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ORCIDYuejie Chi
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- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
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2020 – today
- 2024
[j56]He Wang, Laixi Shi, Yuejie Chi:
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes. RLJ 3: 1467-1510 (2024)- [j55]Gen Li, Yuting Wei
, Yuejie Chi, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. Oper. Res. 72(1): 203-221 (2024) - [j54]Gen Li, Changxiao Cai, Yuxin Chen, Yuting Wei, Yuejie Chi:
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis. Oper. Res. 72(1): 222-236 (2024) - [j53]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. J. Mach. Learn. Res. 25: 4:1-4:48 (2024) - [j52]Laixi Shi, Yuejie Chi:
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity. J. Mach. Learn. Res. 25: 200:1-200:91 (2024) - [j51]Gen Li, Weichen Wu, Yuejie Chi, Cong Ma, Alessandro Rinaldo, Yuting Wei:
High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation. IEEE Trans. Inf. Theory 70(8): 5969-5999 (2024) - [c93]Sijin Chen, Zhize Li, Yuejie Chi:
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. AISTATS 2024: 2701-2709 - [c92]Pedro Valdeira, João Xavier, Cláudia Soares, Yuejie Chi:
Communication-efficient Vertical Federated Learning via Compressed Error Feedback. EUSIPCO 2024: 1037-1041 - [c91]He Wang, Yuejie Chi:
Communication-Efficient Federated Optimization over Semi-Decentralized Networks. ICASSP 2024: 13241-13245 - [c90]Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models. ICLR 2024 - [c89]Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen:
Accelerating Convergence of Score-Based Diffusion Models, Provably. ICML 2024 - [c88]Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi, Beidi Chen:
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference. ICML 2024 - [c87]Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. ICML 2024 - [c86]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. ICML 2024 - [i95]Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai:
Beyond Expectations: Learning with Stochastic Dominance Made Practical. CoRR abs/2402.02698 (2024) - [i94]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. CoRR abs/2402.05876 (2024) - [i93]Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi, Beidi Chen:
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference. CoRR abs/2402.09398 (2024) - [i92]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. CoRR abs/2402.15309 (2024) - [i91]Yu Huang, Zixin Wen, Yuejie Chi, Yingbin Liang:
Transformers Provably Learn Feature-Position Correlations in Masked Image Modeling. CoRR abs/2403.02233 (2024) - [i90]Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen:
Accelerating Convergence of Score-Based Diffusion Models, Provably. CoRR abs/2403.03852 (2024) - [i89]He Wang, Laixi Shi, Yuejie Chi:
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes. CoRR abs/2403.12946 (2024) - [i88]Xingyu Xu, Yuejie Chi:
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction. CoRR abs/2403.17042 (2024) - [i87]Harry Dong, Beidi Chen, Yuejie Chi:
Prompt-prompted Mixture of Experts for Efficient LLM Generation. CoRR abs/2404.01365 (2024) - [i86]Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. CoRR abs/2404.18909 (2024) - [i85]Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai:
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. CoRR abs/2405.19320 (2024) - [i84]Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang:
Learning Discrete Concepts in Latent Hierarchical Models. CoRR abs/2406.00519 (2024) - [i83]Pedro Valdeira, João Xavier, Cláudia Soares, Yuejie Chi:
Communication-efficient Vertical Federated Learning via Compressed Error Feedback. CoRR abs/2406.14420 (2024) - [i82]Gen Li, Yuting Wei, Yuejie Chi, Yuxin Chen:
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models. CoRR abs/2408.02320 (2024) - [i81]Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi:
In-Context Learning with Representations: Contextual Generalization of Trained Transformers. CoRR abs/2408.10147 (2024) - [i80]Sudeep Salgia, Yuejie Chi:
The Sample-Communication Complexity Trade-off in Federated Q-Learning. CoRR abs/2408.16981 (2024) - [i79]Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Can We Break the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning? CoRR abs/2409.20067 (2024) - [i78]Timofey Efimov, Harry Dong, Megna Shah, Jeff P. Simmons, Sean Donegan, Yuejie Chi:
Leveraging Multimodal Diffusion Models to Accelerate Imaging with Side Information. CoRR abs/2410.05143 (2024) - 2023
- [j50]Maxime Ferreira Da Costa, Yuejie Chi:
Local Geometry of Nonconvex Spike Deconvolution From Low-Pass Measurements. IEEE J. Sel. Areas Inf. Theory 4: 1-15 (2023) - [j49]Gen Li, Yuting Wei, Yuejie Chi, Yuxin Chen:
Softmax policy gradient methods can take exponential time to converge. Math. Program. 201(1): 707-802 (2023) - [j48]Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi:
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. SIAM J. Optim. 33(2): 1061-1091 (2023) - [c85]Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang:
Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CVPR 2023: 7918-7928 - [c84]Harry Dong, Megna Shah, Sean Donegan, Yuejie Chi:
Deep Unfolded Tensor Robust PCA With Self-Supervised Learning. ICASSP 2023: 1-5 - [c83]Ruicheng Ao, Shicong Cen, Yuejie Chi:
Asynchronous Gradient Play in Zero-Sum Multi-agent Games. ICLR 2023 - [c82]Shicong Cen, Yuejie Chi, Simon Shaolei Du, Lin Xiao:
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games. ICLR 2023 - [c81]Jiin Woo, Gauri Joshi, Yuejie Chi:
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond. ICML 2023: 37157-37216 - [c80]Xingyu Xu, Yandi Shen, Yuejie Chi, Cong Ma:
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing. ICML 2023: 38611-38654 - [c79]Gen Li, Wenhao Zhan, Jason D. Lee, Yuejie Chi, Yuxin Chen:
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning. NeurIPS 2023 - [c78]Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao:
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. NeurIPS 2023 - [c77]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. NeurIPS 2023 - [c76]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. NeurIPS 2023 - [c75]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. NeurIPS 2023 - [c74]Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist:
Offline Reinforcement Learning with On-Policy Q-Function Regularization. ECML/PKDD (4) 2023: 455-471 - [c73]Yiqi Wang, Mengdi Xu, Laixi Shi, Yuejie Chi:
A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning. UAI 2023: 2226-2236 - [i77]Gen Li, Yanxi Chen, Yuejie Chi, H. Vincent Poor, Yuxin Chen:
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods. CoRR abs/2301.13006 (2023) - [i76]Xingyu Xu, Yandi Shen, Yuejie Chi, Cong Ma:
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing. CoRR abs/2302.01186 (2023) - [i75]Boyue Li, Yuejie Chi:
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression. CoRR abs/2305.09896 (2023) - [i74]Gen Li, Wenhao Zhan, Jason D. Lee, Yuejie Chi, Yuxin Chen:
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning. CoRR abs/2305.10282 (2023) - [i73]Jiin Woo, Gauri Joshi, Yuejie Chi:
The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond. CoRR abs/2305.10697 (2023) - [i72]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. CoRR abs/2305.16589 (2023) - [i71]Gen Li, Weichen Wu, Yuejie Chi, Cong Ma, Alessandro Rinaldo, Yuting Wei:
Sharp high-probability sample complexities for policy evaluation with linear function approximation. CoRR abs/2305.19001 (2023) - [i70]Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang:
Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CoRR abs/2306.04898 (2023) - [i69]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. CoRR abs/2306.07916 (2023) - [i68]Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models. CoRR abs/2306.09251 (2023) - [i67]Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao:
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. CoRR abs/2307.07907 (2023) - [i66]Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist:
Offline Reinforcement Learning with On-Policy Q-Function Regularization. CoRR abs/2307.13824 (2023) - [i65]Harry Dong, Sean Donegan, Megna Shah, Yuejie Chi:
A Lightweight Transformer for Faster and Robust EBSD Data Collection. CoRR abs/2308.09693 (2023) - [i64]Pedro Valdeira, Yuejie Chi, Cláudia Soares, João Xavier:
A Multi-Token Coordinate Descent Method for Semi-Decentralized Vertical Federated Learning. CoRR abs/2309.09977 (2023) - [i63]Shicong Cen, Yuejie Chi:
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control. CoRR abs/2310.05230 (2023) - [i62]Cong Ma, Xingyu Xu, Tian Tong, Yuejie Chi:
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization. CoRR abs/2310.06159 (2023) - [i61]Sijin Chen, Zhize Li, Yuejie Chi:
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. CoRR abs/2310.19059 (2023) - [i60]Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi:
Federated Natural Policy Gradient Methods for Multi-task Reinforcement Learning. CoRR abs/2311.00201 (2023) - [i59]He Wang, Yuejie Chi:
Communication-Efficient Federated Optimization over Semi-Decentralized Networks. CoRR abs/2311.18787 (2023) - 2022
- [j47]Shicong Cen, Chen Cheng, Yuxin Chen, Yuting Wei, Yuejie Chi:
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization. Oper. Res. 70(4): 2563-2578 (2022) - [j46]Tian Tong, Cong Ma, Ashley Prater-Bennette, Erin E. Tripp, Yuejie Chi:
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements. J. Mach. Learn. Res. 23: 163:1-163:77 (2022) - [j45]Boyue Li, Zhize Li, Yuejie Chi:
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. SIAM J. Math. Data Sci. 4(3): 1031-1051 (2022) - [j44]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. IEEE Trans. Inf. Theory 68(1): 448-473 (2022) - [c72]Yuheng Zhang, Hanghang Tong, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying:
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning. AAAI 2022: 9118-9126 - [c71]Diogo Cardoso, Boyue Li, Yuejie Chi, João Xavier:
Harvesting Curvatures for Communication-Efficient Distributed Optimization. IEEECONF 2022: 749-753 - [c70]Tian Tong, Cong Ma, Ashley Prater-Bennette, Erin E. Tripp, Yuejie Chi:
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion. AISTATS 2022: 2607-2617 - [c69]Shicong Cen, Fan Chen, Yuejie Chi:
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization. CDC 2022: 2833-2838 - [c68]Harlin Lee, Andrea L. Bertozzi, Jelena Kovacevic, Yuejie Chi:
Privacy-Preserving Federated Multi-Task Linear Regression: A One-Shot Linear Mixing Approach Inspired By Graph Regularization. ICASSP 2022: 5947-5951 - [c67]Tian Tong, Cong Ma, Yuejie Chi:
Accelerating ILL-Conditioned Robust Low-Rank Tensor Regression. ICASSP 2022: 9072-9076 - [c66]Yuheng Zhang, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying, Hanghang Tong:
Active Heterogeneous Graph Neural Networks with Per-step Meta-Q-Learning. ICDM 2022: 1329-1334 - [c65]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. ICML 2022: 19967-20025 - [c64]Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen:
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model. NeurIPS 2022 - [c63]Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi:
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. NeurIPS 2022 - [c62]Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi:
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression. NeurIPS 2022 - [e1]Diana Marculescu, Yuejie Chi, Carole-Jean Wu:
Proceedings of the Fifth Conference on Machine Learning and Systems, MLSys 2022, Santa Clara, CA, USA, August 29 - September 1, 2022. mlsys.org 2022 [contents] - [i58]Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi:
BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression. CoRR abs/2201.13320 (2022) - [i57]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. CoRR abs/2202.13890 (2022) - [i56]Gen Li, Laixi Shi, Yuxin Chen, Yuejie Chi, Yuting Wei:
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning. CoRR abs/2204.05275 (2022) - [i55]Shicong Cen, Fan Chen, Yuejie Chi:
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization. CoRR abs/2204.05466 (2022) - [i54]Harry Dong, Tian Tong, Cong Ma, Yuejie Chi:
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent. CoRR abs/2206.09109 (2022) - [i53]Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi:
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. CoRR abs/2206.09888 (2022) - [i52]Laixi Shi, Yuejie Chi:
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity. CoRR abs/2208.05767 (2022) - [i51]Maxime Ferreira Da Costa, Yuejie Chi:
Local Geometry of Nonconvex Spike Deconvolution from Low-Pass Measurements. CoRR abs/2208.10073 (2022) - [i50]Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen:
Minimax-Optimal Multi-Agent RL in Zero-Sum Markov Games With a Generative Model. CoRR abs/2208.10458 (2022) - [i49]Shicong Cen, Yuejie Chi, Simon S. Du, Lin Xiao:
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games. CoRR abs/2210.01050 (2022) - [i48]Ruicheng Ao, Shicong Cen, Yuejie Chi:
Asynchronous Gradient Play in Zero-Sum Multi-agent Games. CoRR abs/2211.08980 (2022) - [i47]Harry Dong, Megna Shah, Sean Donegan, Yuejie Chi:
Deep Unfolded Tensor Robust PCA with Self-supervised Learning. CoRR abs/2212.11346 (2022) - 2021
- [j43]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma:
Spectral Methods for Data Science: A Statistical Perspective. Found. Trends Mach. Learn. 14(5): 566-806 (2021) - [j42]Tian Tong, Cong Ma, Yuejie Chi:
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent. J. Mach. Learn. Res. 22: 150:1-150:63 (2021) - [j41]Maxime Ferreira Da Costa, Yuejie Chi:
Compressed Super-Resolution of Positive Sources. IEEE Signal Process. Lett. 28: 56-60 (2021) - [j40]Yuanxin Li, Cong Ma, Yuxin Chen, Yuejie Chi:
Nonconvex Matrix Factorization From Rank-One Measurements. IEEE Trans. Inf. Theory 67(3): 1928-1950 (2021) - [j39]Laixi Shi, Yuejie Chi:
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. IEEE Trans. Inf. Theory 67(7): 4784-4811 (2021) - [j38]Cong Ma, Yuanxin Li, Yuejie Chi:
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing. IEEE Trans. Signal Process. 69: 867-877 (2021) - [j37]Tian Tong, Cong Ma, Yuejie Chi:
Low-Rank Matrix Recovery With Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number. IEEE Trans. Signal Process. 69: 2396-2409 (2021) - [c61]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Softmax Policy Gradient Methods Can Take Exponential Time to Converge. COLT 2021: 3107-3110 - [c60]Vincent Monardo, Abhiram Iyer, Sean Donegan, Marc De Graef, Yuejie Chi:
Plug-And-Play Image Reconstruction Meets Stochastic Variance-Reduced Gradient Methods. ICIP 2021: 2868-2872 - [c59]Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi:
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. ICML 2021: 6296-6306 - [c58]Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei:
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. NeurIPS 2021: 16671-16685 - [c57]Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi:
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. NeurIPS 2021: 17762-17776 - [c56]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. NeurIPS 2021: 27952-27964 - [i46]Cong Ma, Yuanxin Li, Yuejie Chi:
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing. CoRR abs/2101.05113 (2021) - [i45]Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi:
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. CoRR abs/2102.06548 (2021) - [i44]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Softmax Policy Gradient Methods Can Take Exponential Time to Converge. CoRR abs/2102.11270 (2021) - [i43]Tian Tong, Cong Ma, Ashley Prater-Bennette, Erin E. Tripp, Yuejie Chi:
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements. CoRR abs/2104.14526 (2021) - [i42]Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei:
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. CoRR abs/2105.08024 (2021) - [i41]Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi:
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. CoRR abs/2105.11066 (2021) - [i40]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. CoRR abs/2105.15186 (2021) - [i39]Boyue Li, Zhize Li, Yuejie Chi:
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. CoRR abs/2110.01165 (2021) - [i38]Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi:
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. CoRR abs/2110.04645 (2021) - 2020
- [j36]Huaqing Xiong, Yuejie Chi, Bin Hu, Wei Zhang:
Analytical convergence regions of accelerated gradient descent in nonconvex optimization under Regularity Condition. Autom. 113: 108715 (2020) - [j35]Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen:
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution. Found. Comput. Math. 20(3): 451-632 (2020) - [j34]Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi:
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction. J. Mach. Learn. Res. 21: 180:1-180:51 (2020) - [j33]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma, Yuling Yan:
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization. SIAM J. Optim. 30(4): 3098-3121 (2020) - [j32]Yuejie Chi, Maxime Ferreira Da Costa:
Harnessing Sparsity Over the Continuum: Atomic norm minimization for superresolution. IEEE Signal Process. Mag. 37(2): 39-57 (2020) - [j31]Maxime Ferreira Da Costa, Yuejie Chi:
On the Stable Resolution Limit of Total Variation Regularization for Spike Deconvolution. IEEE Trans. Inf. Theory 66(11): 7237-7252 (2020) - [j30]Rohan Varma, Harlin Lee, Jelena Kovacevic, Yuejie Chi:
Vector-Valued Graph Trend Filtering With Non-Convex Penalties. IEEE Trans. Signal Inf. Process. over Networks 6: 48-62 (2020) - [j29]Haoyu Fu, Yuejie Chi, Yingbin Liang:
Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy. IEEE Trans. Signal Process. 68: 3225-3235 (2020) - [j28]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. 68: 3976-3989 (2020) - [j27]Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi:
Learning Latent Features With Pairwise Penalties in Low-Rank Matrix Completion. IEEE Trans. Signal Process. 68: 4210-4225 (2020) - [c55]Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi:
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction. AISTATS 2020: 1662-1672 - [c54]Maxime Ferreira Da Costa, Yuejie Chi:
Support Stability of Spike Deconvolution via Total Variation Minimization. CISS 2020: 1-6 - [c53]Laixi Shi, Yuejie Chi:
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. ICASSP 2020: 5730-5734 - [c52]Kaiyi Ji, Jian Tan, Jinfeng Xu, Yuejie Chi:
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion. SAM 2020: 1-5 - [c51]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. NeurIPS 2020 - [c50]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. NeurIPS 2020 - [c49]Laixi Shi, Yue Zhang, Shijia Pan, Yuejie Chi:
Data Quality-Informed Multiple Occupant Localization using Floor Vibration Sensing. HotMobile 2020: 98 - [i37]Tian Tong, Cong Ma, Yuejie Chi:
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent. CoRR abs/2005.08898 (2020) - [i36]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. CoRR abs/2005.12900 (2020) - [i35]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. CoRR abs/2006.03041 (2020) - [i34]Shicong Cen, Chen Cheng, Yuxin Chen, Yuting Wei, Yuejie Chi:
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization. CoRR abs/2007.06558 (2020) - [i33]Maxime Ferreira Da Costa, Yuejie Chi:
Compressed Super-Resolution of Positive Sources. CoRR abs/2010.10461 (2020) - [i32]Tian Tong, Cong Ma, Yuejie Chi:
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number. CoRR abs/2010.13364 (2020) - [i31]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma:
Spectral Methods for Data Science: A Statistical Perspective. CoRR abs/2012.08496 (2020)
2010 – 2019
- 2019
- [j26]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma:
Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval. Math. Program. 176(1-2): 5-37 (2019) - [j25]Azer P. Shikhaliev, Lee C. Potter, Yuejie Chi:
Low-Rank Structured Covariance Matrix Estimation. IEEE Signal Process. Lett. 26(5): 700-704 (2019) - [j24]Yuejie Chi, Yue M. Lu, Yuxin Chen:
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. IEEE Trans. Signal Process. 67(20): 5239-5269 (2019) - [c48]Maxime Ferreira Da Costa, Yuejie Chi:
Self-Calibrated Super Resolution. ACSSC 2019: 230-234 - [c47]Cong Ma, Yuanxin Li, Yuejie Chi:
Beyond Procrustes: Balancing-free Gradient Descent for Asymmetric Low-Rank Matrix Sensing. ACSSC 2019: 721-725 - [c46]Yuanxin Li, Cong Ma, Yuxin Chen, Yuejie Chi:
Nonconvex Matrix Factorization from Rank-One Measurements. AISTATS 2019: 1496-1505 - [c45]Vincent Monardo, Yuejie Chi:
On the Sensitivity of Spectral Initialization for Noisy Phase Retrieval. ICASSP 2019: 5172-5176 - [c44]Rohan Varma, Harlin Lee, Yuejie Chi, Jelena Kovacevic:
Improving Graph Trend Filtering with Non-convex Penalties. ICASSP 2019: 5391-5395 - [c43]Vincent Monardo, Yuanxin Li, Yuejie Chi:
Solving Quadratic Equations via Amplitude-based Nonconvex Optimization. ICASSP 2019: 5526-5530 - [c42]Myung Cho, Yuejie Chi:
Shift-invariant Subspace Tracking with Missing Data. ICASSP 2019: 8222-8225 - [c41]Haoyu Fu, Yuejie Chi, Yingbin Liang:
Local Geometry of Cross Entropy Loss in Learning One-Hidden-Layer Neural Networks. ISIT 2019: 1972-1976 - [c40]Laixi Shi, Mostafa Mirshekari, Jonathon Fagert, Yuejie Chi, Hae Young Noh, Pei Zhang, Shijia Pan:
Device-free Multiple People Localization through Floor Vibration. DFHS@BuildSys 2019: 57-61 - [i30]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma, Yuling Yan:
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization. CoRR abs/1902.07698 (2019) - [i29]Yuejie Chi, Maxime Ferreira Da Costa:
Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution. CoRR abs/1904.04283 (2019) - [i28]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data. CoRR abs/1905.12648 (2019) - [i27]Rohan Varma, Harlin Lee, Jelena Kovacevic, Yuejie Chi:
Vector-Valued Graph Trend Filtering with Non-Convex Penalties. CoRR abs/1905.12692 (2019) - [i26]Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi:
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking. CoRR abs/1909.05844 (2019) - [i25]Maxime Ferreira Da Costa, Yuejie Chi:
On the Stable Resolution Limit of Total Variation Regularization for Spike Deconvolution. CoRR abs/1910.01629 (2019) - [i24]Changxiao Cai, Gen Li, Yuejie Chi, H. Vincent Poor, Yuxin Chen:
Subspace Estimation from Unbalanced and Incomplete Data Matrices: 𝓁2, ∞ Statistical Guarantees. CoRR abs/1910.04267 (2019) - [i23]Laixi Shi, Yuejie Chi:
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. CoRR abs/1911.11167 (2019) - 2018
- [j23]Namrata Vaswani, Yuejie Chi, Thierry Bouwmans:
Rethinking PCA for Modern Data Sets: Theory, Algorithms, and Applications. Proc. IEEE 106(8): 1274-1276 (2018) - [j22]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. Proc. IEEE 106(8): 1293-1310 (2018) - [j21]Yudong Chen, Yuejie Chi:
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. 35(4): 14-31 (2018) - [j20]Yuejie Chi:
Low-Rank Matrix Completion [Lecture Notes]. IEEE Signal Process. Mag. 35(5): 178-181 (2018) - [j19]Huishuai Zhang, Yuejie Chi, Yingbin Liang:
Median-Truncated Nonconvex Approach for Phase Retrieval With Outliers. IEEE Trans. Inf. Theory 64(11): 7287-7310 (2018) - [j18]Liming Wang, Yuejie Chi:
Stochastic Approximation and Memory-Limited Subspace Tracking for Poisson Streaming Data. IEEE Trans. Signal Process. 66(4): 1051-1064 (2018) - [j17]Haoyu Fu, Yuejie Chi:
Quantized Spectral Compressed Sensing: Cramer-Rao Bounds and Recovery Algorithms. IEEE Trans. Signal Process. 66(12): 3268-3279 (2018) - [c39]Pu Wang, Toshiaki Koike-Akino, Philip V. Orlik, Haoyu Fu, Yuejie Chi:
Terahertz Imaging of Binary Reflectance with Variational Bayesian Inference. ICASSP 2018: 3394-3398 - [c38]Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen:
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion. ICML 2018: 3351-3360 - [c37]Myung Cho, Wenjing Liao, Yuejie Chi:
A Non-Convex Approach To Joint Sensor Calibration And Spectrum Estimation. SSP 2018: 398-402 - [i22]Kaiyi Ji, Jian Tan, Yuejie Chi, Jinfeng Xu:
Learning Latent Features with Pairwise Penalties in Matrix Completion. CoRR abs/1802.05821 (2018) - [i21]Yuanxin Li, Cong Ma, Yuxin Chen, Yuejie Chi:
Nonconvex Matrix Factorization from Rank-One Measurements. CoRR abs/1802.06286 (2018) - [i20]Haoyu Fu, Yuejie Chi, Yingbin Liang:
Local Geometry of One-Hidden-Layer Neural Networks for Logistic Regression. CoRR abs/1802.06463 (2018) - [i19]Yudong Chen, Yuejie Chi:
Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation. CoRR abs/1802.08397 (2018) - [i18]Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma:
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval. CoRR abs/1803.07726 (2018) - [i17]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. CoRR abs/1806.04609 (2018) - [i16]Yuejie Chi, Yue M. Lu, Yuxin Chen:
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. CoRR abs/1809.09573 (2018) - 2017
- [j16]Huishuai Zhang, Yingbin Liang, Yuejie Chi:
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms. J. Mach. Learn. Res. 18: 141:1-141:35 (2017) - [j15]Jiaqing Huang, Mingzhai Sun, Jianjie Ma, Yuejie Chi:
Super-Resolution Image Reconstruction for High-Density Three-Dimensional Single-Molecule Microscopy. IEEE Trans. Computational Imaging 3(4): 763-773 (2017) - [j14]Yuanxin Li, Yue Sun, Yuejie Chi:
Low-Rank Positive Semidefinite Matrix Recovery From Corrupted Rank-One Measurements. IEEE Trans. Signal Process. 65(2): 397-408 (2017) - [j13]Yuejie Chi, Haoyu Fu:
Subspace Learning From Bits. IEEE Trans. Signal Process. 65(17): 4429-4442 (2017) - [c36]Haoyu Fu, Yuejie Chi:
Compressive spectrum estimation using quantized measurements. ACSSC 2017: 686-690 - [c35]Liming Wang, Yuejie Chi:
Memory-Limited stochastic approximation for poisson subspace tracking. CAMSAP 2017: 1-5 - [i15]Yuanxin Li, Yuejie Chi, Huishuai Zhang, Yingbin Liang:
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent. CoRR abs/1709.08114 (2017) - [i14]Haoyu Fu, Yuejie Chi:
Quantized Spectral Compressed Sensing: Cramer-Rao Bounds and Recovery Algorithms. CoRR abs/1710.03654 (2017) - [i13]Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen:
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion and Blind Deconvolution. CoRR abs/1711.10467 (2017) - 2016
- [j12]Yuejie Chi:
Guaranteed Blind Sparse Spikes Deconvolution via Lifting and Convex Optimization. IEEE J. Sel. Top. Signal Process. 10(4): 782-794 (2016) - [j11]Yuejie Chi, Yue M. Lu:
Kaczmarz Method for Solving Quadratic Equations. IEEE Signal Process. Lett. 23(9): 1183-1187 (2016) - [j10]Liming Wang, Yuejie Chi:
Blind Deconvolution From Multiple Sparse Inputs. IEEE Signal Process. Lett. 23(10): 1384-1388 (2016) - [j9]Yuanxin Li, Yuejie Chi:
Off-the-Grid Line Spectrum Denoising and Estimation With Multiple Measurement Vectors. IEEE Trans. Signal Process. 64(5): 1257-1269 (2016) - [c34]Haoyu Fu, Yuejie Chi:
Principal subspace estimation for low-rank Toeplitz covariance matrices with binary sensing. ACSSC 2016: 1344-1348 - [c33]Yuejie Chi:
Kronecker covariance sketching for spatial-temporal data. EUSIPCO 2016: 316-320 - [c32]Yuejie Chi:
Robust blind spikes deconvolution. ICASSP 2016: 2906-2910 - [c31]Yue Sun, Yuanxin Li, Yuejie Chi:
Outlier-robust recovery of low-rank positive semidefinite matrices from magnitude measurements. ICASSP 2016: 4069-4073 - [c30]Huishuai Zhang, Yuejie Chi, Yingbin Liang:
Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow. ICML 2016: 1022-1031 - [c29]Jiaqing Huang, Mingzhai Sun, Yuejie Chi:
Super-resolution image reconstruction for high-density 3D single-molecule microscopy. ISBI 2016: 241-244 - [i12]Yuanxin Li, Yue Sun, Yuejie Chi:
Low-Rank Positive Semidefinite Matrix Recovery from Quadratic Measurements with Outliers. CoRR abs/1602.02737 (2016) - 2015
- [j8]Yao Li, Yuejie Chi, Chu-Hsiang Huang, Lara Dolecek:
Orthogonal Matching Pursuit on Faulty Circuits. IEEE Trans. Commun. 63(7): 2541-2554 (2015) - [j7]Yuxin Chen, Yuejie Chi, Andrea J. Goldsmith:
Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming. IEEE Trans. Inf. Theory 61(7): 4034-4059 (2015) - [j6]Yuejie Chi, Yuxin Chen:
Compressive Two-Dimensional Harmonic Retrieval via Atomic Norm Minimization. IEEE Trans. Signal Process. 63(4): 1030-1042 (2015) - [c28]Yuejie Chi, Yihong Wu:
Change-point estimation of high-dimensional streaming data via sketching. ACSSC 2015: 102-106 - [c27]Yuejie Chi:
Blind super-resolution of sparse spike signals. ACSSC 2015: 1779-1782 - [c26]Yuanxin Li, Yingsheng He, Yuejie Chi, Yue M. Lu:
Blind calibration of multi-channel samplers using sparse recovery. CAMSAP 2015: 33-36 - [c25]Yuejie Chi:
Compressive graph clustering from random sketches. ICASSP 2015: 5466-5469 - [c24]Yiran Jiang, Yuejie Chi:
Covariance tracking from sketches of rapid data streams. ICASSP 2015: 5470-5474 - [c23]Yuanxin Li, Yuejie Chi:
Super-resolution of mutually interfering signals. ISIT 2015: 984-988 - [i11]Yuanxin Li, Yuejie Chi:
Super-Resolution of Mutually Interfering Signals. CoRR abs/1504.06015 (2015) - [i10]Yuejie Chi:
Guaranteed Blind Sparse Spikes Deconvolution via Lifting and Convex Optimization. CoRR abs/1506.02751 (2015) - [i9]Yuanxin Li, Yuejie Chi:
Stable Separation and Super-Resolution of Mixture Models. CoRR abs/1506.07347 (2015) - 2014
- [j5]Yuejie Chi, Fatih Porikli:
Classification and Boosting with Multiple Collaborative Representations. IEEE Trans. Pattern Anal. Mach. Intell. 36(8): 1519-1531 (2014) - [j4]Yuxin Chen, Yuejie Chi:
Robust Spectral Compressed Sensing via Structured Matrix Completion. IEEE Trans. Inf. Theory 60(10): 6576-6601 (2014) - [c22]Yuejie Chi:
One-bit principal subspace estimation. GlobalSIP 2014: 419-423 - [c21]Yuejie Chi:
Joint sparsity recovery for spectral compressed sensing. ICASSP 2014: 3938-3942 - [c20]Yuxin Chen, Yuejie Chi, Andrea J. Goldsmith:
Estimation of simultaneously structured covariance matrices from quadratic measurements. ICASSP 2014: 7669-7673 - [c19]Yuxin Chen, Yuejie Chi, Andrea J. Goldsmith:
Robust and universal covariance estimation from quadratic measurements via convex programming. ISIT 2014: 2017-2021 - [c18]Yuanxin Li, Yuejie Chi:
Compressive parameter estimation with multiple measurement vectors via structured low-rank covariance estimation. SSP 2014: 384-387 - [i8]Yuejie Chi:
Subspace Learning From Bits. CoRR abs/1407.6288 (2014) - [i7]Yuanxin Li, Yuejie Chi:
Off-the-Grid Line Spectrum Denoising and Estimation with Multiple Measurement Vectors. CoRR abs/1408.2242 (2014) - 2013
- [j3]Yuejie Chi, Yonina C. Eldar, A. Robert Calderbank:
PETRELS: Parallel Subspace Estimation and Tracking by Recursive Least Squares From Partial Observations. IEEE Trans. Signal Process. 61(23): 5947-5959 (2013) - [c17]Yuejie Chi, Yuxin Chen:
Compressive recovery of 2-D off-grid frequencies. ACSSC 2013: 687-691 - [c16]Yuejie Chi:
Nearest subspace classification with missing data. ACSSC 2013: 1667-1671 - [c15]Yuejie Chi:
Sparse MIMO radar via structured matrix completion. GlobalSIP 2013: 321-324 - [c14]Yao Xie, Yuejie Chi, A. Robert Calderbank:
Low-rank matrix recovery with poison noise. GlobalSIP 2013: 622 - [c13]Yuejie Chi, A. Robert Calderbank:
Knowledge-enhanced Matching Pursuit. ICASSP 2013: 6576-6580 - [c12]Pooria Pakrooh, Louis L. Scharf, Ali Pezeshki, Yuejie Chi:
Analysis of fisher information and the Cramer-Rao bound for nonlinear parameter estimation after compressed sensing. ICASSP 2013: 6630-6634 - [c11]Yuxin Chen, Yuejie Chi:
Spectral Compressed Sensing via Structured Matrix Completion. ICML (3) 2013: 414-422 - [i6]Yuejie Chi, Yao Xie, A. Robert Calderbank:
Compressive Demodulation of Mutually Interfering Signals. CoRR abs/1303.3904 (2013) - [i5]Yuxin Chen, Yuejie Chi:
Spectral Compressed Sensing via Structured Matrix Completion. CoRR abs/1304.4610 (2013) - [i4]Yuxin Chen, Yuejie Chi:
Robust Spectral Compressed Sensing via Structured Matrix Completion. CoRR abs/1304.8126 (2013) - [i3]Yuxin Chen, Yuejie Chi, Andrea Goldsmith:
Exact and Stable Covariance Estimation from Quadratic Sampling via Convex Programming. CoRR abs/1310.0807 (2013) - [i2]Yuejie Chi:
Joint Sparsity Recovery for Spectral Compressed Sensing. CoRR abs/1311.2229 (2013) - 2012
- [c10]Yuejie Chi, A. Robert Calderbank:
Coherence-based performance guarantees of Orthogonal Matching Pursuit. Allerton Conference 2012: 2003-2009 - [c9]Yuejie Chi, Fatih Porikli:
Connecting the dots in multi-class classification: From nearest subspace to collaborative representation. CVPR 2012: 3602-3609 - [c8]Yuejie Chi, Yonina C. Eldar, A. Robert Calderbank:
PETRELS: Subspace estimation and tracking from partial observations. ICASSP 2012: 3301-3304 - [c7]Yao Xie, Yuejie Chi, Lorne Applebaum, A. Robert Calderbank:
Compressive demodulation of mutually interfering signals. SSP 2012: 592-595 - [i1]Yuejie Chi, Yonina C. Eldar, A. Robert Calderbank:
PETRELS: Parallel Estimation and Tracking of Subspace by Recursive Least Squares from Partial Observations. CoRR abs/1207.6353 (2012) - 2011
- [j2]Yuejie Chi, Louis L. Scharf, Ali Pezeshki, A. Robert Calderbank:
Sensitivity to Basis Mismatch in Compressed Sensing. IEEE Trans. Signal Process. 59(5): 2182-2195 (2011) - [j1]Yuejie Chi, Ahmad Gomaa, Naofal Al-Dhahir, A. Robert Calderbank:
Training Signal Design and Tradeoffs for Spectrally-Efficient Multi-User MIMO-OFDM Systems. IEEE Trans. Wirel. Commun. 10(7): 2234-2245 (2011) - [c6]Harinath Garudadri, Yuejie Chi, Steve Baker, Somdeb Majumdar, Pawan K. Baheti, Dan Ballard:
Diagnostic grade wireless ECG monitoring. EMBC 2011: 850-855 - [c5]Yuejie Chi, Ahmad Gomaa, Naofal Al-Dhahir, A. Robert Calderbank:
MMSE-optimal training sequences for spectrally-efficient Multi-User MIMO-OFDM systems. EUSIPCO 2011: 634-638 - [c4]Ahmad Gomaa, Yuejie Chi, Naofal Al-Dhahir, A. Robert Calderbank:
On Training Signal Design for Multi-User MIMO-OFDM: Performance Analysis and Tradeoffs. VTC Fall 2011: 1-5 - 2010
- [c3]Yuejie Chi, Ali Pezeshki, Louis L. Scharf, A. Robert Calderbank:
Sensitivity to basis mismatch in compressed sensing. ICASSP 2010: 3930-3933 - [c2]Yiyue Wu, Yuejie Chi, A. Robert Calderbank:
Compressive blind source separation. ICIP 2010: 89-92 - [c1]Yuejie Chi, Yiyue Wu, A. Robert Calderbank:
Regularized blind detection for MIMO communications. ISIT 2010: 2108-2112
Coauthor Index
[j55] [j54] [c90] [c89] [i90] [i82] [j49] [j48] [c79] [c76] [i77] [i74] [i72] [i68] [i60] [j47] [j44] [c65] [c64] [i57] [i56] [i50] [j43] [j40] [c61] [c59] [c58] [c57] [i45] [i44] [i42] [i41] [i38] [j35] [j34] [j33] [c55] [c51] [c50] [i36] [i35] [i34] [i31] [j26] [j24] [c46] [i30] [i26] [i24] [c38] [i21] [i18] [i16] [i13] [j7] [j6] [j4] [c20] [c19] [c17] [c11] [i5] [i4] [i3]
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