Tengyu Ma

According to our database, Tengyu Ma authored at least 132 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Formal Theorem Proving by Rewarding LLMs to Decompose Proofs Hierarchically.

Kefan Dong, Arvind V. Mahankali, Tengyu Ma

CoRR, 2024

Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape Perspective.

Kaiyue Wen, Zhiyuan Li, Jason Wang, David Hall, Percy Liang, Tengyu Ma

CoRR, 2024

Linguistic Calibration of Language Models.

Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto

CoRR, 2024

Chain of Thought Empowers Transformers to Solve Inherently Serial Problems.

Zhiyuan Li, Hong Liu, Denny Zhou, Tengyu Ma

CoRR, 2024

Linguistic Calibration of Long-Form Generations.

Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto

Proceedings of the Forty-first International Conference on Machine Learning, 2024

One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention.

Arvind V. Mahankali, Tatsunori Hashimoto, Tengyu Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training.

Hong Liu, Zhiyuan Li, David Leo Wright Hall, Percy Liang, Tengyu Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Large Language Models as Tool Makers.

Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Chain of Thought Empowers Transformers to Solve Inherently Serial Problems.

Zhiyuan Liu, Hong Liu, Denny Zhou, Tengyu Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time.

Arvind V. Mahankali, Jeff Z. HaoChen, Kefan Dong, Margalit Glasgow, Tengyu Ma

CoRR, 2023

The Inductive Bias of Flatness Regularization for Deep Matrix Factorization.

Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank J. Reddi, Tengyu Ma, Stefanie Jegelka

CoRR, 2023

Toward L_∞-recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields.

Kefan Dong, Tengyu Ma

CoRR, 2023

Larger language models do in-context learning differently.

Jerry W. Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, Tengyu Ma

CoRR, 2023

Data Selection for Language Models via Importance Resampling.

Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining.

Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization.

Kaiyue Wen, Zhiyuan Li, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time.

Arvind V. Mahankali, Haochen Zhang, Kefan Dong, Margalit Glasgow, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models.

Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models.

Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma

Proceedings of the International Conference on Machine Learning, 2023

How Sharpness-Aware Minimization Minimizes Sharpness?

Kaiyue Wen, Tengyu Ma, Zhiyuan Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A theoretical study of inductive biases in contrastive learning.

Jeff Z. HaoChen, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence.

Margalit Glasgow, Colin Wei, Mary Wootters, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Asymptotic Instance-Optimal Algorithms for Interactive Decision Making.

Kefan Dong, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

First Steps Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains.

Kefan Dong, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

What learning algorithm is in-context learning? Investigations with linear models.

Ekin Akyürek, Dale Schuurmans, Jacob Andreas, Tengyu Ma, Denny Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Symbol tuning improves in-context learning in language models.

Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Toward L_∞Recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields.

Kefan Dong, Tengyu Ma

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

On the optimization landscape of tensor decompositions.

Rong Ge, Tengyu Ma

Math. Program., 2022

How Does Sharpness-Aware Minimization Minimize Sharpness?

Kaiyue Wen, Tengyu Ma, Zhiyuan Li

CoRR, 2022

Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift.

Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers.

Colin Wei, Yining Chen, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations.

Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments.

Yining Chen, Elan Rosenfeld, Mark Sellke, Tengyu Ma, Andrej Risteski

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation.

Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang

Proceedings of the International Conference on Machine Learning, 2022

Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification.

Ling Pan, Longbo Huang, Tengyu Ma, Huazhe Xu

Proceedings of the International Conference on Machine Learning, 2022

Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path.

Haoyuan Cai, Tengyu Ma, Simon S. Du

Proceedings of the International Conference on Machine Learning, 2022

An Explanation of In-context Learning as Implicit Bayesian Inference.

Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma

Proceedings of the Tenth International Conference on Learning Representations, 2022

Self-supervised Learning is More Robust to Dataset Imbalance.

Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma

Proceedings of the Tenth International Conference on Learning Representations, 2022

Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, Percy Liang

Proceedings of the Tenth International Conference on Learning Representations, 2022

DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization.

Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine

Proceedings of the Tenth International Conference on Learning Representations, 2022

Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective.

Margalit R. Glasgow, Honglin Yuan, Tengyu Ma

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System.

Zichuan Lin, Jing Huang, Bowen Zhou, Xiaodong He, Tengyu Ma

CoRR, 2021

Why Do Local Methods Solve Nonconvex Problems?

Tengyu Ma

CoRR, 2021

Entity and Evidence Guided Document-Level Relation Extraction.

Kevin Huang, Peng Qi, Guangtao Wang, Tengyu Ma, Jing Huang

Proceedings of the 6th Workshop on Representation Learning for NLP, 2021

Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration.

Shengjia Zhao, Michael P. Kim, Roshni Sahoo, Tengyu Ma, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning.

Colin Wei, Sang Michael Xie, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Safe Reinforcement Learning by Imagining the Near Future.

Garrett Thomas, Yuping Luo, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations.

Yuping Luo, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss.

Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature.

Kefan Dong, Jiaqi Yang, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Label Noise SGD Provably Prefers Flat Global Minimizers.

Alex Damian, Tengyu Ma, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variance-reduced First-order Meta-learning for Natural Language Processing Tasks.

Lingxiao Wang, Kevin Huang, Tengyu Ma, Quanquan Gu, Jing Huang

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization.

Sang Michael Xie, Tengyu Ma, Percy Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness.

Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang

Proceedings of the 9th International Conference on Learning Representations, 2021

Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data.

Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

Optimal Regularization can Mitigate Double Descent.

Preetum Nakkiran, Prayaag Venkat, Sham M. Kakade, Tengyu Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization.

Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap.

Haike Xu, Tengyu Ma, Simon S. Du

Proceedings of the Conference on Learning Theory, 2021

Shape Matters: Understanding the Implicit Bias of the Noise Covariance.

Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma

Proceedings of the Conference on Learning Theory, 2021

Active Online Learning with Hidden Shifting Domains.

Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling.

Wenxuan Zhou, Kevin Huang, Tengyu Ma, Jing Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Meta-learning Transferable Representations with a Single Target Domain.

Hong Liu, Jeff Z. HaoChen, Colin Wei, Tengyu Ma

CoRR, 2020

Entity and Evidence Guided Relation Extraction for DocRED.

Kevin Huang, Guangtao Wang, Tengyu Ma, Jing Huang

CoRR, 2020

Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK.

Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang

CoRR, 2020

Simplifying Models with Unlabeled Output Data.

Sang Michael Xie, Tengyu Ma, Percy Liang

CoRR, 2020

Active Online Domain Adaptation.

Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang

CoRR, 2020

Robust and On-the-fly Dataset Denoising for Image Classification.

Jiaming Song, Lunjia Hu, Yann N. Dauphin, Michael Auli, Tengyu Ma

CoRR, 2020

Federated Accelerated Stochastic Gradient Descent.

Honglin Yuan, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

MOPO: Model-based Offline Policy Optimization.

Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Beyond Lazy Training for Over-parameterized Tensor Decomposition.

Xiang Wang, Chenwei Wu, Jason D. Lee, Tengyu Ma, Rong Ge

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Model-based Adversarial Meta-Reinforcement Learning.

Zichuan Lin, Garrett Thomas, Guangwen Yang, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-training Avoids Using Spurious Features Under Domain Shift.

Yining Chen, Colin Wei, Ananya Kumar, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Individual Calibration with Randomized Forecasting.

Shengjia Zhao, Tengyu Ma, Stefano Ermon

Proceedings of the 37th International Conference on Machine Learning, 2020

The Implicit and Explicit Regularization Effects of Dropout.

Colin Wei, Sham M. Kakade, Tengyu Ma

Proceedings of the 37th International Conference on Machine Learning, 2020

Understanding Self-Training for Gradual Domain Adaptation.

Ananya Kumar, Tengyu Ma, Percy Liang

Proceedings of the 37th International Conference on Machine Learning, 2020

On the Expressivity of Neural Networks for Deep Reinforcement Learning.

Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma

Proceedings of the 37th International Conference on Machine Learning, 2020

Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin.

Colin Wei, Tengyu Ma

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling.

Yuping Luo, Huazhe Xu, Tengyu Ma

Proceedings of the 8th International Conference on Learning Representations, 2020

Robust and On-the-Fly Dataset Denoising for Image Classification.

Jiaming Song, Yann N. Dauphin, Michael Auli, Tengyu Ma

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Over-Parametrized Two-Layer Neural Networks beyond NTK.

Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang

Proceedings of the Conference on Learning Theory, 2020

Why Do Local Methods Solve Nonconvex Problems?

Tengyu Ma

Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2019

Optimal Design of Process Flexibility for General Production Systems.

Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou

Oper. Res., 2019

Bootstrapping the Expressivity with Model-based Planning.

Kefan Dong, Yuping Luo, Tengyu Ma

CoRR, 2019

Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin.

Colin Wei, Tengyu Ma

CoRR, 2019

A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning.

Nicholas C. Landolfi, Garrett Thomas, Tengyu Ma

CoRR, 2019

Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation.

Colin Wei, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel.

Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks.

Yuanzhi Li, Colin Wei, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Verified Uncertainty Calibration.

Ananya Kumar, Percy Liang, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss.

Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fixup Initialization: Residual Learning Without Normalization.

Hongyi Zhang, Yann N. Dauphin, Tengyu Ma

Proceedings of the 7th International Conference on Learning Representations, 2019

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees.

Yuping Luo, Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma

Proceedings of the 7th International Conference on Learning Representations, 2019

Approximability of Discriminators Implies Diversity in GANs.

Yu Bai, Tengyu Ma, Andrej Risteski

Proceedings of the 7th International Conference on Learning Representations, 2019

On the Performance of Thompson Sampling on Logistic Bandits.

Shi Dong, Tengyu Ma, Benjamin Van Roy

Proceedings of the Conference on Learning Theory, 2019

2018

Linear Algebraic Structure of Word Senses, with Applications to Polysemy.

Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski

Trans. Assoc. Comput. Linguistics, 2018

Gradient Descent Learns Linear Dynamical Systems.

Moritz Hardt, Tengyu Ma, Benjamin Recht

J. Mach. Learn. Res., 2018

On the Margin Theory of Feedforward Neural Networks.

Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma

CoRR, 2018

Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees.

Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma

CoRR, 2018

Generalization and equilibrium in generative adversarial nets (GANs) (invited talk).

Tengyu Ma

Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018

Learning One-hidden-layer Neural Networks with Landscape Design.

Rong Ge, Jason D. Lee, Tengyu Ma

Proceedings of the 6th International Conference on Learning Representations, 2018

Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations.

Yuanzhi Li, Tengyu Ma, Hongyang Zhang

Proceedings of the Conference On Learning Theory, 2018

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors.

Mikhail Khodak, Nikunj Saunshi, Yingyu Liang, Tengyu Ma, Brandon Stewart, Sanjeev Arora

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding

Tengyu Ma

PhD thesis, 2017

Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement.

Jason D. Lee, Qihang Lin, Tengyu Ma, Tianbao Yang

J. Mach. Learn. Res., 2017

Algorithmic Regularization in Over-parameterized Matrix Recovery.

Yuanzhi Li, Tengyu Ma, Hongyang Zhang

CoRR, 2017

Provable learning of noisy-OR networks.

Sanjeev Arora, Rong Ge, Tengyu Ma, Andrej Risteski

Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Finding approximate local minima faster than gradient descent.

Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma

Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Generalization and Equilibrium in Generative Adversarial Nets (GANs).

Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang

Proceedings of the 34th International Conference on Machine Learning, 2017

Identity Matters in Deep Learning.

Moritz Hardt, Tengyu Ma

Proceedings of the 5th International Conference on Learning Representations, 2017

A Simple but Tough-to-Beat Baseline for Sentence Embeddings.

Sanjeev Arora, Yingyu Liang, Tengyu Ma

Proceedings of the 5th International Conference on Learning Representations, 2017

On the Ability of Neural Nets to Express Distributions.

Holden Lee, Rong Ge, Tengyu Ma, Andrej Risteski, Sanjeev Arora

Proceedings of the 30th Conference on Learning Theory, 2017

2016

A Latent Variable Model Approach to PMI-based Word Embeddings.

Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski

Trans. Assoc. Comput. Linguistics, 2016

The Simulated Greedy Algorithm for Several Submodular Matroid Secretary Problems.

Tengyu Ma, Bo Tang, Yajun Wang

Theory Comput. Syst., 2016

Finding Approximate Local Minima for Nonconvex Optimization in Linear Time.

Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma

CoRR, 2016

Communication lower bounds for statistical estimation problems via a distributed data processing inequality.

Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, David P. Woodruff

Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

A Non-generative Framework and Convex Relaxations for Unsupervised Learning.

Elad Hazan, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Matrix Completion has No Spurious Local Minimum.

Rong Ge, Jason D. Lee, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Provable Algorithms for Inference in Topic Models.

Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra

Proceedings of the 33nd International Conference on Machine Learning, 2016

Polynomial-Time Tensor Decompositions with Sum-of-Squares.

Tengyu Ma, Jonathan Shi, David Steurer

Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

2015

Distributed Stochastic Variance Reduced Gradient Methods.

Jason D. Lee, Tengyu Ma, Qihang Lin

CoRR, 2015

Why are deep nets reversible: A simple theory, with implications for training.

Sanjeev Arora, Yingyu Liang, Tengyu Ma

CoRR, 2015

Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings.

Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski

CoRR, 2015

Sum-of-Squares Lower Bounds for Sparse PCA.

Tengyu Ma, Avi Wigderson

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online Learning of Eigenvectors.

Dan Garber, Elad Hazan, Tengyu Ma

Proceedings of the 32nd International Conference on Machine Learning, 2015

Simple, Efficient, and Neural Algorithms for Sparse Coding.

Sanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra

Proceedings of The 28th Conference on Learning Theory, 2015

Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms.

Rong Ge, Tengyu Ma

Proceedings of the Approximation, 2015

2014

Lower Bound for High-Dimensional Statistical Learning Problem via Direct-Sum Theorem.

Ankit Garg, Tengyu Ma, Huy L. Nguyen

CoRR, 2014

More Algorithms for Provable Dictionary Learning.

Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma

CoRR, 2014

On Communication Cost of Distributed Statistical Estimation and Dimensionality.

Ankit Garg, Tengyu Ma, Huy L. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Provable Bounds for Learning Some Deep Representations.

Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

On a conjecture of Butler and Graham.

Tengyu Ma, Xiaoming Sun, Huacheng Yu

Des. Codes Cryptogr., 2013

2011

A New Variation of Hat Guessing Games.

Tengyu Ma, Xiaoming Sun, Huacheng Yu

Proceedings of the Computing and Combinatorics - 17th Annual International Conference, 2011