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ORCIDZhao Song 0002
Person information
- affiliation: Institute for Advanced Study at Princeton, NJ, USA
- affiliation: 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 — Duke University, Department of Electrical and Computer Engineering, Durham, NC, USA
- 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
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2020 – today
- 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)- [c58]Jan van den Brand, Binghui Peng, Zhao Song, Omri Weinstein:
Training (Overparametrized) Neural Networks in Near-Linear Time. ITCS 2021: 63:1-63:15 - [i66]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) - [i65]Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao:
Solving Tall Dense SDPs in the Current Matrix Multiplication Time. CoRR abs/2101.08208 (2021) - [i64]Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang:
Symmetric Boolean Factor Analysis with Applications to InstaHide. CoRR abs/2102.01570 (2021) - [i63]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) - [i62]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) - [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. 28: 27 (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:
Breaking the n-Pass Barrier: A Streaming Algorithm for 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]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. NeurIPS 2019: 4739-4750 - [c35]Zhao Song, David P. Woodruff, Peilin Zhong:
Towards a Zero-One Law for Column Subset Selection. NeurIPS 2019: 6120-6131 - [c34]Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song:
On the Convergence Rate of Training Recurrent Neural Networks. NeurIPS 2019: 6673-6685 - [c33]Zhao Song, David P. Woodruff, Peilin Zhong:
Average Case Column Subset Selection for Entrywise 퓁1-Norm Loss. NeurIPS 2019: 10111-10121 - [c32]Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon:
Provable Non-linear Inductive Matrix Completion. NeurIPS 2019: 11435-11445 - [c31]Zhao Song, David P. Woodruff, Peilin Zhong:
Relative Error Tensor Low Rank Approximation. SODA 2019: 2772-2789 - [c30]Vasileios Nakos, Zhao Song:
Stronger l2/l2 compressed sensing; without iterating. STOC 2019: 289-297 - [c29]Michael B. Cohen, Yin Tat Lee, Zhao Song:
Solving linear programs in the current matrix multiplication time. STOC 2019: 938-942 - [i37]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. CoRR abs/1901.04684 (2019) - [i36]Rasmus Kyng, Kyle Luh, Zhao Song:
Four Deviations Suffice for Rank 1 Matrices. CoRR abs/1901.06731 (2019) - [i35]Vasileios Nakos, Zhao Song:
Stronger L2/L2 Compressed Sensing; Without Iterating. CoRR abs/1903.02742 (2019) - [i34]Aviad Rubinstein, Zhao Song:
Reducing approximate Longest Common Subsequence to approximate Edit Distance. CoRR abs/1904.05451 (2019) - [i33]Zhao Song, Wen Sun:
Efficient Model-free Reinforcement Learning in Metric Spaces. CoRR abs/1905.00475 (2019) - [i32]Yin Tat Lee, Zhao Song, Qiuyi Zhang:
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time. CoRR abs/1905.04447 (2019) - [i31]Zhao Song, Xin Yang:
Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound. CoRR abs/1906.03593 (2019) - [i30]Vasileios Nakos, Zhao Song, Zhengyu Wang:
(Nearly) Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless. CoRR abs/1909.11123 (2019) - [i29]Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang:
Total Least Squares Regression in Input Sparsity Time. CoRR abs/1909.12441 (2019) - [i28]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. CoRR abs/1909.13384 (2019) - [i27]Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong:
Efficient Symmetric Norm Regression via Linear Sketching. CoRR abs/1910.01788 (2019) - [i26]Sitan Chen, Jerry Li, Zhao Song:
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments. CoRR abs/1912.07629 (2019) - 2018
- [j4]Sergey Bereg, Binay Bhattacharya, Sandip Das, Tsunehiko Kameda, Priya Ranjan Sinha Mahapatra, Zhao Song:
Optimizing squares covering a set of points. Theor. Comput. Sci. 729: 68-83 (2018) - [c28]David Liau, Zhao Song, Eric Price, Ger Yang:
Stochastic Multi-armed Bandits in Constant Space. AISTATS 2018: 386-394 - [c27]Huaian Diao, Zhao Song, Wen Sun, David P. Woodruff:
Sketching for Kronecker Product Regression and P-splines. AISTATS 2018: 1299-1308 - [c26]Rasmus Kyng, Zhao Song:
A Matrix Chernoff Bound for Strongly Rayleigh Distributions and Spectral Sparsifiers from a few Random Spanning Trees. FOCS 2018: 373-384 - [c25]Alexandr Andoni, Zhao Song, Clifford Stein, Zhengyu Wang, Peilin Zhong:
Parallel Graph Connectivity in Log Diameter Rounds. FOCS 2018: 674-685 - [c24]Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon:
Towards Fast Computation of Certified Robustness for ReLU Networks. ICML 2018: 5273-5282 - [c23]Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon:
Learning Long Term Dependencies via Fourier Recurrent Units. ICML 2018: 5810-5818 - [c22]Ankit Garg, Yin Tat Lee, Zhao Song, Nikhil Srivastava:
A matrix expander Chernoff bound. STOC 2018: 1102-1114 - [r2]Bo Hu, Zhao Song, Martin Ester:
Topic Modeling in Online Social Media, User Features and Social Networks for. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i25]Zhao Song, Lin F. Yang, Peilin Zhong:
Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to k-Clustering. CoRR abs/1802.00459 (2018) - [i24]Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon:
Learning Long Term Dependencies via Fourier Recurrent Units. CoRR abs/1803.06585 (2018) - [i23]Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel:
Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR abs/1804.09699 (2018) - [i22]Alexandr Andoni, Clifford Stein, Zhao Song, Zhengyu Wang, Peilin Zhong:
Parallel Graph Connectivity in Log Diameter Rounds. CoRR abs/1805.03055 (2018) - [i21]Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon:
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. CoRR abs/1805.10477 (2018) - [i20]Michael B. Cohen, Yin Tat Lee, Zhao Song:
Solving Linear Programs in the Current Matrix Multiplication Time. CoRR abs/1810.07896 (2018) - [i19]Rasmus Kyng, Zhao Song:
A Matrix Chernoff Bound for Strongly Rayleigh Distributions and Spectral Sparsifiers from a few Random Spanning Trees. CoRR abs/1810.08345 (2018) - [i18]Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song:
On the Convergence Rate of Training Recurrent Neural Networks. CoRR abs/1810.12065 (2018) - [i17]Zhao Song, David P. Woodruff, Peilin Zhong:
Towards a Zero-One Law for Entrywise Low Rank Approximation. CoRR abs/1811.01442 (2018) - [i16]Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song:
A Convergence Theory for Deep Learning via Over-Parameterization. CoRR abs/1811.03962 (2018) - [i15]Yin Tat Lee, Zhao Song, Santosh S. Vempala:
Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities. CoRR abs/1812.06243 (2018) - [i14]Yibo Lin, Zhao Song, Lin F. Yang:
Towards a Theoretical Understanding of Hashing-Based Neural Nets. CoRR abs/1812.10244 (2018) - [i13]Zhao Song, David P. Woodruff, Peilin Zhong:
Relative Error Tensor Low Rank Approximation. Electron. Colloquium Comput. Complex. 25: 103 (2018) - 2017
- [c21]Eric Price, Zhao Song, David P. Woodruff:
Fast Regression with an $ell_infty$ Guarantee. ICALP 2017: 59:1-59:14 - [c20]Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon:
Recovery Guarantees for One-hidden-layer Neural Networks. ICML 2017: 4140-4149 - [c19]Zhao Song, David P. Woodruff, Peilin Zhong:
Low rank approximation with entrywise l1-norm error. STOC 2017: 688-701 - [i12]Zhao Song, David P. Woodruff, Peilin Zhong:
Relative Error Tensor Low Rank Approximation. CoRR abs/1704.08246 (2017) - [i11]Eric Price, Zhao Song, David P. Woodruff:
Fast Regression with an $\ell_\infty$ Guarantee. CoRR abs/1705.10723 (2017) - [i10]Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon:
Recovery Guarantees for One-hidden-layer Neural Networks. CoRR abs/1706.03175 (2017) - [i9]Kai Zhong, Zhao Song, Inderjit S. Dhillon:
Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels. CoRR abs/1711.03440 (2017) - [i8]David Liau, Eric Price, Zhao Song, Ger Yang:
Stochastic Multi-armed Bandits in Constant Space. CoRR abs/1712.09007 (2017) - [i7]Huaian Diao, Zhao Song, Wen Sun, David P. Woodruff:
Sketching for Kronecker Product Regression and P-splines. CoRR abs/1712.09473 (2017) - 2016
- [j3]Ankit Singh Rawat, Zhao Song, Alexandros G. Dimakis, Anna Gál:
Batch Codes Through Dense Graphs Without Short Cycles. IEEE Trans. Inf. Theory 62(4): 1592-1604 (2016) - [c18]Xue Chen, Daniel M. Kane, Eric Price, Zhao Song:
Fourier-Sparse Interpolation without a Frequency Gap. FOCS 2016: 741-750 - [c17]Ruohan Zhang, Zhao Song:
Maximum Sustainable Yield Problem for Robot Foraging and Construction System. IJCAI 2016: 2725-2731 - [c16]Zhao Song, David P. Woodruff, Huan Zhang:
Sublinear Time Orthogonal Tensor Decomposition. NIPS 2016: 793-801 - [c15]Ilya P. Razenshteyn, Zhao Song, David P. Woodruff:
Weighted low rank approximations with provable guarantees. STOC 2016: 250-263 - [c14]Aritra Banik, Binay K. Bhattacharya, Sandip Das, Tsunehiko Kameda, Zhao Song:
The p-Center Problem in Tree Networks Revisited. SWAT 2016: 6:1-6:15 - [i6]Aritra Banik, Binay K. Bhattacharya, Sandip Das, Tsunehiko Kameda, Zhao Song:
The $p$-Center Problem in Tree Networks Revisited. CoRR abs/1604.07535 (2016) - [i5]Eric Price, Zhao Song:
A Robust Sparse Fourier Transform in the Continuous Setting. CoRR abs/1609.00896 (2016) - [i4]Xue Chen, Daniel M. Kane, Eric Price, Zhao Song:
Fourier-sparse interpolation without a frequency gap. CoRR abs/1609.01361 (2016) - [i3]Zhao Song, David P. Woodruff, Peilin Zhong:
Low Rank Approximation with Entrywise ℓ1-Norm Error. CoRR abs/1611.00898 (2016) - 2015
- [j2]Binay Bhattacharya, Tsunehiko Kameda, Zhao Song:
Minmax regret 1-center algorithms for path/tree/unicycle/cactus networks. Discret. Appl. Math. 195: 18-30 (2015) - [c13]Ruohan Zhang, Zhao Song, Dana H. Ballard:
Global Policy Construction in Modular Reinforcement Learning. AAAI 2015: 4226-4227 - [c12]Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis:
Novel power grid reduction method based on L1 regularization. DAC 2015: 93:1-93:6 - [c11]Eric Price, Zhao Song:
A Robust Sparse Fourier Transform in the Continuous Setting. FOCS 2015: 583-600 - [c10]Ankit Singh Rawat, Zhao Song, Alexandros G. Dimakis, Anna Gál:
Batch codes through dense graphs without short cycles. ISIT 2015: 1477-1481 - 2014
- [j1]Binay K. Bhattacharya, Tsunehiko Kameda, Zhao Song:
A Linear Time Algorithm for Computing Minmax Regret 1-Median on a Tree Network. Algorithmica 70(1): 2-21 (2014) - [c9]Zhao Song, Wen Sun:
Probabilistic recharging model in uncertain environments. AAMAS 2014: 1343-1344 - [c8]Binay K. Bhattacharya, Sandip Das, Tsunehiko Kameda, Priya Ranjan Sinha Mahapatra, Zhao Song:
Optimizing Squares Covering a Set of Points. COCOA 2014: 37-52 - [c7]Binay K. Bhattacharya, Minati De, Tsunehiko Kameda, Sasanka Roy, Vladyslav Sokol, Zhao Song:
Back-Up 2-Center on a Path/Tree/Cycle/Unicycle. COCOON 2014: 417-428 - [c6]Binay K. Bhattacharya, Tsunehiko Kameda, Zhao Song:
Improved Minmax Regret 1-Center Algorithms for Cactus Networks with c Cycles. LATIN 2014: 330-341 - [r1]Bo Hu, Zhao Song, Martin Ester:
Topic Modeling in Online Social Media, User Features, and Social Networks for. Encyclopedia of Social Network Analysis and Mining 2014: 2178-2191 - [i2]Alexandros G. Dimakis, Anna Gál, Ankit Singh Rawat, Zhao Song:
Batch Codes through Dense Graphs without Short Cycles. CoRR abs/1410.2920 (2014) - [i1]Alexandros G. Dimakis, Anna Gál, Ankit Singh Rawat, Zhao Song:
Batch Codes through Dense Graphs without Short Cycles. Electron. Colloquium Comput. Complex. 21: 127 (2014) - 2013
- [c5]Zhao Song, Yuke Zhu:
Graphical Model-Based Learning in High Dimensional Feature Spaces. AAAI 2013 - [c4]