@article{YXLA2024-gsm1,
author = {Ye, Tian and Xu, Zicheng and Li, Yuanzhi and {Allen-Zhu}, Zeyuan},
title = {{Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process}},
journal = {ArXiv e-prints},
year = 2024,
month = jul,
volume = {abs/2407.20311},
note = {Full version available at \url{http://arxiv.org/abs/2407.20311}}
}
%
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@article{YXLA2024-gsm2,
author = {Ye, Tian and Xu, Zicheng and Li, Yuanzhi and {Allen-Zhu}, Zeyuan},
title = {{Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems}},
journal = {ArXiv e-prints},
year = 2024,
month = aug,
volume = {abs/2408.16293},
note = {Full version available at \url{http://arxiv.org/abs/2408.16293}}
}
%
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@article{AL2024-knowledge3,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws}},
journal = {ArXiv e-prints},
year = 2024,
month = apr,
volume = {abs/2404.05405},
note = {Full version available at \url{http://arxiv.org/abs/2404.05405}}
}
%
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@article{GAWS2024,
title={{Reverse Training to Nurse the Reversal Curse}},
author={Golovneva, Olga and {Allen-Zhu}, Zeyuan and Weston, Jason and Sukhbaatar, Sainbayar},
journal = {ArXiv e-prints},
year = 2024,
month = mar,
volume = {abs/2403.13799},
note = {Full version available at \url{http://arxiv.org/abs/2403.13799}}
}
%
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@article{AL2023-knowledge2,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Physics of Language Models: Part 3.2, Knowledge Manipulation}},
journal = {ArXiv e-prints},
year = 2023,
month = sep,
volume = {abs/2309.14402},
note = {Full version available at \url{http://arxiv.org/abs/2309.14402}}
}
%
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@article{AL2023-knowledge1,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Physics of Language Models: Part 3.1, Knowledge Storage and Extraction}},
journal = {ArXiv e-prints},
year = 2023,
month = sep,
volume = {abs/2309.14316},
note = {Full version available at \url{http://arxiv.org/abs/2309.14316}}
}
%
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@article{AL2023-cfg,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Physics of Language Models: Part 1, Learning Hierarchical Language Structures}},
journal = {ArXiv e-prints},
year = 2023,
month = may,
volume = {abs/2305.13673},
note = {Full version available at \url{http://arxiv.org/abs/2305.13673}}
}
%
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@inproceedings{LWACL2023,
author={Li, Cathy and Sotakova, Jana and Wenger, Emily and {Allen-Zhu}, Zeyuan and Charton, Francois and Lauter, Kristin},
title = {{SALSA VERDE: a machine learning attack on LWE with sparse small secrets}},
booktitle = {Proceedings of the 37rd Conference on Neural Information Processing Systems},
series = {NeurIPS~'23},
year = {2023},
}
%
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@inproceedings{AL2023-densenet,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Backward Feature Correction: How Deep Learning Performs Deep Learning}},
booktitle = {Conference on Learning Theory},
series = {COLT~'23},
year = 2023,
note = {Full version available at \url{http://arxiv.org/abs/2001.04413}}
}
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@inproceedings{AL2023-gan,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions}},
booktitle = {International Conference on Learning Representations},
series = {ICLR~'23},
year = 2023,
note = {Full version available at \url{http://arxiv.org/abs/2106.02619}}
}
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@inproceedings{AL2023-ensemble,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning}},
booktitle = {International Conference on Learning Representations},
series = {ICLR~'23},
year = 2023,
note = {Full version available at \url{http://arxiv.org/abs/2012.09816}}
}
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@inproceedings{HuShenWallis2022-lora,
author={Hu, Edward J and Shen, Yelong and Wallis, Phillip and {Allen-Zhu}, Zeyuan and Li, Yuanzhi and Wang, Shean and Chen, Weizhu},
title = {{LoRA: Low-Rank Adaptation of Large Language Models}},
booktitle = {International Conference on Learning Representations},
series = {ICLR~'22},
year = 2022,
note = {Full version available at \url{http://arxiv.org/abs/2106.09685}}
}
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@inproceedings{AL2021-robust,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Feature Purification: How Adversarial Training Performs Robust Deep Learning}},
booktitle = {Symposium on Foundations of Computer Science},
series = {FOCS~'21},
year = 2021,
note = {Full version available at \url{http://arxiv.org/abs/2005.10190}}
}
%
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@inproceedings{AELA2021,
author = {{Allen-Zhu}, Zeyuan and Ebrahimianghazani, Faeze and Li, Jerry and Alistarh, Dan},
title = {{Byzantine-Resilient Non-Convex Stochastic Gradient Descent}},
booktitle = {International Conference on Learning Representations},
series = {ICLR~'21},
year = {2021},
note = {Full version available at \url{http://arxiv.org/abs/2012.14368}}
}
%
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@inproceedings{AL2019-resnet,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{What Can ResNet Learn Efficiently, Going Beyond Kernels?}},
booktitle = {Proceedings of the 33rd Conference on Neural Information Processing Systems},
series = {NeurIPS~'19},
year = {2019},
note = {Full version available at \url{http://arxiv.org/abs/1905.10337}}
}
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@inproceedings{AL2019-RNNgen,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Can SGD Learn Recurrent Neural Networks with Provable Generalization?}},
booktitle = {Proceedings of the 33rd Conference on Neural Information Processing Systems},
series = {NeurIPS~'19},
year = {2019},
note = {Full version available at \url{http://arxiv.org/abs/1902.01028}}
}
%
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@inproceedings{ALL2019-threelayer,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Liang, Yingyu},
title = {{Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers}},
booktitle = {Proceedings of the 33rd Conference on Neural Information Processing Systems},
series = {NeurIPS~'19},
year = {2019},
note = {Full version available at \url{http://arxiv.org/abs/1811.04918}}
}
%
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@inproceedings{ALS2018-dnn,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Song, Zhao},
title = {{A Convergence Theory for Deep Learning via Over-Parameterization}},
booktitle = {Proceedings of the 36th International Conference on Machine Learning},
series = {ICML~'19},
year = {2019},
note = {Full version available at \url{http://arxiv.org/abs/1811.03962}}
}
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@inproceedings{ALS2018-rnn,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Song, Zhao},
title = {{On the Convergence Rate of Training Recurrent Neural Networks}},
booktitle = {Proceedings of the 33rd Conference on Neural Information Processing Systems},
series = {NeurIPS~'19},
year = {2019},
note = {Full version available at \url{http://arxiv.org/abs/1810.12065}}
}
%
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@article{ALSW2017-experiment2,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Singh, Aarti and Wang, Yining},
title = {{Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach}},
journal= {Mathematical Programming},
year = 2020,
month = jan,
note = {Full version available at \url{http://arxiv.org/abs/1711.05174}}
}
%
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@inproceedings{ASW2018,
author = {{Allen-Zhu}, Zeyuan and {Simchi-Levi}, David and Wang, Xinshang},
title = {{The Lingering of Gradients: How to Reuse Gradients over Time}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NeurIPS~'18},
year = {2018},
note = {Full version available at \url{https://arxiv.org/abs/1901.02871}}
}
%
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@inproceedings{JABJ2018,
author = {Jin, Chi and {Allen-Zhu}, Zeyuan and Bubeck, S{\'e}bastien and Jordan, Michael I.},
title = {{Is Q-Learning Provably Efficient?}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NeurIPS~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1807.03765}}
}
%
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@inproceedings{AAL2018,
author = {Alistarh, Dan and {Allen-Zhu}, Zeyuan and Li, Jerry},
title = {{Byzantine Stochastic Gradient Descent}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NeurIPS~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1803.08917}}
}
%
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@inproceedings{AllenZhu2018-sgd3,
author = {{Allen-Zhu}, Zeyuan},
title = {{How To Make the Gradients Small Stochastically}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NeurIPS~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1801.02982}}
}
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@inproceedings{AllenLi2017-neon2,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Neon2: Finding Local Minima via First-Order Oracles}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NeurIPS~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1711.06673}}
}
%
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@inproceedings{AllenZhu2017-natasha2,
author = {{Allen-Zhu}, Zeyuan},
title = {{Natasha 2: Faster Non-Convex Optimization Than SGD}},
booktitle = {Proceedings of the 32nd Conference on Neural Information Processing Systems},
series = {NIPS~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1708.08694}}
}
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@inproceedings{AllenZhu2018-KatyushaX,
author = {{Allen-Zhu}, Zeyuan},
title = {{Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization}},
booktitle = {Proceedings of the 35th International Conference on Machine Learning},
series = {ICML~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1802.03866}}
}
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@inproceedings{ABL2018,
author = {{Allen-Zhu}, Zeyuan and Bubeck, S{\'e}bastien and Li, Yuanzhi},
title = {{Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits}},
booktitle = {Proceedings of the 35th International Conference on Machine Learning},
series = {ICML~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1802.03386}}
}
%
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@inproceedings{AGLOW2018,
author = {{Allen-Zhu}, Zeyuan and Garg, Ankit and Li, Yuanzhi and Oliveira, Rafael and Wigderson, Avi},
title = {{Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing}},
booktitle = {Proceedings of the 50th Annual ACM on Symposium on Theory of Computing},
series = {STOC~'18},
year = {2018},
note = {Full version available at \url{http://arxiv.org/abs/1804.01076}}
}
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@inproceedings{AHHL2017-fw,
author = {{Allen-Zhu}, Zeyuan and Hazan, Elad and Hu, Wei and Li, Yuanzhi},
title = {{Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls}},
booktitle = {Proceedings of the 31st Conference on Neural Information Processing Systems},
series = {NIPS~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1708.02105}}
}
%
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@inproceedings{ALOW2017,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Oliveira, Rafael and Wigderson, Avi},
title = {{Much Faster Algorithms for Matrix Scaling}},
booktitle = {Proceedings of the 58th Symposium on Foundations of Computer Science},
series = {FOCS~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1704.02315}}
}
%
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@inproceedings{ALSW2017-experiment,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi and Singh, Aarti and Wang, Yining},
title = {{Near-Optimal Design of Experiments via Regret Minimization}},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
series = {ICML~'17},
year = {2017},
note = {This paper is superceded by \url{http://arxiv.org/abs/1711.05174}}
}
%
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@inproceedings{Allenzhu2017-natasha,
author = {{Allen-Zhu}, Zeyuan},
title = {{Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter}},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
series = {ICML~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1702.00763}}
}
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@inproceedings{AllenLi2017-FTCL,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU}},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
series = {ICML~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1701.01722}}
}
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@inproceedings{AllenLi2017-PCR,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Faster Principal Component Regression and Stable Matrix Chebyshev Approximation}},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
series = {ICML~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1608.04773}}
}
%
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@inproceedings{AllenLi2017-streampca,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{First Efficient Convergence for Streaming k-PCA: a Global, Gap-Free, and Near-Optimal Rate}},
booktitle = {Proceedings of the 58th Symposium on Foundations of Computer Science},
series = {FOCS~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1607.07837}}
}
%
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@inproceedings{AllenLi2017-CCA,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition}},
booktitle = {Proceedings of the 34th International Conference on Machine Learning},
series = {ICML~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1607.06017}}
}
%
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@inproceedings{Allenzhu2017-katyusha,
author = {{Allen-Zhu}, Zeyuan},
title = {{Katyusha: The First Direct Acceleration of Stochastic Gradient Methods}},
booktitle = {STOC},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1603.05953}}
}
%
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@inproceedings{AABHM2017,
author = {Agarwal, Naman and {Allen-Zhu}, Zeyuan and Bullins, Brian and Hazan, Elad and Ma, Tengyu},
title = {{Finding Approximate Local Minima Faster Than Gradient Descent}},
booktitle = {STOC},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1611.01146}}
}
%
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@inproceedings{AllenOrecchia2017,
author = {{Allen-Zhu}, Zeyuan and Orecchia, Lorenzo},
title = {{Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent}},
booktitle = {Proceedings of the 8th Innovations in Theoretical Computer Science},
series = {ITCS~'17},
year = {2017},
note = {Full version available at \url{http://arxiv.org/abs/1407.1537}}
}
%
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@inproceedings{AllenHazan2016-reduction,
author = {{Allen-Zhu}, Zeyuan and Hazan, Elad},
title = {{Optimal Black-Box Reductions Between Optimization Objectives}},
booktitle = {Proceedings of the 30th Conference on Neural Information Processing Systems},
series = {NIPS~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1603.05642}}
}
%
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@inproceedings{AYS2016,
author = {{Allen-Zhu}, Zeyuan and Yuan, Yang and Sridharan, Karthik},
title = {{Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters}},
booktitle = {Proceedings of the 30th Conference on Neural Information Processing Systems},
series = {NIPS~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1602.02151}}
}
%
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@inproceedings{AllenLi2016-kSVD,
author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi},
title = {{LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain}},
booktitle = {Proceedings of the 30th Conference on Neural Information Processing Systems},
series = {NIPS~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1607.03463}}
}
%
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@inproceedings{AllenHazan2016-nonconvex,
author = {{Allen-Zhu}, Zeyuan and Hazan, Elad},
title = {{Variance Reduction for Faster Non-Convex Optimization}},
booktitle = {Proceedings of the 33rd International Conference on Machine Learning},
series = {ICML~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1603.05643}}
}
%
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@inproceedings{AllenYang2016,
author = {{Allen-Zhu}, Zeyuan and Yuan, Yang},
title = {{Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives}},
booktitle = {Proceedings of the 33rd International Conference on Machine Learning},
series = {ICML~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1506.01972}}
}
%
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@inproceedings{ARQY2016,
author = {{Allen-Zhu}, Zeyuan and Richt\'arik, Peter and Qu, Zheng and Yuan, Yang},
title = {{Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling}},
booktitle = {Proceedings of the 33rd International Conference on Machine Learning},
series = {ICML~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1512.09103}}
}
%
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@inproceedings{ALY2016,
author = {{Allen-Zhu}, Zeyuan and Liao, Zhenyu and Yuan, Yang},
title = {{Optimization Algorithms for Faster Computational Geometry}},
booktitle = {Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming},
series = {ICALP~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1412.1001}}
}
%
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@inproceedings{ABLMO2016,
author = {{Allen-Zhu}, Zeyuan and Bhaskara, Aditya and Lattanzi, Silvio and Mirrokni, Vahab and Orecchia, Lorenzo},
title = {Expanders via Local Edge Flips},
booktitle = {Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms},
series = {SODA~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1510.07768}}
}
%
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@inproceedings{ALO2016,
author = {{Allen-Zhu}, Zeyuan and Lee, Yin Tat and Orecchia, Lorenzo},
title = {Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver},
booktitle = {Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms},
series = {SODA~'16},
year = {2016},
note = {Full version available at \url{http://arxiv.org/abs/1507.02259}}
}
%
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@inproceedings{AllenOrecchia2015-sequential,
author = {{Allen-Zhu}, Zeyuan and Orecchia, Lorenzo},
title = {Nearly-Linear Time Positive LP Solver with Faster Convergence Rate},
booktitle = {Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing},
series = {STOC~'15},
year = {2015},
pages = {229--236},
note = {Newer version available at \url{http://arxiv.org/abs/1411.1124}}
}
%
%
@inproceedings{ALO2015,
author = {{Allen-Zhu}, Zeyuan and Liao, Zhenyu and Orecchia, Lorenzo},
title = {Spectral Sparsification and Regret Minimization Beyond Matrix Multiplicative Updates},
booktitle = {Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing},
series = {STOC~'15},
year = {2015},
pages = {237--245},
note = {Newer version available at \url{http://arxiv.org/abs/1506.04838}}
}
%
%
@inproceedings{AGR2015,
author = {{Allen-Zhu}, Zeyuan and Gelashvili, Rati and Razenshteyn, Ilya},
title = {{Restricted Isometry Property for General p-Norms}},
booktitle = {Proceedings of the 31st International Symposium on Computational Geometry},
pages = {451--460},
series = {SoCG~'15},
year = {2015},
note = {Full version available at \url{http://arxiv.org/abs/1407.2178}}
}
%
%
@inproceedings{AllenOrecchia2015-parallel,
author = {{Allen-Zhu}, Zeyuan and Orecchia, Lorenzo},
title = {Using Optimization to Break the Epsilon Barrier: A Faster and Simpler Width-independent Algorithm for Solving Positive Linear Programs in Parallel},
booktitle = {Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms},
series = {SODA '15},
year = {2015},
pages = {1439--1456},
nonte = {Full version with title ``Using Optimization to Solve Positive LPs Faster in Parallel'' available at \url{http://arxiv.org/abs/1407.1925}}
}
%
%
@article{CMZ2015,
author = {Chiesa, Alessandro and Micali, Silvio and Zhu, Zeyuan Allen},
title = {Knightian Analysis of the Vickrey Mechanism},
journal = {Econometrica},
volume = {83},
number = {5},
publisher = {Blackwell Publishing Ltd},
pages = {1727--1754},
year = {2015},
note = {Full version available at \url{http://arxiv.org/abs/1403.6413}}
}
%
%
@article{ChiesaZhu2015,
title = {Shorter arithmetization of nondeterministic computations},
author = {Alessandro Chiesa and Zeyuan Allen Zhu},
journal = {Theoretical Computer Science},
volume = {600},
pages = {107--131},
year = {2015},
}
%
%
@article{AllenOrecchia2014,
author = {{Allen-Zhu}, Zeyuan and Orecchia, Lorenzo},
journal = {ArXiv e-prints},
month = jul,
title = {Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent},
volume = {abs/1407.1537},
year = {2014}
}
%
%
@article{AGMS2014,
author = {{Allen-Zhu}, Zeyuan and Gelashvili, Rati and Micali, Silvio and Shavit, Nir},
title = {Sparse sign-consistent Johnson�CLindenstrauss matrices: Compression with neuroscience-based constraints},
volume = {111},
number = {47},
pages = {16872-16876},
year = {2014},
journal = {Proceedings of the National Academy of Sciences},
note = {Full version available at \url{http://arxiv.org/abs/1411.5383}}
}
%
%
@article{MicaliZhu2014,
author = {Micali, Silvio and Zhu, Zeyuan Allen},
title = {Reconstructing Markov processes from independent and anonymous experiments},
journal = {Discrete Applied Mathematics},
volume = {200},
pages = {108--122},
year = {2016},
}
%
%
@inproceedings{CMZ2014,
author = {Chiesa, Alessandro and Micali, Silvio and Zhu, Zeyuan Allen},
title = {Knightian Self Uncertainty in the Vcg Mechanism for Unrestricted Combinatorial Auctions},
booktitle = {Proceedings of the Fifteenth ACM Conference on Economics and Computation},
series = {EC~'14},
year = {2014},
pages = {619--620},
}
%
%
@inproceedings{OrecchiaZhu2014,
author = {Orecchia, Lorenzo and Zhu, Zeyuan Allen},
title = {Flow-based Algorithms for Local Graph Clustering},
booktitle = {Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms},
series = {SODA~'14},
year = {2014},
pages = {1267--1286},
}
%
%
@inproceedings{ZLM2013,
title={A local algorithm for finding well-connected clusters},
author={Zhu, Zeyuan Allen and Lattanzi, Silvio and Mirrokni, Vahab},
booktitle={Proceedings of the 30th International Conference on Machine Learning},
series = {ICML~'13},
pages={396--404},
year={2013},
note={Full version with title ``Local Graph Clustering Beyond Cheeger's Inequality'' available at \url{http://arxiv.org/abs/1304.8132}}
}
%
%
@inproceedings{KOSZ2013,
author = {Kelner, Jonathan A. and Orecchia, Lorenzo and Sidford, Aaron and Zhu, Zeyuan Allen},
title = {A Simple, Combinatorial Algorithm for Solving SDD Systems in Nearly-linear Time},
booktitle = {Proceedings of the Forty-fifth Annual ACM Symposium on Theory of Computing},
series = {STOC~'13},
year = {2013},
pages = {911--920},
}
%
%
@inproceedings{CMZ2012,
author = {Chiesa, Alessandro and Micali, Silvio and Zhu, Zeyuan Allen},
title = {Mechanism Design with Approximate Valuations},
booktitle = {Proceedings of the 3rd Innovations in Theoretical Computer Science Conference},
series = {ITCS~'12},
year = {2012},
pages = {34--38},
}
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@inproceedings{ZMKR2012,
author = {Zhu, Zeyuan Allen and Misailovic, Sasa and Kelner, Jonathan A. and Rinard, Martin},
title = {Randomized Accuracy-aware Program Transformations for Efficient Approximate Computations},
booktitle = {Proceedings of the 39th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages},
series = {POPL~'12},
year = {2012},
pages = {441--454},
}
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@inproceedings{Chen2011-pricing,
author = {Chen, Wei and Lu, Pinyan and Sun, Xiaorui and Tang, Bo and Wang, Yajun and Zhu, Zeyuan Allen},
title = {Optimal Pricing in Social Networks with Incomplete Information},
booktitle = {Proceedings of the 7th International Conference on Internet and Network Economics},
series = {WINE~'11},
year = {2011},
pages = {49--60},
}
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@inproceedings{Lu2010-facility,
author = {Lu, Pinyan and Sun, Xiaorui and Wang, Yajun and Zhu, Zeyuan Allen},
title = {Asymptotically Optimal Strategy-proof Mechanisms for Two-facility Games},
booktitle = {Proceedings of the 11th ACM Conference on Electronic Commerce},
series = {EC~'10},
year = {2010},
pages = {315--324},
}
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@inproceedings{Zhu2010-GCM,
author = {Zhu, Zeyuan Allen and Chen, Weizhu and Minka, Tom and Zhu, Chenguang and Chen, Zheng},
title = {A Novel Click Model and Its Applications to Online Advertising},
booktitle = {Proceedings of the Third ACM International Conference on Web Search and Data Mining},
series = {WSDM~'10},
year = {2010},
pages = {321--330},
}
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@inproceedings{Zhu2009-Inverse,
author = {Zhu, Zeyuan Allen and Chen, Weizhu and Zhu, Chenguang and Wang, Gang and Wang, Haixun and Chen, Zheng},
title = {Inverse Time Dependency in Convex Regularized Learning},
booktitle = {Proceedings of the 2009 Ninth IEEE International Conference on Data Mining},
series = {ICDM~'09},
year = {2009},
pages = {667--676},
}
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@inproceedings{Zhu2009-Ppack,
author = {Zhu, Zeyuan Allen and Chen, Weizhu and Wang, Gang and Zhu, Chenguang and Chen, Zheng},
title = {P-packSVM: Parallel Primal grAdient desCent Kernel SVM},
booktitle = {Proceedings of the 2009 Ninth IEEE International Conference on Data Mining},
series = {ICDM~'09},
year = {2009},
pages = {677--686},
}
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@inproceedings{Zhu2009-DandQ,
author = {Zhu, Zeyuan Allen and Chen, Weizhu and Wan, Tao and Zhu, Chenguang and Wang, Gang and Chen, Zheng},
title = {To Divide and Conquer Search Ranking by Learning Query Difficulty},
booktitle = {Proceedings of the 18th ACM Conference on Information and Knowledge Management},
series = {CIKM~'09},
year = {2009},
pages = {1883--1886},
}
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@inproceedings{Zhu2009-MPBoost,
author = {Zhu, Chenguang and Chen, Weizhu and Zhu, Zeyuan Allen and Wang, Gang and Wang, Dong and Chen, Zheng},
title = {A General Magnitude-preserving Boosting Algorithm for Search Ranking},
booktitle = {Proceedings of the 18th ACM Conference on Information and Knowledge Management},
series = {CIKM~'09},
year = {2009},
pages = {817--826},
}
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