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ORCIDZhao Song 0002
Person information
- affiliation: Adobe Research
- affiliation (former): Institute for Advanced Study, Princeton, NJ, USA
- affiliation (former): Princeton University, NJ, USA
- affiliation (former): University of Washington, DC, USA
- affiliation (PhD 2019): University of Texas at Austin, Department of Computer Science, USA
- affiliation (former): Harvard University, Cambridge, MA, USA
- affiliation (former): University of California Berkeley, CA, USA
- affiliation (former): Simon Fraser University, School of Computing Science, Burnaby, Canada
Other persons with the same name
- Zhao Song 0001 — Amazon AWS AI Labs, Santa Clara, CA, USA (and 2 more)
- Zhao Song 0003 — Iowa State University, Department of Electrical and Computer Engineering, Ames, IA, USA
- Zhao Song 0004 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, China (and 1 more)
- Zhao Song 0005 — Zhengzhou Institute of Aeronautical Industry Management, Henan, China
- Zhao Song 0006 — University of Missouri, Department of Computer Science, Columbia, USA
- Zhao Song 0007 — State University of New York at Buffalo, Department of Mathematics, NY, USA
- Zhao Song 0008 — Northwestern Polytechnical University, School of Mechanical Engineering, OPTIMAL, Xi'an, China
- Zhao Song 0009 — Munich University of Applied Sciences, Laboratory for Mechatronic and Renewable Energy Systems, Germany
- Zhao Song 0010 — Alibaba Group
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2020 – today
- 2023
[i108]Zhao Song, Tianyi Zhou:
Faster Sinkhorn's Algorithm with Small Treewidth. CoRR abs/2301.06741 (2023)- 2022
- [j8]Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu:
Differentially Oblivious Relational Database Operators. Proc. VLDB Endow. 16(4): 842-855 (2022) - [j7]András Gilyén, Zhao Song, Ewin Tang
:
An improved quantum-inspired algorithm for linear regression. Quantum 6: 754 (2022) - [c80]Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo:
Fast Graph Neural Tangent Kernel via Kronecker Sketching. AAAI 2022: 7033-7041 - [c79]Zhao Song, Ruizhe Zhang:
Hyperbolic Concentration, Anti-Concentration, and Discrepancy. APPROX/RANDOM 2022: 10:1-10:19 - [c78]Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang:
Solving SDP Faster: A Robust IPM Framework and Efficient Implementation. FOCS 2022: 233-244 - [c77]Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré:
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. ICLR 2022 - [c76]Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré:
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning. ICML 2022: 3090-3122 - [c75]Alexander Munteanu, Simon Omlor, Zhao Song, David P. Woodruff:
Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis. ICML 2022: 16083-16122 - [c74]Aravind Reddy, Ryan A. Rossi, Zhao Song, Anup B. Rao, Tung Mai, Nedim Lipka, Gang Wu, Eunyee Koh, Nesreen K. Ahmed:
One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes. ICML 2022: 18463-18482 - [c73]Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang:
Symmetric Sparse Boolean Matrix Factorization and Applications. ITCS 2022: 46:1-46:25 - [i107]Baihe Huang, Zhao Song, Omri Weinstein, Hengjie Zhang, Ruizhe Zhang:
A Dynamic Fast Gaussian Transform. CoRR abs/2202.12329 (2022) - [i106]Zhao Song, Zhaozhuo Xu, Lichen Zhang:
Speeding Up Sparsification using Inner Product Search Data Structures. CoRR abs/2204.03209 (2022) - [i105]Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré:
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning. CoRR abs/2204.07596 (2022) - [i104]Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan:
Smoothed Online Combinatorial Optimization Using Imperfect Predictions. CoRR abs/2204.10979 (2022) - [i103]Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang:
Sparse Fourier Transform over Lattices: A Unified Approach to Signal Reconstruction. CoRR abs/2205.00658 (2022) - [i102]Yichuan Deng, Zhao Song, Omri Weinstein, Ruizhe Zhang:
Fast Distance Oracles for Any Symmetric Norm. CoRR abs/2205.14816 (2022) - [i101]Alexander Munteanu, Simon Omlor, Zhao Song, David P. Woodruff:
Bounding the Width of Neural Networks via Coupled Initialization - A Worst Case Analysis. CoRR abs/2206.12802 (2022) - [i100]Zhao Song, Zhaozhuo Xu, Yuanyuan Yang, Lichen Zhang:
Accelerating Frank-Wolfe Algorithm using Low-Dimensional and Adaptive Data Structures. CoRR abs/2207.09002 (2022) - [i99]Hang Hu, Zhao Song, Runzhou Tao, Zhaozhuo Xu, Danyang Zhuo:
Sublinear Time Algorithm for Online Weighted Bipartite Matching. CoRR abs/2208.03367 (2022) - [i98]Xiaoxiao Li, Zhao Song, Jiaming Yang:
Federated Adversarial Learning: A Framework with Convergence Analysis. CoRR abs/2208.03635 (2022) - [i97]Jiehao Liang, Zhao Song, Zhaozhuo Xu, Danyang Zhuo:
Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory. CoRR abs/2208.03915 (2022) - [i96]Hang Hu, Zhao Song, Omri Weinstein, Danyang Zhuo:
Training Overparametrized Neural Networks in Sublinear Time. CoRR abs/2208.04508 (2022) - [i95]Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang:
A Sublinear Adversarial Training Algorithm. CoRR abs/2208.05395 (2022) - [i94]Yeqi Gao, Zhao Song, Baocheng Sun:
An O(k log n) Time Fourier Set Query Algorithm. CoRR abs/2208.09634 (2022) - [i93]Aravind Reddy, Zhao Song, Lichen Zhang:
Dynamic Tensor Product Regression. CoRR abs/2210.03961 (2022) - [i92]Yichuan Deng, Zhao Song, Yitan Wang, Yuanyuan Yang:
A Nearly Optimal Size Coreset Algorithm with Nearly Linear Time. CoRR abs/2210.08361 (2022) - [i91]Zhao Song, Yitan Wang, Zheng Yu, Lichen Zhang:
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability. CoRR abs/2210.08371 (2022) - [i90]Zhao Song, Xin Yang, Yuanyuan Yang, Lichen Zhang:
Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance. CoRR abs/2210.11542 (2022) - [i89]Yichuan Deng, Zhao Song, Omri Weinstein:
Discrepancy Minimization in Input-Sparsity Time. CoRR abs/2210.12468 (2022) - [i88]Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang:
Quartic Samples Suffice for Fourier Interpolation. CoRR abs/2210.12495 (2022) - [i87]Xiaoxiao Li, Zhao Song, Runzhou Tao, Guangyi Zhang:
A Convergence Theory for Federated Average: Beyond Smoothness. CoRR abs/2211.01588 (2022) - [i86]Yuzhou Gu, Zhao Song:
A Faster Small Treewidth SDP Solver. CoRR abs/2211.06033 (2022) - [i85]Josh Alman, Jiehao Liang, Zhao Song, Ruizhe Zhang, Danyang Zhuo:
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing. CoRR abs/2211.14227 (2022) - [i84]Zhao Song, Xin Yang, Yuanyuan Yang, Tianyi Zhou:
Faster Algorithm for Structured John Ellipsoid Computation. CoRR abs/2211.14407 (2022) - [i83]Yichuan Deng, Wenyu Jin, Zhao Song, Xiaorui Sun, Omri Weinstein:
Dynamic Kernel Sparsifiers. CoRR abs/2211.14825 (2022) - [i82]Jiehao Liang, Somdeb Sarkhel, Zhao Song, Chenbo Yin, Danyang Zhuo:
A Faster k-means++ Algorithm. CoRR abs/2211.15118 (2022) - [i81]Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu:
Adore: Differentially Oblivious Relational Database Operators. CoRR abs/2212.05176 (2022) - [i80]Lianke Qin, Aravind Reddy, Zhao Song, Zhaozhuo Xu, Danyang Zhuo:
Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations. CoRR abs/2212.11408 (2022) - 2021
- [j6]Michael B. Cohen, Yin Tat Lee, Zhao Song:
Solving Linear Programs in the Current Matrix Multiplication Time. J. ACM 68(1): 3:1-3:39 (2021) - [c72]Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu:
Near-Optimal Two-Pass Streaming Algorithm for Sampling Random Walks over Directed Graphs. ICALP 2021: 52:1-52:19 - [c71]Sitan Chen, Xiaoxiao Li, Zhao Song, Danyang Zhuo:
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization. ICLR 2021 - [c70]Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré:
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR 2021 - [c69]Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang:
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis. ICML 2021: 4423-4434 - [c68]Zhao Song, David P. Woodruff, Zheng Yu, Lichen Zhang:
Fast Sketching of Polynomial Kernels of Polynomial Degree. ICML 2021: 9812-9823 - [c67]Zhao Song, Zheng Yu:
Oblivious Sketching-based Central Path Method for Linear Programming. ICML 2021: 9835-9847 - [c66]Jan van den Brand, Binghui Peng, Zhao Song, Omri Weinstein:
Training (Overparametrized) Neural Networks in Near-Linear Time. ITCS 2021: 63:1-63:15 - [c65]Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava:
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures. NeurIPS 2021: 5576-5589 - [c64]Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora:
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. NeurIPS 2021: 7232-7241 - [c63]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention. NeurIPS 2021: 17413-17426 - [c62]Zhao Song, Shuo Yang, Ruizhe Zhang:
Does Preprocessing Help Training Over-parameterized Neural Networks? NeurIPS 2021: 22890-22904 - [c61]Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu:
Almost optimal super-constant-pass streaming lower bounds for reachability. STOC 2021: 570-583 - [c60]Shunhua Jiang, Zhao Song, Omri Weinstein, Hengjie Zhang:
A faster algorithm for solving general LPs. STOC 2021: 823-832 - [c59]Jan van den Brand, Yin Tat Lee, Yang P. Liu, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang:
Minimum cost flows, MDPs, and ℓ1-regression in nearly linear time for dense instances. STOC 2021: 859-869 - [c58]Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu:
When is particle filtering efficient for planning in partially observed linear dynamical systems? UAI 2021: 728-737 - [i79]Jan van den Brand, Yin Tat Lee, Yang P. Liu, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang:
Minimum Cost Flows, MDPs, and 𝓁1-Regression in Nearly Linear Time for Dense Instances. CoRR abs/2101.05719 (2021) - [i78]Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao:
Solving Tall Dense SDPs in the Current Matrix Multiplication Time. CoRR abs/2101.08208 (2021) - [i77]Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang:
Symmetric Boolean Factor Analysis with Applications to InstaHide. CoRR abs/2102.01570 (2021) - [i76]Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh Saxena, Zhao Song, Huacheng Yu:
Near-Optimal Two-Pass Streaming Algorithm for Sampling Random Walks over Directed Graphs. CoRR abs/2102.11251 (2021) - [i75]Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang:
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis. CoRR abs/2105.05001 (2021) - [i74]Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu:
Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing. CoRR abs/2105.08285 (2021) - [i73]Zhao Song, David P. Woodruff, Zheng Yu, Lichen Zhang:
Fast Sketching of Polynomial Kernels of Polynomial Degree. CoRR abs/2108.09420 (2021) - [i72]Zhao Song, Shuo Yang, Ruizhe Zhang:
Does Preprocessing Help Training Over-parameterized Neural Networks? CoRR abs/2110.04622 (2021) - [i71]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention Approximation. CoRR abs/2110.15343 (2021) - [i70]Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco:
An Interpretable Graph Generative Model with Heterophily. CoRR abs/2111.03030 (2021) - [i69]Aviad Rubinstein, Saeed Seddighin, Zhao Song, Xiaorui Sun:
Approximation Algorithms for LCS and LIS with Truly Improved Running Times. CoRR abs/2111.10538 (2021) - [i68]Aravind Reddy, Ryan A. Rossi, Zhao Song, Anup B. Rao, Tung Mai, Nedim Lipka, Gang Wu, Eunyee Koh, Nesreen K. Ahmed:
Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes. CoRR abs/2111.14674 (2021) - [i67]Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu:
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures. CoRR abs/2111.15139 (2021) - [i66]Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré:
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. CoRR abs/2112.00029 (2021) - [i65]Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora:
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. CoRR abs/2112.00059 (2021) - [i64]Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo:
Fast Graph Neural Tangent Kernel via Kronecker Sketching. CoRR abs/2112.02446 (2021) - [i63]Wei Deng, Yi-An Ma, Zhao Song, Qian Zhang, Guang Lin:
On Convergence of Federated Averaging Langevin Dynamics. CoRR abs/2112.05120 (2021) - [i62]Zhao Song, Lichen Zhang, Ruizhe Zhang:
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time. CoRR abs/2112.07628 (2021) - [i61]Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh Saxena, Zhao Song, Huacheng Yu:
Almost Optimal Super-Constant-Pass Streaming Lower Bounds for Reachability. Electron. Colloquium Comput. Complex. TR21 (2021) - 2020
- [c57]Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang:
Sketching Transformed Matrices with Applications to Natural Language Processing. AISTATS 2020: 467-481 - [c56]Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora:
TextHide: Tackling Data Privacy for Language Understanding Tasks. EMNLP (Findings) 2020: 1368-1382 - [c55]Josh Alman, Timothy Chu, Aaron Schild, Zhao Song:
Algorithms and Hardness for Linear Algebra on Geometric Graphs. FOCS 2020: 541-552 - [c54]Haotian Jiang, Tarun Kathuria, Yin Tat Lee, Swati Padmanabhan, Zhao Song:
A Faster Interior Point Method for Semidefinite Programming. FOCS 2020: 910-918 - [c53]Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang:
Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. FOCS 2020: 919-930 - [c52]Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora:
InstaHide: Instance-hiding Schemes for Private Distributed Learning. ICML 2020: 4507-4518 - [c51]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for Mixed Linear Regression. ICML 2020: 5394-5404 - [c50]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. NeurIPS 2020 - [c49]Yi Zhang, Orestis Plevrakis, Simon S. Du, Xingguo Li, Zhao Song, Sanjeev Arora:
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality. NeurIPS 2020 - [c48]Aviad Rubinstein, Zhao Song:
Reducing approximate Longest Common Subsequence to approximate Edit Distance. SODA 2020: 1591-1600 - [c47]Sitan Chen, Jerry Li, Zhao Song:
Learning mixtures of linear regressions in subexponential time via Fourier moments. STOC 2020: 587-600 - [c46]Jan van den Brand, Yin Tat Lee, Aaron Sidford, Zhao Song:
Solving tall dense linear programs in nearly linear time. STOC 2020: 775-788 - [c45]Haotian Jiang, Yin Tat Lee, Zhao Song, Sam Chiu-wai Wong:
An improved cutting plane method for convex optimization, convex-concave games, and its applications. STOC 2020: 944-953 - [i60]Jan van den Brand, Yin Tat Lee, Aaron Sidford, Zhao Song:
Solving Tall Dense Linear Programs in Nearly Linear Time. CoRR abs/2002.02304 (2020) - [i59]Yi Zhang, Orestis Plevrakis, Simon S. Du, Xingguo Li, Zhao Song, Sanjeev Arora:
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality. CoRR abs/2002.06668 (2020) - [i58]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for mixed linear regression. CoRR abs/2002.08936 (2020) - [i57]Yingyu Liang, Zhao Song, Mengdi Wang, Lin F. Yang, Xin Yang:
Sketching Transformed Matrices with Applications to Natural Language Processing. CoRR abs/2002.09812 (2020) - [i56]Yangsibo Huang, Yushan Su, Sachin Ravi, Zhao Song, Sanjeev Arora, Kai Li:
Privacy-preserving Learning via Deep Net Pruning. CoRR abs/2003.01876 (2020) - [i55]Haotian Jiang, Yin Tat Lee, Zhao Song, Sam Chiu-wai Wong:
An Improved Cutting Plane Method for Convex Optimization, Convex-Concave Games and its Applications. CoRR abs/2004.04250 (2020) - [i54]Shunhua Jiang, Zhao Song, Omri Weinstein, Hengjie Zhang:
Faster Dynamic Matrix Inverse for Faster LPs. CoRR abs/2004.07470 (2020) - [i53]Zhao Song, David P. Woodruff, Peilin Zhong:
Average Case Column Subset Selection for Entrywise 𝓁1-Norm Loss. CoRR abs/2004.07986 (2020) - [i52]Yaonan Jin, Daogao Liu, Zhao Song:
A robust multi-dimensional sparse Fourier transform in the continuous setting. CoRR abs/2005.06156 (2020) - [i51]Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu:
When is Particle Filtering Efficient for POMDP Sequential Planning? CoRR abs/2006.05975 (2020) - [i50]Jan van den Brand, Binghui Peng, Zhao Song, Omri Weinstein:
Training (Overparametrized) Neural Networks in Near-Linear Time. CoRR abs/2006.11648 (2020) - [i49]Zhao Song, Ruizhe Zhang:
Hyperbolic Polynomials I : Concentration and Discrepancy. CoRR abs/2008.09593 (2020) - [i48]Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang:
Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. CoRR abs/2009.01802 (2020) - [i47]S. Cliff Liu, Zhao Song, Hengjie Zhang, Lichen Zhang, Tianyi Zhou:
Space-Efficient Interior Point Method, with applications to Linear Programming and Maximum Weight Bipartite Matching. CoRR abs/2009.06106 (2020) - [i46]András Gilyén, Zhao Song, Ewin Tang:
An improved quantum-inspired algorithm for linear regression. CoRR abs/2009.07268 (2020) - [i45]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. CoRR abs/2009.09829 (2020) - [i44]Haotian Jiang, Tarun Kathuria, Yin Tat Lee, Swati Padmanabhan, Zhao Song:
A Faster Interior Point Method for Semidefinite Programming. CoRR abs/2009.10217 (2020) - [i43]Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora:
InstaHide: Instance-hiding Schemes for Private Distributed Learning. CoRR abs/2010.02772 (2020) - [i42]Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora:
TextHide: Tackling Data Privacy in Language Understanding Tasks. CoRR abs/2010.06053 (2020) - [i41]Xiaoxiao Li, Yangsibo Huang, Binghui Peng, Zhao Song, Kai Li:
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery. CoRR abs/2010.11463 (2020) - [i40]Josh Alman, Timothy Chu, Aaron Schild, Zhao Song:
Algorithms and Hardness for Linear Algebra on Geometric Graphs. CoRR abs/2011.02466 (2020) - [i39]Sitan Chen, Zhao Song, Danyang Zhuo:
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization. CoRR abs/2011.11181 (2020) - [i38]Baihe Huang, Zhao Song, Runzhou Tao, Ruizhe Zhang, Danyang Zhuo:
InstaHide's Sample Complexity When Mixing Two Private Images. CoRR abs/2011.11877 (2020)
2010 – 2019
- 2019
- [j5]Maria-Florina Balcan, Yingyu Liang, Zhao Song, David P. Woodruff, Hongyang Zhang:
Non-Convex Matrix Completion and Related Problems via Strong Duality. J. Mach. Learn. Res. 20: 102:1-102:56 (2019) - [c44]Yibo Lin, Zhao Song, Lin F. Yang:
Towards a Theoretical Understanding of Hashing-Based Neural Nets. AISTATS 2019: 127-137 - [c43]Yin Tat Lee, Zhao Song, Qiuyi Zhang:
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time. COLT 2019: 2140-2157 - [c42]Aviad Rubinstein, Saeed Seddighin, Zhao Song, Xiaorui Sun:
Approximation Algorithms for LCS and LIS with Truly Improved Running Times. FOCS 2019: 1121-1145 - [c41]Vasileios Nakos, Zhao Song, Zhengyu Wang:
(Nearly) Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless. FOCS 2019: 1568-1577 - [c40]Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh:
The Limitations of Adversarial Training and the Blind-Spot Attack. ICLR (Poster) 2019 - [c39]Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song:
A Convergence Theory for Deep Learning via Over-Parameterization. ICML 2019: 242-252 - [c38]Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong:
Efficient Symmetric Norm Regression via Linear Sketching. NeurIPS 2019: 828-838 - [c37]Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang:
Total Least Squares Regression in Input Sparsity Time. NeurIPS 2019: 2478-2489 - [c36]