Christopher Liaw

54 papers A* 18A 1B 3Journal 30Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Unified Approach to Submodular Maximization Under Noise.
CoRR
Kshipra Bhawalkar, Yang Cai, Zhe Feng, Christopher Liaw, Tao Lin
2025 B conf
Agnostic Private Density Estimation for GMMs via List Global Stability.
ALT
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2025 A* conf
Autobidding With Interdependent Values.
WWW
Martino Banchio, Kshipra Bhawalkar, Christopher Liaw, Aranyak Mehta, Andrés Perlroth
2025 J jnl
Equilibria and Learning in Modular Marketplaces.
CoRR
Kshipra Bhawalkar, Jeff Dean, Christopher Liaw, Aranyak Mehta, Neel Patel
2025 A* conf
Equilibrium Efficiency and Learning in Budgeted Procurement Marketplaces.
EC
Kshipra Bhawalkar, Jeff Dean, Christopher Liaw, Aranyak Mehta, Neel Patel
2025 J jnl
Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding.
CoRR
Christopher Liaw, Wennan Zhu
2024 J jnl
Agnostic Private Density Estimation via Stable List Decoding.
CoRR
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2024 J jnl
Auto-Bidding and Auctions in Online Advertising: A Survey.
SIGecom Exch.
Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo
2024 J jnl
Auto-bidding and Auctions in Online Advertising: A Survey.
CoRR
Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo
2024 J jnl
Continuous Prediction with Experts' Advice.
J. Mach. Learn. Res.
Nicholas J. A. Harvey, Christopher Liaw, Victor S. Portella
2024 A* conf
Efficiency of Non-Truthful Auctions in Auto-bidding with Budget Constraints.
WWW
Christopher Liaw, Aranyak Mehta, Wennan Zhu
2024 J jnl
Improved Online Learning Algorithms for CTR Prediction in Ad Auctions.
CoRR
Zhe Feng, Christopher Liaw, Zixin Zhou
2024 B conf
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples.
ALT
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2024 A* conf
The Power of Two-Sided Recruitment in Two-Sided Markets.
STOC
Yang Cai, Christopher Liaw, Aranyak Mehta, Mingfei Zhao
2024 A* conf
User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization.
WWW
Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta, Grigoris Velegkas
2023 J jnl
Efficiency of Non-Truthful Auctions in Auto-bidding with Budget Constraints.
CoRR
Christopher Liaw, Aranyak Mehta, Wennan Zhu
2023 A* conf
Efficiency of Non-Truthful Auctions in Auto-bidding: The Power of Randomization.
WWW
Christopher Liaw, Aranyak Mehta, Andrés Perlroth
2023 A* conf
Improved Online Learning Algorithms for CTR Prediction in Ad Auctions.
ICML
Zhe Feng, Christopher Liaw, Zixin Zhou
2023 J jnl
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples.
CoRR
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2023 A* conf
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models.
ICML
Jamil Arbas, Hassan Ashtiani, Christopher Liaw
2023 J jnl
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models.
CoRR
Jamil Arbas, Hassan Ashtiani, Christopher Liaw
2023 J jnl
The Power of Two-sided Recruitment in Two-sided Markets.
CoRR
Yang Cai, Christopher Liaw, Aranyak Mehta, Mingfei Zhao
2023 J jnl
User Response in Ad Auctions: An MDP Formulation of Long-Term Revenue Optimization.
CoRR
Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta
2022 J jnl
Continuous Prediction with Experts' Advice.
CoRR
Victor Sanches Portella, Christopher Liaw, Nicholas J. A. Harvey
2022 J jnl
Efficiency of non-truthful auctions under auto-bidding.
CoRR
Christopher Liaw, Aranyak Mehta, Andrés Perlroth
2022 A* conf
Private and polynomial time algorithms for learning Gaussians and beyond.
COLT
Hassan Ashtiani, Christopher Liaw
2021 A* conf
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions.
AAAI
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
2021 J jnl
Private and polynomial time algorithms for learning Gaussians and beyond.
CoRR
Hassan Ashtiani, Christopher Liaw
2021 A* conf
Privately Learning Mixtures of Axis-Aligned Gaussians.
NeurIPS
Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
2021 J jnl
Privately Learning Mixtures of Axis-Aligned Gaussians.
CoRR
Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
2020 J jnl
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions.
CoRR
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
2020 A* conf
Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds.
NeurIPS
Nicholas J. A. Harvey, Christopher Liaw, Tasuku Soma
2020 J jnl
Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes.
J. ACM
Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2020 A* conf
Optimal anytime regret for two experts.
FOCS
Nicholas J. A. Harvey, Christopher Liaw, Edwin A. Perkins, Sikander Randhawa
2020 J jnl
Optimal anytime regret with two experts.
CoRR
Nicholas J. A. Harvey, Christopher Liaw, Edwin A. Perkins, Sikander Randhawa
2019 — conf
A new dog learns old tricks: RL finds classic optimization algorithms.
ICLR (Poster)
Weiwei Kong, Christopher Liaw, Aranyak Mehta, D. Sivakumar
2019 J jnl
Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks.
J. Mach. Learn. Res.
Peter L. Bartlett, Nick Harvey, Christopher Liaw, Abbas Mehrabian
2019 J jnl
Simple and optimal high-probability bounds for strongly-convex stochastic gradient descent.
CoRR
Nicholas J. A. Harvey, Christopher Liaw, Sikander Randhawa
2019 A* conf
The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue.
EC
Hu Fu, Christopher Liaw, Sikander Randhawa
2019 J jnl
The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue.
CoRR
Hu Fu, Christopher Liaw, Sikander Randhawa
2019 A* conf
Tight analyses for non-smooth stochastic gradient descent.
COLT
Nicholas J. A. Harvey, Christopher Liaw, Yaniv Plan, Sikander Randhawa
2018 — conf
Approximation Schemes for Covering and Packing in the Streaming Model.
CCCG
Christopher Liaw, Paul Liu, Robert Reiss
2018 B conf
Greedy and Local Ratio Algorithms in the MapReduce Model.
SPAA
Nicholas J. A. Harvey, Christopher Liaw, Paul Liu
2018 J jnl
Greedy and Local Ratio Algorithms in the MapReduce Model.
CoRR
Nicholas J. A. Harvey, Christopher Liaw, Paul Liu
2018 A* conf
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes.
NeurIPS
Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2018 A* conf
The Value of Information Concealment.
SODA
Hu Fu, Christopher Liaw, Pinyan Lu, Zhihao Gavin Tang
2018 J jnl
Tight Analyses for Non-Smooth Stochastic Gradient Descent.
CoRR
Nicholas J. A. Harvey, Christopher Liaw, Yaniv Plan, Sikander Randhawa
2017 J jnl
Approximation Schemes for Covering and Packing in the Streaming Model.
CoRR
Christopher Liaw, Paul Liu, Robert Reiss
2017 A* conf
Nearly-tight VC-dimension bounds for piecewise linear neural networks.
COLT
Nick Harvey, Christopher Liaw, Abbas Mehrabian
2017 J jnl
Nearly-tight VC-dimension bounds for piecewise linear neural networks.
CoRR
Nick Harvey, Christopher Liaw, Abbas Mehrabian
2017 J jnl
Rainbow Hamilton cycles and lopsidependency.
Discret. Math.
Nicholas J. A. Harvey, Christopher Liaw
2017 A conf
Tight Load Balancing Via Randomized Local Search.
IPDPS
Petra Berenbrink, Peter Kling, Christopher Liaw, Abbas Mehrabian
2017 J jnl
Tight Load Balancing via Randomized Local Search.
CoRR
Petra Berenbrink, Peter Kling, Christopher Liaw, Abbas Mehrabian
2016 J jnl
A simple tool for bounding the deviation of random matrices on geometric sets.
CoRR
Christopher Liaw, Abbas Mehrabian, Yaniv Plan, Roman Vershynin