Yuejie Chi
Orcid: 0000-0002-6766-5459Affiliations:
- Carnegie Mellon University, Pittsburgh, PA, USA
According to our database1,
Yuejie Chi
authored at least 163 papers
between 2010 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction.
CoRR, 2024
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes.
CoRR, 2024
CoRR, 2024
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference.
CoRR, 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices.
CoRR, 2024
2023
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence.
SIAM J. Optim., June, 2023
Math. Program., 2023
IEEE J. Sel. Areas Inf. Theory, 2023
CoRR, 2023
CoRR, 2023
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression.
CoRR, 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization.
CoRR, 2023
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control.
CoRR, 2023
A Multi-Token Coordinate Descent Method for Semi-Decentralized Vertical Federated Learning.
CoRR, 2023
CoRR, 2023
Sharp high-probability sample complexities for policy evaluation with linear function approximation.
CoRR, 2023
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression.
CoRR, 2023
CoRR, 2023
A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model.
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
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning.
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
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction.
IEEE Trans. Inf. Theory, 2022
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization.
SIAM J. Math. Data Sci., 2022
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements.
J. Mach. Learn. Res., 2022
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization.
Oper. Res., 2022
CoRR, 2022
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity.
CoRR, 2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent.
CoRR, 2022
CoRR, 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression.
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
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the IEEE International Conference on Data Mining, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
Privacy-Preserving Federated Multi-Task Linear Regression: A One-Shot Linear Mixing Approach Inspired By Graph Regularization.
Proceedings of the IEEE International Conference on Acoustics, 2022
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Low-Rank Matrix Recovery With Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number.
IEEE Trans. Signal Process., 2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing.
IEEE Trans. Signal Process., 2021
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently.
IEEE Trans. Inf. Theory, 2021
IEEE Trans. Inf. Theory, 2021
J. Mach. Learn. Res., 2021
Found. Trends Mach. Learn., 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Plug-And-Play Image Reconstruction Meets Stochastic Variance-Reduced Gradient Methods.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021
Proceedings of the Conference on Learning Theory, 2021
2020
IEEE Trans. Signal Process., 2020
IEEE Trans. Signal Process., 2020
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data.
IEEE Trans. Signal Process., 2020
IEEE Trans. Signal Inf. Process. over Networks, 2020
On the Stable Resolution Limit of Total Variation Regularization for Spike Deconvolution.
IEEE Trans. Inf. Theory, 2020
Harnessing Sparsity Over the Continuum: Atomic norm minimization for superresolution.
IEEE Signal Process. Mag., 2020
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization.
SIAM J. Optim., 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction.
J. Mach. Learn. Res., 2020
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution.
Found. Comput. Math., 2020
Analytical convergence regions of accelerated gradient descent in nonconvex optimization under Regularity Condition.
Autom., 2020
Proceedings of the HotMobile '20: The 21st International Workshop on Mobile Computing Systems and Applications, 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020
2019
IEEE Trans. Signal Process., 2019
Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval.
Math. Program., 2019
Subspace Estimation from Unbalanced and Incomplete Data Matrices: 𝓁<sub>2, ∞</sub> Statistical Guarantees.
CoRR, 2019
CoRR, 2019
Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution.
CoRR, 2019
Proceedings of the 1st ACM International Workshop on Device-Free Human Sensing, 2019
Proceedings of the IEEE International Symposium on Information Theory, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
Stochastic Approximation and Memory-Limited Subspace Tracking for Poisson Streaming Data.
IEEE Trans. Signal Process., 2018
IEEE Trans. Signal Process., 2018
IEEE Trans. Inf. Theory, 2018
Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation: Recent Theory and Fast Algorithms via Convex and Nonconvex Optimization.
IEEE Signal Process. Mag., 2018
Proc. IEEE, 2018
CoRR, 2018
CoRR, 2018
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
2017
IEEE Trans. Signal Process., 2017
Super-Resolution Image Reconstruction for High-Density Three-Dimensional Single-Molecule Microscopy.
IEEE Trans. Computational Imaging, 2017
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms.
J. Mach. Learn. Res., 2017
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent.
CoRR, 2017
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017
2016
Off-the-Grid Line Spectrum Denoising and Estimation With Multiple Measurement Vectors.
IEEE Trans. Signal Process., 2016
IEEE J. Sel. Top. Signal Process., 2016
Low-Rank Positive Semidefinite Matrix Recovery from Quadratic Measurements with Outliers.
CoRR, 2016
Super-resolution image reconstruction for high-density 3D single-molecule microscopy.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Outlier-robust recovery of low-rank positive semidefinite matrices from magnitude measurements.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Proceedings of the 24th European Signal Processing Conference, 2016
Principal subspace estimation for low-rank Toeplitz covariance matrices with binary sensing.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
2015
IEEE Trans. Signal Process., 2015
Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming.
IEEE Trans. Inf. Theory, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
2014
IEEE Trans. Inf. Theory, 2014
IEEE Trans. Pattern Anal. Mach. Intell., 2014
Compressive parameter estimation with multiple measurement vectors via structured low-rank covariance estimation.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014
Robust and universal covariance estimation from quadratic measurements via convex programming.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Proceedings of the IEEE International Conference on Acoustics, 2014
Estimation of simultaneously structured covariance matrices from quadratic measurements.
Proceedings of the IEEE International Conference on Acoustics, 2014
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014
2013
PETRELS: Parallel Subspace Estimation and Tracking by Recursive Least Squares From Partial Observations.
IEEE Trans. Signal Process., 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
Analysis of fisher information and the Cramer-Rao bound for nonlinear parameter estimation after compressed sensing.
Proceedings of the IEEE International Conference on Acoustics, 2013
Proceedings of the IEEE International Conference on Acoustics, 2013
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013
Proceedings of the 2013 Asilomar Conference on Signals, 2013
Proceedings of the 2013 Asilomar Conference on Signals, 2013
2012
PETRELS: Parallel Estimation and Tracking of Subspace by Recursive Least Squares from Partial Observations
CoRR, 2012
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012
Connecting the dots in multi-class classification: From nearest subspace to collaborative representation.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012
Proceedings of the 50th Annual Allerton Conference on Communication, 2012
2011
Training Signal Design and Tradeoffs for Spectrally-Efficient Multi-User MIMO-OFDM Systems.
IEEE Trans. Wirel. Commun., 2011
IEEE Trans. Signal Process., 2011
On Training Signal Design for Multi-User MIMO-OFDM: Performance Analysis and Tradeoffs.
Proceedings of the 74th IEEE Vehicular Technology Conference, 2011
MMSE-optimal training sequences for spectrally-efficient Multi-User MIMO-OFDM systems.
Proceedings of the 19th European Signal Processing Conference, 2011
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
2010
Proceedings of the IEEE International Symposium on Information Theory, 2010
Proceedings of the International Conference on Image Processing, 2010