Yuanzhi Li
Orcid: 0009-0004-4418-9308
According to our database1,
Yuanzhi Li
authored at least 129 papers
between 2007 and 2024.
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Bibliography
2024
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs.
CoRR, 2024
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Can We Trust the Phone Vendors? Comprehensive Security Measurements on the Android Firmware Ecosystem.
IEEE Trans. Software Eng., July, 2023
Detection of Gas Pipeline Leakage Using Distributed Optical Fiber Sensors: Multi-Physics Analysis of Leakage-Fiber Coupling Mechanism in Soil Environment.
Sensors, 2023
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Backward Feature Correction: How Deep Learning Performs Deep (Hierarchical) Learning.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
2021
Near-optimal discrete optimization for experimental design: a regret minimization approach.
Math. Program., 2021
On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimization.
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
PET: Optimizing Tensor Programs with Partially Equivalent Transformations and Automated Corrections.
Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021
Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021
Proceedings of the Conference on Learning Theory, 2021
2020
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020
Proceedings of the Conference on Learning Theory, 2020
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without.
Proceedings of the Conference on Learning Theory, 2020
2019
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees.
Proceedings of the 7th International Conference on Learning Representations, 2019
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives.
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
Trans. Assoc. Comput. Linguistics, 2018
Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees.
CoRR, 2018
An homotopy method for l<sub>p</sub> regression provably beyond self-concordance and in input-sparsity time.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Operator scaling via geodesically convex optimization, invariant theory and polynomial identity testing.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
A Nearly Instance Optimal Algorithm for Top-<i>k</i> Ranking under the Multinomial Logit Model.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations.
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Algorithmic Learning Theory, 2018
2017
Manag. Sci., 2017
Follow the Compressed Leader: Faster Algorithms for Matrix Multiplicative Weight Updates.
CoRR, 2017
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model.
CoRR, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations.
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU.
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017
First Efficient Convergence for Streaming k-PCA: A Global, Gap-Free, and Near-Optimal Rate.
Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017
2016
Trans. Assoc. Comput. Linguistics, 2016
Faster Principal Component Regression via Optimal Polynomial Approximation to sgn(x).
CoRR, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings.
CoRR, 2015
2014
Proceedings of the 11th IEEE International Conference on e-Business Engineering, 2014
2013
Proceedings of the COLT 2013, 2013
2007
An Empirical Research of Factors Influencing the Decision-Making of Chinese Online Shoppers.
Proceedings of the Integration and Innovation Orient to E-Society, 2007