization
Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta +1 more
2023The Web Conference2 citations Open access
Semantic Scholar
Optimal anytime regret for two experts
Nicholas J. A. Harvey, Christopher Liaw, Edwin A. Perkins, Sikander Randhawa
2020IEEE Annual Symposium on Foundations of Computer Science1 citations
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Optimal algorithms for experts and mixtures of Gaussians
Christopher Liaw
20200 citations
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