| 2026 | ICALP | Computing Flows in Subquadratic Space. | Jan van den Brand, Zhao Song, Albert Weng |
| 2026 | ISCAS | A 56Gb/s PAM-4 Transmitter with Robust DCC and Unsegmented Voltage-Mode Driver Achieving Wide-Coefficient-Tuning-Range FFE in 65nm CMOS. | Lihong Yang, Zhongji Zhang, Xiaoteng Zhao, Zhao Song, Zixing Luo, Zhangming Zhu |
| 2026 | WACV | T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation. | Yubin Chen, Xuyang Guo, Zhenmei Shi, Zhao Song, Jiahao Zhang |
| 2026 | SODA | L | Honghao Lin, Zhao Song, David P. Woodruff, Shenghao Xie, Samson Zhou |
| 2025 | AAAI | LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers. | Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li, Yifan Gong, Kai Zhang, Hao Tan, Jason Kuen, Henghui Ding, Zhihao Shu, Wei Niu, Pu Zhao, Yanzhi Wang, Jiuxiang Gu |
| 2025 | AAAI | Numerical Pruning for Efficient Autoregressive Models. | Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Jing Liu, Ruiyi Zhang, Ryan A. Rossi, Hao Tan, Tong Yu, Xiang Chen, Yufan Zhou, Tong Sun, Pu Zhao, Yanzhi Wang, Jiuxiang Gu |
| 2025 | AISTATS | Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent. | Bo Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song |
| 2025 | AISTATS | An Iterative Algorithm for Rescaled Hyperbolic Functions Regression. | Yeqi Gao, Zhao Song, Junze Yin |
| 2025 | AISTATS | Looped ReLU MLPs May Be All You Need as Practical Programmable Computers. | Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Yufa Zhou |
| 2025 | AISTATS | When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time? | Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song |
| 2025 | AISTATS | Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs. | Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Tianyi Zhou |
| 2025 | CIKM | Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling. | Yang Cao, Bo Chen, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan |
| 2025 | EMNLP | Circuit Complexity Bounds for RoPE-based Transformer Architecture. | Bo Chen, Xiaoyu Li, Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Jiahao Zhang |
| 2025 | EMNLP | Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers. | Yingyu Liang, Heshan Liu, Zhenmei Shi, Zhao Song, Zhuoyan Xu, Jiale Zhao, Zhen Zhuang |
| 2025 | EMNLP | Towards Infinite-Long Prefix in Transformer. | Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang |
| 2025 | ICCV | Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective. | Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Yufa Zhou |
| 2025 | ICDM | Fast Sampling for Privacy-Preserving Lazy Multiplicative Weight Update. | Xiaoyu Li, Zhao Song, Jiale Zhao |
| 2025 | ICLR | Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation. | Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang |
| 2025 | ICLR | Faster Algorithms for Structured Linear and Kernel Support Vector Machines. | Yuzhou Gu, Zhao Song, Lichen Zhang |
| 2025 | ICLR | Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models. | Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu |
| 2025 | ICLR | Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency. | Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu |
| 2025 | ICLR | Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix. | Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou |
| 2025 | ICML | Discrepancy Minimization in Input-Sparsity Time. | Yichuan Deng, Xiaoyu Li, Zhao Song, Omri Weinstein |
| 2025 | ICML | Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities. | Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song |
| 2025 | ICML | Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies. | Yuefan Cao, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Jiahao Zhang |
| 2025 | ICML | On Differential Privacy for Adaptively Solving Search Problems via Sketching. | Shiyuan Feng, Ying Feng, George Zhaoqi Li, Zhao Song, David P. Woodruff, Lichen Zhang |
| 2025 | ICML | Binary Hypothesis Testing for Softmax Models and Leverage Score Models. | Yuzhou Gu, Zhao Song, Junze Yin |
| 2025 | ICML | Deterministic Sparse Fourier Transform for Continuous Signals with Frequency Gap. | Xiaoyu Li, Zhao Song, Shenghao Xie |
| 2025 | ICML | In-Context Deep Learning via Transformer Models. | Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu |
| 2025 | IECON | A Novel PHIL System with (almost) Ideal Delay Compensation for Grid Impedance Emulation. | Zhao Song, Christoph M. Hackl |
| 2025 | KDD | The Expressibility of Polynomial based Attention Scheme. | Zhao Song, Chongxi Wang, Guangyi Xu, Junze Yin |
| 2025 | WACV | Differential Privacy Mechanisms in Neural Tangent Kernel Regression. | Jiuxiang Gu, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song |
| 2025 | UAI | NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism. | Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Xugang Ye |
| 2025 | UAI | A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time. | Yeqi Gao, Zhao Song, Weixin Wang, Junze Yin |
| 2025 | UAI | Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory. | Jiehao Liang, Zhao Song, Zhaozhuo Xu, Junze Yin, Danyang Zhuo |
| 2024 | AAAI | How to Protect Copyright Data in Optimization of Large Language Models? | Timothy Chu, Zhao Song, Chiwun Yang |
| 2024 | AISTATS | Fast Dynamic Sampling for Determinantal Point Processes. | Zhao Song, Junze Yin, Lichen Zhang, Ruizhe Zhang |
| 2024 | AISTATS | Solving Attention Kernel Regression Problem via Pre-conditioner. | Zhao Song, Junze Yin, Lichen Zhang |
| 2024 | AISTATS | A General Algorithm for Solving Rank-one Matrix Sensing. | Lianke Qin, Zhao Song, Ruizhe Zhang |
| 2024 | CLOUD | Vista: Machine Learning based Database Performance Troubleshooting Framework in Amazon RDS. | Vikramank Y. Singh, Zhao Song, Balakrishnan (Murali) Narayanaswamy, Kapil Eknath Vaidya, Tim Kraska |
| 2024 | ICLR | How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation. | Josh Alman, Zhao Song |
| 2024 | ICLR | A Sublinear Adversarial Training Algorithm. | Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang |
| 2024 | ICLR | Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time. | Yuzhou Gu, Zhao Song, Junze Yin, Lichen Zhang |
| 2024 | ICML | Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models. | Jan van den Brand, Zhao Song, Tianyi Zhou |
| 2024 | ICML | On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis. | Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu |
| 2024 | SODA | Convex Minimization with Integer Minima in | Haotian Jiang, Yin Tat Lee, Zhao Song, Lichen Zhang |
| 2024 | UAI | On Convergence of Federated Averaging Langevin Dynamics. | Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin |
| 2023 | AAAI | Smoothed Online Combinatorial Optimization Using Imperfect Predictions. | Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan |
| 2023 | AAAI | Emergence of Punishment in Social Dilemma with Environmental Feedback. | Zhen Wang, Zhao Song, Chen Shen, Shuyue Hu |
| 2023 | AISTATS | An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization. | Lianke Qin, Zhao Song, Lichen Zhang, Danyang Zhuo |
| 2023 | AISTATS | A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space. | Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava |
| 2023 | FOCS | Quartic Samples Suffice for Fourier Interpolation. | Zhao Song, Baocheng Sun, Omri Weinstein, Ruizhe Zhang |
| 2023 | ICALP | Space-Efficient Interior Point Method, with Applications to Linear Programming and Maximum Weight Bipartite Matching. | S. Cliff Liu, Zhao Song, Hengjie Zhang, Lichen Zhang, Tianyi Zhou |
| 2023 | ICASSP | VPPT: Visual Pre-Trained Prompt Tuning Framework for Few-Shot Image Classification. | Zhao Song, Ke Yang, Naiyang Guan, Junjie Zhu, Peng Qiao, Qingyong Hu |
| 2023 | ICML | Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance. | Zhao Song, Xin Yang, Yuanyuan Yang, Lichen Zhang |
| 2023 | ICML | Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability. | Zhao Song, Yitan Wang, Zheng Yu, Lichen Zhang |
| 2023 | ICML | A Nearly-Optimal Bound for Fast Regression with ℓ | Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang |
| 2023 | ICML | Federated Adversarial Learning: A Framework with Convergence Analysis. | Xiaoxiao Li, Zhao Song, Jiaming Yang |
| 2023 | ICML | Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. | Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher R, Beidi Chen |
| 2023 | SODA | Towards Multi-Pass Streaming Lower Bounds for Optimal Approximation of Max-Cut. | Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu |
| 2023 | SODA | Super-resolution and Robust Sparse Continuous Fourier Transform in Any Constant Dimension: Nearly Linear Time and Sample Complexity. | Yaonan Jin, Daogao Liu, Zhao Song |
| 2022 | AAAI | Fast Graph Neural Tangent Kernel via Kronecker Sketching. | Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo |
| 2022 | FOCS | Solving SDP Faster: A Robust IPM Framework and Efficient Implementation. | Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang |
| 2022 | ICLR | Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. | Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher R |
| 2022 | ICML | Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning. | Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher R |
| 2022 | ICML | Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis. | Alexander Munteanu, Simon Omlor, Zhao Song, David P. Woodruff |
| 2022 | ICML | One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes. | Aravind Reddy, Ryan A. Rossi, Zhao Song, Anup B. Rao, Tung Mai, Nedim Lipka, Gang Wu, Eunyee Koh, Nesreen K. Ahmed |
| 2022 | ICML | FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers. | Abishek Sankararaman, Balakrishnan Narayanaswamy, Vikramank Y. Singh, Zhao Song |
| 2021 | ICALP | Near-Optimal Two-Pass Streaming Algorithm for Sampling Random Walks over Directed Graphs. | Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu |
| 2021 | ICLR | On InstaHide, Phase Retrieval, and Sparse Matrix Factorization. | Sitan Chen, Xiaoxiao Li, Zhao Song, Danyang Zhuo |
| 2021 | ICLR | MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. | Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher R |
| 2021 | ICML | Fast Sketching of Polynomial Kernels of Polynomial Degree. | Zhao Song, David P. Woodruff, Zheng Yu, Lichen Zhang |
| 2021 | ICML | Oblivious Sketching-based Central Path Method for Linear Programming. | Zhao Song, Zheng Yu |
| 2021 | ICML | FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis. | Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang |
| 2021 | STOC | Almost optimal super-constant-pass streaming lower bounds for reachability. | Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu |
| 2021 | STOC | Minimum cost flows, MDPs, and ℓ | Jan van den Brand, Yin Tat Lee, Yang P. Liu, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang |
| 2021 | STOC | A faster algorithm for solving general LPs. | Shunhua Jiang, Zhao Song, Omri Weinstein, Hengjie Zhang |
| 2021 | UAI | When is particle filtering efficient for planning in partially observed linear dynamical systems? | Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu |
| 2020 | AISTATS | Sketching Transformed Matrices with Applications to Natural Language Processing. | Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang |
| 2020 | EMNLP | TextHide: Tackling Data Privacy for Language Understanding Tasks. | Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora |
| 2020 | FOCS | Algorithms and Hardness for Linear Algebra on Geometric Graphs. | Josh Alman, Timothy Chu, Aaron Schild, Zhao Song |
| 2020 | FOCS | Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. | Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang |
| 2020 | FOCS | A Faster Interior Point Method for Semidefinite Programming. | Haotian Jiang, Tarun Kathuria, Yin Tat Lee, Swati Padmanabhan, Zhao Song |
| 2020 | ICML | InstaHide: Instance-hiding Schemes for Private Distributed Learning. | Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora |
| 2020 | ICML | Meta-learning for Mixed Linear Regression. | Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh |
| 2020 | ICML | Non-Autoregressive Neural Text-to-Speech. | Kainan Peng, Wei Ping, Zhao Song, Kexin Zhao |
| 2020 | ICML | WaveFlow: A Compact Flow-based Model for Raw Audio. | Wei Ping, Kainan Peng, Kexin Zhao, Zhao Song |
| 2020 | SODA | Reducing approximate Longest Common Subsequence to approximate Edit Distance. | Aviad Rubinstein, Zhao Song |
| 2020 | STOC | Solving tall dense linear programs in nearly linear time. | Jan van den Brand, Yin Tat Lee, Aaron Sidford, Zhao Song |
| 2020 | STOC | Learning mixtures of linear regressions in subexponential time via Fourier moments. | Sitan Chen, Jerry Li, Zhao Song |
| 2020 | STOC | An improved cutting plane method for convex optimization, convex-concave games, and its applications. | Haotian Jiang, Yin Tat Lee, Zhao Song, Sam Chiu-wai Wong |
| 2019 | AISTATS | Towards a Theoretical Understanding of Hashing-Based Neural Nets. | Yibo Lin, Zhao Song, Lin F. Yang |
| 2019 | COLT | Solving Empirical Risk Minimization in the Current Matrix Multiplication Time. | Yin Tat Lee, Zhao Song, Qiuyi Zhang |
| 2019 | FOCS | (Nearly) Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless. | Vasileios Nakos, Zhao Song, Zhengyu Wang |
| 2019 | FOCS | Approximation Algorithms for LCS and LIS with Truly Improved Running Times. | Aviad Rubinstein, Saeed Seddighin, Zhao Song, Xiaorui Sun |
| 2019 | ICLR | The Limitations of Adversarial Training and the Blind-Spot Attack. | Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh |
| 2019 | ICML | A Convergence Theory for Deep Learning via Over-Parameterization. | Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song |
| 2019 | ICML | Revisiting the Softmax Bellman Operator: New Benefits and New Perspective. | Zhao Song, Ronald Parr, Lawrence Carin |
| 2019 | SODA | Relative Error Tensor Low Rank Approximation. | Zhao Song, David P. Woodruff, Peilin Zhong |
| 2019 | STOC | Solving linear programs in the current matrix multiplication time. | Michael B. Cohen, Yin Tat Lee, Zhao Song |
| 2019 | STOC | Stronger l | Vasileios Nakos, Zhao Song |
| 2018 | AISTATS | Sketching for Kronecker Product Regression and P-splines. | Huaian Diao, Zhao Song, Wen Sun, David P. Woodruff |
| 2018 | AISTATS | Stochastic Multi-armed Bandits in Constant Space. | David Liau, Zhao Song, Eric Price, Ger Yang |
| 2018 | FOCS | Parallel Graph Connectivity in Log Diameter Rounds. | Alexandr Andoni, Zhao Song, Clifford Stein, Zhengyu Wang, Peilin Zhong |
| 2018 | FOCS | A Matrix Chernoff Bound for Strongly Rayleigh Distributions and Spectral Sparsifiers from a few Random Spanning Trees. | Rasmus Kyng, Zhao Song |
| 2018 | ICML | Towards Fast Computation of Certified Robustness for ReLU Networks. | Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon |
| 2018 | ICML | Learning Long Term Dependencies via Fourier Recurrent Units. | Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon |
| 2018 | STOC | A matrix expander Chernoff bound. | Ankit Garg, Yin Tat Lee, Zhao Song, Nikhil Srivastava |
| 2017 | ICALP | Fast Regression with an $ell_infty$ Guarantee. | Eric Price, Zhao Song, David P. Woodruff |
| 2017 | ICML | Recovery Guarantees for One-hidden-layer Neural Networks. | Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon |
| 2017 | STOC | Low rank approximation with entrywise l | Zhao Song, David P. Woodruff, Peilin Zhong |
| 2016 | AISTATS | Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. | Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin |
| 2016 | FOCS | Fourier-Sparse Interpolation without a Frequency Gap. | Xue Chen, Daniel M. Kane, Eric Price, Zhao Song |
| 2016 | IJCAI | Maximum Sustainable Yield Problem for Robot Foraging and Construction System. | Ruohan Zhang, Zhao Song |
| 2016 | STOC | Weighted low rank approximations with provable guarantees. | Ilya P. Razenshteyn, Zhao Song, David P. Woodruff |
| 2015 | AAAI | Global Policy Construction in Modular Reinforcement Learning. | Ruohan Zhang, Zhao Song, Dana H. Ballard |
| 2015 | DAC | Novel power grid reduction method based on L1 regularization. | Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis |
| 2015 | FOCS | A Robust Sparse Fourier Transform in the Continuous Setting. | Eric Price, Zhao Song |
| 2015 | ISIT | Batch codes through dense graphs without short cycles. | Ankit Singh Rawat, Zhao Song, Alexandros G. Dimakis, Anna Gl |
| 2014 | COCOA | Optimizing Squares Covering a Set of Points. | Binay K. Bhattacharya, Sandip Das, Tsunehiko Kameda, Priya Ranjan Sinha Mahapatra, Zhao Song |
| 2014 | COCOON | Back-Up 2-Center on a Path/Tree/Cycle/Unicycle. | Binay K. Bhattacharya, Minati De, Tsunehiko Kameda, Sasanka Roy, Vladyslav Sokol, Zhao Song |
| 2014 | LATIN | Improved Minmax Regret 1-Center Algorithms for Cactus Networks with c Cycles. | Binay K. Bhattacharya, Tsunehiko Kameda, Zhao Song |
| 2013 | AAAI | Graphical Model-Based Learning in High Dimensional Feature Spaces. | Zhao Song, Yuke Zhu |
| 2013 | IROS | Sustainable robot foraging: Adaptive fine-grained multi-robot task allocation for maximum sustainable yield of biological resources. | Zhao Song, Richard T. Vaughan |
| 2013 | ISIT | PREMIER - PRobabilistic error-correction using Markov inference in errored reads. | Xin Yin, Zhao Song, Karin S. Dorman, Aditya Ramamoorthy |
| 2012 | AAMAS | MO-LOST: adaptive ant trail untangling in multi-objective multi-colony robot foraging. | Zhao Song, Seyed Abbas Sadat, Richard T. Vaughan |
| 2012 | CISS | A Bayesian max-product EM algorithm for reconstructing structured sparse signals. | Zhao Song, Aleksandar Dogandzic |
| 2012 | ISAAC | Computing Minmax Regret 1-Median on a Tree Network with Positive/Negative Vertex Weights. | Binay K. Bhattacharya, Tsunehiko Kameda, Zhao Song |