To divide and conquer search ranking by learning query difficulty. - Zeyuan Allen Zhu; Weizhu Chen; Tao Wan; Chenguang Zhu; Gang Wang 010; Zheng Chen 001 (CIKM, 2009)

A general magnitude-preserving boosting algorithm for search ranking. - Chenguang Zhu; Weizhu Chen; Zeyuan Allen Zhu; Gang Wang 010; Dong Wang 022; Zheng Chen 001 (CIKM, 2009)

P-packSVM: Parallel Primal grAdient desCent Kernel SVM. - Zeyuan Allen Zhu; Weizhu Chen; Gang Wang 010; Chenguang Zhu; Zheng Chen 001 (ICDM, 2009)

Inverse Time Dependency in Convex Regularized Learning. - Zeyuan Allen Zhu; Weizhu Chen; Chenguang Zhu; Gang Wang 010; Haixun Wang; Zheng Chen 001 (ICDM, 2009)

Asymptotically optimal strategy-proof mechanisms for two-facility games. - Pinyan Lu; Xiaorui Sun; Yajun Wang 001; Zeyuan Allen Zhu (EC, 2010)

A novel click model and its applications to online advertising. - Zeyuan Allen Zhu; Weizhu Chen; Tom Minka; Chenguang Zhu; Zheng Chen 001 (WSDM, 2010)

Pricing in Social Networks: Equilibrium and Revenue Maximization - Wei Chen 013; Pinyan Lu; Xiaorui Sun; Yajun Wang 001; Zeyuan Allen Zhu (CoRR, 2010)

Survey & Experiment: Towards the Learning Accuracy - Zeyuan Allen Zhu (CoRR, 2010)

Optimal Pricing in Social Networks with Incomplete Information. - Wei Chen 013; Pinyan Lu; Xiaorui Sun; Bo Tang 003; Yajun Wang 001; Zeyuan Allen Zhu (WINE, 2011)

Knightian Auctions - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2011)

Mechanism design with approximate valuations. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (ITCS, 2012)

Randomized accuracy-aware program transformations for efficient approximate computations. - Zeyuan Allen Zhu; Sasa Misailovic; Jonathan A. Kelner; Martin C. Rinard (POPL, 2012)

A Local Algorithm for Finding Well-Connected Clusters. - Zeyuan Allen Zhu; Silvio Lattanzi; Vahab S. Mirrokni (ICML (3), 2013)

A simple, combinatorial algorithm for solving SDD systems in nearly-linear time. - Jonathan A. Kelner; Lorenzo Orecchia; Aaron Sidford; Zeyuan Allen Zhu (STOC, 2013)

Knightian self uncertainty in the vcg mechanism for unrestricted combinatorial auctions. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (EC, 2014)

Flow-Based Algorithms for Local Graph Clustering. - Lorenzo Orecchia; Zeyuan Allen Zhu (SODA, 2014)

Bridging Utility Maximization and Regret Minimization. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2014)

Knightian Robustness from Regret Minimization. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2014)

Knightian Analysis of the VCG Mechanism in Unrestricted Combinatorial Auctions. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2014)

Knightian Robustness of Single-Parameter Domains. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2014)

Knightian Robustness of the Vickrey Mechanism. - Alessandro Chiesa; Silvio Micali; Zeyuan Allen Zhu (CoRR, 2014)

Johnson-Lindenstrauss Compression with Neuroscience-Based Constraints. - Zeyuan Allen Zhu; Rati Gelashvili; Silvio Micali; Nir Shavit (CoRR, 2014)

Using Optimization to Find Maximum Inscribed Balls and Minimum Enclosing Balls. - Zeyuan Allen Zhu; Zhenyu Liao; Lorenzo Orecchia (CoRR, 2014)

A Novel, Simple Interpretation of Nesterov's Accelerated Method as a Combination of Gradient and Mirror Descent. - Zeyuan Allen Zhu; Lorenzo Orecchia (CoRR, 2014)

Nearly-Linear Time Packing and Covering LP Solver with Faster Convergence Rate Than $O(1/ varepsilon^2)$. - Zeyuan Allen Zhu; Lorenzo Orecchia (CoRR, 2014)

Using Optimization to Break the Epsilon Barrier: A Faster and Simpler Width-Independent Algorithm for Solving Positive Linear Programs in Parallel. - Zeyuan Allen Zhu; Lorenzo Orecchia (SODA, 2015)

Spectral Sparsification and Regret Minimization Beyond Matrix Multiplicative Updates. - Zeyuan Allen Zhu; Zhenyu Liao; Lorenzo Orecchia (STOC, 2015)

Nearly-Linear Time Positive LP Solver with Faster Convergence Rate. - Zeyuan Allen Zhu; Lorenzo Orecchia (STOC, 2015)

UniVR: A Universal Variance Reduction Framework for Proximal Stochastic Gradient Method. - Zeyuan Allen Zhu; Yang Yuan (CoRR, 2015)

Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling. - Zeyuan Allen Zhu; Yang Yuan (CoRR, 2015)

Shorter arithmetization of nondeterministic computations. - Alessandro Chiesa; Zeyuan Allen Zhu (Theor. Comput. Sci., 2015)

Optimization Algorithms for Faster Computational Geometry. - Zeyuan Allen Zhu; Zhenyu Liao; Yang Yuan (ICALP, 2016)

Variance Reduction for Faster Non-Convex Optimization. - Zeyuan Allen Zhu; Elad Hazan (ICML, 2016)

Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling. - Zeyuan Allen Zhu; Zheng Qu 001; Peter Richtárik; Yang Yuan (ICML, 2016)

Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives. - Zeyuan Allen Zhu; Yang Yuan (ICML, 2016)

Optimal Black-Box Reductions Between Optimization Objectives. - Zeyuan Allen Zhu; Elad Hazan (NIPS, 2016)

Even Faster SVD Decomposition Yet Without Agonizing Pain. - Zeyuan Allen Zhu; Yuanzhi Li (NIPS, 2016)

Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters. - Zeyuan Allen Zhu; Yang Yuan; Karthik Sridharan (NIPS, 2016)

Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver. - Zeyuan Allen Zhu; Yin Tat Lee; Lorenzo Orecchia (SODA, 2016)

Expanders via Local Edge Flips. - Zeyuan Allen Zhu; Aditya Bhaskara; Silvio Lattanzi; Vahab S. Mirrokni; Lorenzo Orecchia (SODA, 2016)

Finding Approximate Local Minima for Nonconvex Optimization in Linear Time. - Naman Agarwal; Zeyuan Allen Zhu; Brian Bullins; Elad Hazan; Tengyu Ma 001 (CoRR, 2016)

Katyusha: Accelerated Variance Reduction for Faster SGD. - Zeyuan Allen Zhu (CoRR, 2016)

Fast Global Convergence of Online PCA. - Zeyuan Allen Zhu; Yuanzhi Li (CoRR, 2016)

Faster Principal Component Regression via Optimal Polynomial Approximation to sgn(x). - Zeyuan Allen Zhu; Yuanzhi Li (CoRR, 2016)

Reconstructing Markov processes from independent and anonymous experiments. - Silvio Micali; Zeyuan Allen Zhu (Discret. Appl. Math., 2016)

Restricted Isometry Property for General p-Norms. - Zeyuan Allen Zhu; Rati Gelashvili; Ilya P. Razenshteyn (IEEE Trans. Inf. Theory, 2016)

First Efficient Convergence for Streaming k-PCA: A Global, Gap-Free, and Near-Optimal Rate. - Zeyuan Allen-Zhu; Yuanzhi Li (FOCS, 2017)

Much Faster Algorithms for Matrix Scaling. - Zeyuan Allen-Zhu; Yuanzhi Li; Rafael Mendes de Oliveira; Avi Wigderson (FOCS, 2017)

Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter. - Zeyuan Allen-Zhu (ICML, 2017)

Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition. - Zeyuan Allen-Zhu; Yuanzhi Li (ICML, 2017)

Faster Principal Component Regression and Stable Matrix Chebyshev Approximation. - Zeyuan Allen-Zhu; Yuanzhi Li (ICML, 2017)

Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU. - Zeyuan Allen-Zhu; Yuanzhi Li (ICML, 2017)

Near-Optimal Design of Experiments via Regret Minimization. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (ICML, 2017)

Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent. - Zeyuan Allen Zhu; Lorenzo Orecchia (ITCS, 2017)

Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. - Zeyuan Allen-Zhu; Elad Hazan; Wei Hu 014; Yuanzhi Li (NIPS, 2017)

Finding approximate local minima faster than gradient descent. - Naman Agarwal; Zeyuan Allen Zhu; Brian Bullins; Elad Hazan; Tengyu Ma 001 (STOC, 2017)

Follow the Compressed Leader: Faster Algorithms for Matrix Multiplicative Weight Updates. - Zeyuan Allen Zhu; Yuanzhi Li (CoRR, 2017)

Katyusha: The First Direct Acceleration of Stochastic Gradient Methods. - Zeyuan Allen-Zhu (J. Mach. Learn. Res., 2017)

Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization. - Zeyuan Allen-Zhu (ICML, 2018)

Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. - Zeyuan Allen-Zhu; Sébastien Bubeck; Yuanzhi Li (ICML, 2018)

Byzantine Stochastic Gradient Descent. - Dan Alistarh; Zeyuan Allen-Zhu; Jerry Li 001 (NeurIPS, 2018)

How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD. - Zeyuan Allen-Zhu (NeurIPS, 2018)

Natasha 2: Faster Non-Convex Optimization Than SGD. - Zeyuan Allen-Zhu (NeurIPS, 2018)

NEON2: Finding Local Minima via First-Order Oracles. - Zeyuan Allen-Zhu; Yuanzhi Li (NeurIPS, 2018)

The Lingering of Gradients: How to Reuse Gradients Over Time. - Zeyuan Allen-Zhu; David Simchi-Levi; Xinshang Wang (NeurIPS, 2018)

Is Q-Learning Provably Efficient? - Chi Jin 001; Zeyuan Allen-Zhu; Sébastien Bubeck; Michael I. Jordan (NeurIPS, 2018)

Operator scaling via geodesically convex optimization, invariant theory and polynomial identity testing. - Zeyuan Allen-Zhu; Ankit Garg; Yuanzhi Li; Rafael Mendes de Oliveira; Avi Wigderson (STOC, 2018)

How To Make the Gradients Small Stochastically. - Zeyuan Allen-Zhu (CoRR, 2018)

A Convergence Theory for Deep Learning via Over-Parameterization. - Zeyuan Allen-Zhu; Yuanzhi Li; Zhao Song 002 (ICML, 2019)

What Can ResNet Learn Efficiently, Going Beyond Kernels? - Zeyuan Allen-Zhu; Yuanzhi Li (NeurIPS, 2019)

Can SGD Learn Recurrent Neural Networks with Provable Generalization? - Zeyuan Allen-Zhu; Yuanzhi Li (NeurIPS, 2019)

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers. - Zeyuan Allen-Zhu; Yuanzhi Li; Yingyu Liang (NeurIPS, 2019)

On the Convergence Rate of Training Recurrent Neural Networks. - Zeyuan Allen-Zhu; Yuanzhi Li; Zhao Song 002 (NeurIPS, 2019)

Nearly linear-time packing and covering LP solvers - Achieving width-independence and -convergence. - Zeyuan Allen-Zhu; Lorenzo Orecchia (Math. Program., 2019)

Backward Feature Correction: How Deep Learning Performs Deep Learning. - Zeyuan Allen-Zhu; Yuanzhi Li (CoRR, 2020)

Feature Purification: How Adversarial Training Performs Robust Deep Learning. - Zeyuan Allen-Zhu; Yuanzhi Li (FOCS, 2021)

Byzantine-Resilient Non-Convex Stochastic Gradient Descent. - Zeyuan Allen-Zhu; Faeze Ebrahimianghazani; Jerry Li 001; Dan Alistarh (ICLR, 2021)

LoRA: Low-Rank Adaptation of Large Language Models. - Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Weizhu Chen (CoRR, 2021)

Near-optimal discrete optimization for experimental design: a regret minimization approach. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (Math. Program., 2021)

LoRA: Low-Rank Adaptation of Large Language Models. - Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Lu Wang; Weizhu Chen (ICLR, 2022)

Backward Feature Correction: How Deep Learning Performs Deep (Hierarchical) Learning. - Zeyuan Allen-Zhu; Yuanzhi Li (COLT, 2023)

Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning. - Zeyuan Allen-Zhu; Yuanzhi Li (ICLR, 2023)

Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions. - Zeyuan Allen-Zhu; Yuanzhi Li (ICLR, 2023)

SALSA VERDE: a machine learning attack on LWE with sparse small secrets. - Cathy Yuanchen Li; Emily Wenger; Zeyuan Allen-Zhu; François Charton; Kristin E. Lauter (NeurIPS, 2023)

Physics of Language Models: Part 1, Context-Free Grammar. - Zeyuan Allen-Zhu; Yuanzhi Li (CoRR, 2023)

SALSA VERDE: a machine learning attack on Learning with Errors with sparse small secrets. - Cathy Yuanchen Li; Jana Sotáková; Emily Wenger; Zeyuan Allen-Zhu; François Charton; Kristin E. Lauter (IACR Cryptol. ePrint Arch., 2023)

Physics of Language Models: Part 3.1, Knowledge Storage and Extraction. - Zeyuan Allen-Zhu; Yuanzhi Li (ICML, 2024)

Reverse Training to Nurse the Reversal Curse. - Olga Golovneva; Zeyuan Allen-Zhu; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems. - Tian Ye 011; Zicheng Xu; Yuanzhi Li; Zeyuan Allen-Zhu (ICLR, 2025)

Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process. - Tian Ye 011; Zicheng Xu; Yuanzhi Li; Zeyuan Allen-Zhu (ICLR, 2025)

Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws. - Zeyuan Allen-Zhu; Yuanzhi Li (ICLR, 2025)

Physics of Language Models: Part 3.2, Knowledge Manipulation. - Zeyuan Allen-Zhu; Yuanzhi Li (ICLR, 2025)