@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}}, author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi}, journal = {ArXiv e-prints}, year = 2024, month = jul, volume = {abs/2407.xxxx}, note = {to appear} } % %

@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}}, author = {{Allen-Zhu}, Zeyuan and Li, Yuanzhi}, journal = {ArXiv e-prints}, year = 2024, month = jul, volume = {abs/2407.xxxx}, note = {to appear} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}, } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}} } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % %

@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}, } % % % % % % % %