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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
![[0000-0001-6566-1473]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-6566-1473")
— Dartmouth College, Department of Mathematics, Hanover, NH, USA (and 1 more) - 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
- Zhao Song 0011 — Defense Innovation Institute, Beijing, China
- Zhao Song 0012 — Southern Medical University, Shenzhen Hospital, China
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2020 – today
- 2024
[c115]Timothy Chu, Zhao Song, Chiwun Yang:
How to Protect Copyright Data in Optimization of Large Language Models? AAAI 2024: 17871-17879- [c114]Zhao Song, Junze Yin, Lichen Zhang:
Solving Attention Kernel Regression Problem via Pre-conditioner. AISTATS 2024: 208-216 - [c113]Zhao Song, Junze Yin, Lichen Zhang, Ruizhe Zhang:
Fast Dynamic Sampling for Determinantal Point Processes. AISTATS 2024: 244-252 - [c112]Lianke Qin, Zhao Song, Ruizhe Zhang:
A General Algorithm for Solving Rank-one Matrix Sensing. AISTATS 2024: 757-765 - [c111]Josh Alman, Zhao Song:
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation. ICLR 2024 - [c110]Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang:
A Sublinear Adversarial Training Algorithm. ICLR 2024 - [c109]Yuzhou Gu, Zhao Song, Junze Yin, Lichen Zhang:
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time. ICLR 2024 - [c108]Jan van den Brand, Zhao Song, Tianyi Zhou:
Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models. ICML 2024 - [c107]Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu:
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis. ICML 2024 - [c106]Zhao Song, Lichen Zhang, Ruizhe Zhang:
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time. ITCS 2024: 93:1-93:15 - [c105]Haotian Jiang, Yin Tat Lee, Zhao Song, Lichen Zhang:
Convex Minimization with Integer Minima in Õ(n4) Time. SODA 2024: 3659-3684 - [i188]Yichuan Deng, Zhao Song, Chiwun Yang:
Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence. CoRR abs/2402.01515 (2024) - [i187]Josh Alman, Zhao Song:
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models. CoRR abs/2402.04497 (2024) - [i186]Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu:
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis. CoRR abs/2402.04520 (2024) - [i185]Yeqi Gao, Zhao Song, Ruizhe Zhang:
Quantum Speedup for Spectral Approximation of Kronecker Products. CoRR abs/2402.07027 (2024) - [i184]Jiuxiang Gu, Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Tianyi Zhou:
Fourier Circuits in Neural Networks: Unlocking the Potential of Large Language Models in Mathematical Reasoning and Modular Arithmetic. CoRR abs/2402.09469 (2024) - [i183]Yichuan Deng, Zhao Song, Chiwun Yang:
Attention is Naturally Sparse with Gaussian Distributed Input. CoRR abs/2404.02690 (2024) - [i182]Zhihang Li, Zhao Song, Weixin Wang, Junze Yin, Zheng Yu:
How to Inverting the Leverage Score Distribution? CoRR abs/2404.13785 (2024) - [i181]Jiuxiang Gu, Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song:
Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond. CoRR abs/2405.03251 (2024) - [i180]Jiuxiang Gu, Yingyu Liang, Heshan Liu, Zhenmei Shi, Zhao Song, Junze Yin:
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers. CoRR abs/2405.05219 (2024) - [i179]Yeqi Gao, Yuzhou Gu, Zhao Song:
Binary Hypothesis Testing for Softmax Models and Leverage Score Models. CoRR abs/2405.06003 (2024) - [i178]Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, Yufa Zhou:
Tensor Attention Training: Provably Efficient Learning of Higher-order Transformers. CoRR abs/2405.16411 (2024) - [i177]Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, Yufa Zhou:
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective. CoRR abs/2405.16418 (2024) - [i176]Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu:
Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models. CoRR abs/2406.03136 (2024) - [i175]Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang:
Toward Infinite-Long Prefix in Transformer. CoRR abs/2406.14036 (2024) - [i174]Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Zhao Song, Han Liu:
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs). CoRR abs/2407.01079 (2024) - [i173]Jiuxiang Gu, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song:
Differential Privacy Mechanisms in Neural Tangent Kernel Regression. CoRR abs/2407.13621 (2024) - [i172]Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, Yufa Zhou:
Differential Privacy of Cross-Attention with Provable Guarantee. CoRR abs/2407.14717 (2024) - [i171]Jiuxiang Gu, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Junwei Yu:
Fast John Ellipsoid Computation with Differential Privacy Optimization. CoRR abs/2408.06395 (2024) - [i170]Chenyang Li, Zhao Song, Zhaoxing Xu, Junze Yin:
Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method. CoRR abs/2408.11267 (2024) - [i169]Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song:
A Tighter Complexity Analysis of SparseGPT. CoRR abs/2408.12151 (2024) - [i168]Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Yufa Zhou:
Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Time. CoRR abs/2408.13233 (2024) - [i167]Xiaoyu Li, Zhao Song, Junwei Yu:
Quantum Speedups for Approximating the John Ellipsoid. CoRR abs/2408.14018 (2024) - [i166]Erzhi Liu, Jerry Yao-Chieh Hu, Alex Daniel Reneau, Zhao Song, Han Liu:
Differentially Private Kernel Density Estimation. CoRR abs/2409.01688 (2024) - 2023
- [c104]Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan:
Smoothed Online Combinatorial Optimization Using Imperfect Predictions. AAAI 2023: 12130-12137 - [c103]Lianke Qin, Zhao Song, Lichen Zhang, Danyang Zhuo:
An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization. AISTATS 2023: 101-156 - [c102]Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava:
A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space. AISTATS 2023: 788-836 - [c101]Yichuan Deng, Yeqi Gao, Zhao Song:
Solving Tensor Low Cycle Rank Approximation. IEEE Big Data 2023: 6-16 - [c100]Lianke Qin, Aravind Reddy, Zhao Song:
Online Adaptive Mahalanobis Distance Estimation. IEEE Big Data 2023: 56-65 - [c99]Lianke Qin, Saayan Mitra, Zhao Song, Yuanyuan Yang, Tianyi Zhou:
Fast Heavy Inner Product Identification Between Weights and Inputs in Neural Network Training. IEEE Big Data 2023: 128-133 - [c98]Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang:
Quartic Samples Suffice for Fourier Interpolation. FOCS 2023: 1414-1425 - [c97]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. ICALP 2023: 88:1-88:14 - [c96]Xiaoxiao Li, Zhao Song, Jiaming Yang:
Federated Adversarial Learning: A Framework with Convergence Analysis. ICML 2023: 19932-19959 - [c95]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML 2023: 22137-22176 - [c94]Zhao Song, Yitan Wang, Zheng Yu, Lichen Zhang:
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability. ICML 2023: 32365-32417 - [c93]Zhao Song, Xin Yang, Yuanyuan Yang, Lichen Zhang:
Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance. ICML 2023: 32418-32462 - [c92]Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang:
A Nearly-Optimal Bound for Fast Regression with ℓ∞ Guarantee. ICML 2023: 32463-32482 - [c91]Josh Alman, Zhao Song:
Fast Attention Requires Bounded Entries. NeurIPS 2023 - [c90]Josh Alman, Jiehao Liang, Zhao Song, Ruizhe Zhang, Danyang Zhuo:
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing. NeurIPS 2023 - [c89]Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco:
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. NeurIPS 2023 - [c88]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. NeurIPS 2023 - [c87]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS 2023 - [c86]Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu:
Towards Multi-Pass Streaming Lower Bounds for Optimal Approximation of Max-Cut. SODA 2023: 878-924 - [c85]Yaonan Jin, Daogao Liu, Zhao Song:
Super-resolution and Robust Sparse Continuous Fourier Transform in Any Constant Dimension: Nearly Linear Time and Sample Complexity. SODA 2023: 4667-4767 - [i165]Zhao Song, Tianyi Zhou:
Faster Sinkhorn's Algorithm with Small Treewidth. CoRR abs/2301.06741 (2023) - [i164]Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang:
A Nearly-Optimal Bound for Fast Regression with 𝓁∞ Guarantee. CoRR abs/2302.00248 (2023) - [i163]Yuzhou Gu, Zhao Song, Junze Yin, Lichen Zhang:
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time. CoRR abs/2302.11068 (2023) - [i162]Josh Alman, Zhao Song:
Fast Attention Requires Bounded Entries. CoRR abs/2302.13214 (2023) - [i161]Yichuan Deng, Zhao Song, Zifan Wang, Han Zhang:
Streaming Kernel PCA Algorithm With Small Space. CoRR abs/2303.04555 (2023) - [i160]Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu:
A Theoretical Analysis Of Nearest Neighbor Search On Approximate Near Neighbor Graph. CoRR abs/2303.06210 (2023) - [i159]Yichuan Deng, Zhihang Li, Zhao Song:
An Improved Sample Complexity for Rank-1 Matrix Sensing. CoRR abs/2303.06895 (2023) - [i158]Lianke Qin, Zhao Song, Ruizhe Zhang:
A General Algorithm for Solving Rank-one Matrix Sensing. CoRR abs/2303.12298 (2023) - [i157]Zhihang Li, Zhao Song, Tianyi Zhou:
Solving Regularized Exp, Cosh and Sinh Regression Problems. CoRR abs/2303.15725 (2023) - [i156]Yeqi Gao, Sridhar Mahadevan, Zhao Song:
An Over-parameterized Exponential Regression. CoRR abs/2303.16504 (2023) - [i155]Jan van den Brand, Zhao Song, Tianyi Zhou:
Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models. CoRR abs/2304.02207 (2023) - [i154]Haotian Jiang, Yin Tat Lee, Zhao Song, Lichen Zhang:
Convex Minimization with Integer Minima in Õ(n4) Time. CoRR abs/2304.03426 (2023) - [i153]Yichuan Deng, Sridhar Mahadevan, Zhao Song:
Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension. CoRR abs/2304.04397 (2023) - [i152]Yichuan Deng, Yeqi Gao, Zhao Song:
Solving Tensor Low Cycle Rank Approximation. CoRR abs/2304.06594 (2023) - [i151]Yichuan Deng, Zhihang Li, Zhao Song:
Attention Scheme Inspired Softmax Regression. CoRR abs/2304.10411 (2023) - [i150]Shuai Li, Zhao Song, Yu Xia, Tong Yu, Tianyi Zhou:
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression. CoRR abs/2304.13276 (2023) - [i149]Yeqi Gao, Zhao Song, Junze Yin:
An Iterative Algorithm for Rescaled Hyperbolic Functions Regression. CoRR abs/2305.00660 (2023) - [i148]Yeqi Gao, Zhao Song, Xin Yang:
Differentially Private Attention Computation. CoRR abs/2305.04701 (2023) - [i147]Zhao Song, Mingquan Ye:
Efficient Asynchronize Stochastic Gradient Algorithm with Structured Data. CoRR abs/2305.08001 (2023) - [i146]Zhao Song, Weixin Wang, Chenbo Yin:
Fast and Efficient Matching Algorithm with Deadline Instances. CoRR abs/2305.08353 (2023) - [i145]Lianke Qin, Zhao Song, Yitan Wang:
Fast Submodular Function Maximization. CoRR abs/2305.08367 (2023) - [i144]Song Bian, Zhao Song, Junze Yin:
Federated Empirical Risk Minimization via Second-Order Method. CoRR abs/2305.17482 (2023) - [i143]Yichuan Deng, Zhao Song, Junze Yin:
Faster Robust Tensor Power Method for Arbitrary Order. CoRR abs/2306.00406 (2023) - [i142]Ritwik Sinha, Zhao Song, Tianyi Zhou:
A Mathematical Abstraction for Balancing the Trade-off Between Creativity and Reality in Large Language Models. CoRR abs/2306.02295 (2023) - [i141]Xiaoxiao Li, Zhao Song, Guangyi Zhang:
Sparse Convolution for Approximate Sparse Instance. CoRR abs/2306.02381 (2023) - [i140]Xiang Chen, Zhao Song, Baocheng Sun, Junze Yin, Danyang Zhuo:
Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis. CoRR abs/2306.03356 (2023) - [i139]Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang:
Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation. CoRR abs/2306.04169 (2023) - [i138]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. CoRR abs/2306.04933 (2023) - [i137]Yichuan Deng, Zhao Song, Lichen Zhang, Ruizhe Zhang:
Efficient Algorithm for Solving Hyperbolic Programs. CoRR abs/2306.07587 (2023) - [i136]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR abs/2306.14048 (2023) - [i135]Yeqi Gao, Zhao Song, Shenghao Xie:
In-Context Learning for Attention Scheme: from Single Softmax Regression to Multiple Softmax Regression via a Tensor Trick. CoRR abs/2307.02419 (2023) - [i134]Lianke Qin, Zhao Song, Yuanyuan Yang:
Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification. CoRR abs/2307.06565 (2023) - [i133]Yuzhou Gu, Zhao Song, Lichen Zhang:
A Nearly-Linear Time Algorithm for Structured Support Vector Machines. CoRR abs/2307.07735 (2023) - [i132]Yeqi Gao, Zhao Song, Xin Yang, Ruizhe Zhang:
Fast Quantum Algorithm for Attention Computation. CoRR abs/2307.08045 (2023) - [i131]Yichuan Deng, Zhihang Li, Sridhar Mahadevan, Zhao Song:
Zero-th Order Algorithm for Softmax Attention Optimization. CoRR abs/2307.08352 (2023) - [i130]Yichuan Deng, Zhao Song, Shenghao Xie:
Convergence of Two-Layer Regression with Nonlinear Units. CoRR abs/2308.08358 (2023) - [i129]Yeqi Gao, Zhao Song, Junze Yin:
GradientCoin: A Peer-to-Peer Decentralized Large Language Models. CoRR abs/2308.10502 (2023) - [i128]Yichuan Deng, Michalis Mamakos, Zhao Song:
Clustered Linear Contextual Bandits with Knapsacks. CoRR abs/2308.10722 (2023) - [i127]Timothy Chu, Zhao Song, Chiwun Yang:
How to Protect Copyright Data in Optimization of Large Language Models? CoRR abs/2308.12247 (2023) - [i126]Zhao Song, Junze Yin, Lichen Zhang:
Solving Attention Kernel Regression Problem via Pre-conditioner. CoRR abs/2308.14304 (2023) - [i125]Lianke Qin, Aravind Reddy, Zhao Song:
Online Adaptive Mahalanobis Distance Estimation. CoRR abs/2309.01030 (2023) - [i124]Zhao Song, Mingquan Ye, Lichen Zhang:
Streaming Semidefinite Programs: O(√n) Passes, Small Space and Fast Runtime. CoRR abs/2309.05135 (2023) - [i123]Yeqi Gao, Zhao Song, Weixin Wang, Junze Yin:
A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time. CoRR abs/2309.07418 (2023) - [i122]Lianke Qin, Zhao Song, Baocheng Sun:
Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network? CoRR abs/2309.07452 (2023) - [i121]Zhao Song, Weixin Wang, Junze Yin:
A Unified Scheme of ResNet and Softmax. CoRR abs/2309.13482 (2023) - [i120]Timothy Chu, Zhao Song, Chiwun Yang:
Fine-tune Language Models to Approximate Unbiased In-context Learning. CoRR abs/2310.03331 (2023) - [i119]Josh Alman, Zhao Song:
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation. CoRR abs/2310.04064 (2023) - [i118]Zhao Song, Chiwun Yang:
An Automatic Learning Rate Schedule Algorithm for Achieving Faster Convergence and Steeper Descent. CoRR abs/2310.11291 (2023) - [i117]Yichuan Deng, Zhao Song, Tianyi Zhou:
Superiority of Softmax: Unveiling the Performance Edge Over Linear Attention. CoRR abs/2310.11685 (2023) - [i116]Yichuan Deng, Zhao Song, Shenghao Xie, Chiwun Yang:
Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights. CoRR abs/2310.12462 (2023) - [i115]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR abs/2310.17157 (2023) - [i114]Zhao Song, Guangyi Xu, Junze Yin:
The Expressibility of Polynomial based Attention Scheme. CoRR abs/2310.20051 (2023) - [i113]Lianke Qin, Saayan Mitra, Zhao Song, Yuanyuan Yang, Tianyi Zhou:
Fast Heavy Inner Product Identification Between Weights and Inputs in Neural Network Training. CoRR abs/2311.11429 (2023) - [i112]Chenyang Li, Zhao Song, Weixin Wang, Chiwun Yang:
A Theoretical Insight into Attack and Defense of Gradient Leakage in Transformer. CoRR abs/2311.13624 (2023) - [i111]Raghav Addanki, Chenyang Li, Zhao Song, Chiwun Yang:
One Pass Streaming Algorithm for Super Long Token Attention Approximation in Sublinear Space. CoRR abs/2311.14652 (2023) - [i110]Zhao Song, Junze Yin, Ruizhe Zhang:
Revisiting Quantum Algorithms for Linear Regressions: Quadratic Speedups without Data-Dependent Parameters. CoRR abs/2311.14823 (2023) - [i109]Zhihang Li, Zhao Song, Zifan Wang, Junze Yin:
Local Convergence of Approximate Newton Method for Two Layer Nonlinear Regression. CoRR abs/2311.15390 (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) - [c84]Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo:
Fast Graph Neural Tangent Kernel via Kronecker Sketching. AAAI 2022: 7033-7041 - [c83]Zhao Song, Ruizhe Zhang:
Hyperbolic Concentration, Anti-Concentration, and Discrepancy. APPROX/RANDOM 2022: 10:1-10:19 - [c82]Lianke Qin, Aravind Reddy, Zhao Song, Zhaozhuo Xu, Danyang Zhuo:
Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations. IEEE Big Data 2022: 115-120 - [c81]Xiaoxiao Li, Zhao Song, Runzhou Tao, Guangyi Zhang:
A Convergence Theory for Federated Average: Beyond Smoothness. IEEE Big Data 2022: 1292-1297 - [c80]