Canaries in the Network. - Danyang Zhuo; Qiao Zhang 001; Xin Yang 017; Vincent Liu 001 (HotNets, 2016)

Number Balancing is as Hard as Minkowski's Theorem and Shortest Vector. - Rebecca Hoberg; Harishchandra Ramadas; Thomas Rothvoss; Xin Yang 017 (IPCO, 2017)

Time-Space Tradeoffs for Learning from Small Test Spaces: Learning Low Degree Polynomial Functions. - Paul Beame; Shayan Oveis Gharan; Xin Yang 017 (Electron. Colloquium Comput. Complex., 2017)

Time-Space Tradeoffs for Learning Finite Functions from Random Evaluations, with Applications to Polynomials. - Paul Beame; Shayan Oveis Gharan; Xin Yang 017 (Electron. Colloquium Comput. Complex., 2018)

A near-optimal algorithm for approximating the John Ellipsoid. - Michael B. Cohen; Ben Cousins; Yin Tat Lee; Xin Yang 017 (COLT, 2019)

Total Least Squares Regression in Input Sparsity Time. - Huaian Diao; Zhao Song 002; David P. Woodruff; Xin Yang 017 (NeurIPS, 2019)

Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound. - Zhao Song 002; Xin Yang 017 (CoRR, 2019)

Sketching Transformed Matrices with Applications to Natural Language Processing. - Yingyu Liang; Zhao Song 002; Mengdi Wang; Lin Yang 011; Xin Yang 017 (AISTATS, 2020)

On the Bias of Reed-Muller Codes over Odd Prime Fields. - Paul Beame; Shayan Oveis Gharan; Xin Yang 017 (SIAM J. Discret. Math., 2020)

Towards Better Understanding of Algorithms and Complexity of Some Learning Problems. - Xin Yang 017 (2020)

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis. - Baihe Huang; Xiaoxiao Li; Zhao Song 002; Xin Yang 017 (ICML, 2021)

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis. - Baihe Huang; Xiaoxiao Li; Zhao Song 002; Xin Yang 017 (CoRR, 2021)

Vertical Federated Learning without Revealing Intersection Membership. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Aonan Zhang; Weihao Gao; Junyuan Xie; Chong Wang 002 (CoRR, 2021)

Label Leakage and Protection in Two-party Split Learning. - Oscar Li; Jiankai Sun; Xin Yang 017; Weihao Gao; Hongyi Zhang; Junyuan Xie; Virginia Smith; Chong Wang 002 (ICLR, 2022)

Differentially private multi-party data release for linear regression. - Ruihan Wu; Xin Yang 017; Yuanshun Yao; Jiankai Sun; Tianyi Liu; Kilian Q. Weinberger; Chong Wang 002 (UAI, 2022)

Label Leakage and Protection from Forward Embedding in Vertical Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Chong Wang 002 (CoRR, 2022)

Differentially Private Label Protection in Split Learning. - Xin Yang 017; Jiankai Sun; Yuanshun Yao; Junyuan Xie; Chong Wang 002 (CoRR, 2022)

Differentially Private AUC Computation in Vertical Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Junyuan Xie; Di Wu; Chong Wang 002 (CoRR, 2022)

Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance. - Zhao Song 002; Xin Yang 017; Yuanyuan Yang 005; Lichen Zhang 003 (CoRR, 2022)

Faster Algorithm for Structured John Ellipsoid Computation. - Zhao Song 002; Xin Yang 017; Yuanyuan Yang 005; Tianyi Zhou 002 (CoRR, 2022)

DPAUC: Differentially Private AUC Computation in Federated Learning. - Jiankai Sun; Xin Yang 017; Yuanshun Yao; Junyuan Xie; Di Wu; Chong Wang 002 (AAAI, 2023)

Label Inference Attack against Split Learning under Regression Setting. - Shangyu Xie; Xin Yang 017; Yuanshun Yao; Tianyi Liu; Taiqing Wang; Jiankai Sun (CoRR, 2023)

Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations. - Mimee Xu; Jiankai Sun; Xin Yang 017; Kevin Yao; Chong Wang 002 (CoRR, 2023)