Peilin Zhong - RankMe

88 papers A* 35A 1B 3Misc 1Journal 46Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Memory Caching: RNNs with Growing Memory. CoRR Ali Behrouz, Zeman Li, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	ATLAS: Learning to Optimally Memorize the Context at Test Time. CoRR Ali Behrouz, Zeman Li, Praneeth Kacham, Majid Daliri, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. ICLR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model. ICML Rachel Cummings, Alessandro Epasto, Jieming Mao, Tamalika Mukherjee, Tingting Ou, Peilin Zhong
2025	J	`jnl`	Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model. CoRR Rachel Cummings, Alessandro Epasto, Jieming Mao, Tamalika Mukherjee, Tingting Ou, Peilin Zhong
2025	—	`conf`	Differentially Private Synthetic Data Release for Topics API Outputs. KDD (2) Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Andrés Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2025	J	`jnl`	Differentially Private Synthetic Data Release for Topics API Outputs. CoRR Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Andrés Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2025	J	`jnl`	It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization. CoRR Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni
2025	J	`jnl`	MS-SSM: A Multi-Scale State Space Model for Efficient Sequence Modeling. CoRR Mahdi Karami, Ali Behrouz, Peilin Zhong, Razvan Pascanu, Vahab Mirrokni
2025	A*	`conf`	Massively Parallel Minimum Spanning Tree in General Metric Spaces. SODA Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Lacki, Vahab Mirrokni, Peilin Zhong
2025	A*	`conf`	Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures. ICML Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy L. Nguyen, David P. Woodruff, Peilin Zhong
2025	J	`jnl`	Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures. CoRR Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy L. Nguyen, David P. Woodruff, Peilin Zhong
2025	J	`jnl`	Nested Learning: The Illusion of Deep Learning Architectures. CoRR Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni
2025	J	`jnl`	PiKE: Adaptive Data Mixing for Multi-Task Learning Under Low Gradient Conflicts. CoRR Zeman Li, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	Retraining with Predicted Hard Labels Provably Increases Model Accuracy. ICML Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
2025	J	`jnl`	TNT: Improving Chunkwise Training for Test-Time Memorization. CoRR Zeman Li, Ali Behrouz, Yuan Deng, Peilin Zhong, Praneeth Kacham, Mahdi Karami, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	Titans: Learning to Memorize at Test Time. CoRR Ali Behrouz, Peilin Zhong, Vahab Mirrokni
2024	J	`jnl`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. CoRR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2024	A*	`conf`	High-Dimensional Geometric Streaming for Nearly Low Rank Data. ICML Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024	J	`jnl`	High-Dimensional Geometric Streaming for Nearly Low Rank Data. CoRR Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong
2024	A*	`conf`	Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. SODA Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
2024	J	`jnl`	Massively Parallel Minimum Spanning Tree in General Metric Spaces. CoRR Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Lacki, Vahab Mirrokni, Peilin Zhong
2024	A*	`conf`	Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond. STOC Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024	J	`jnl`	Optimal Communication for Classic Functions in the Coordinator Model and Beyond. CoRR Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024	A*	`conf`	Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth. SODA Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, Peilin Zhong
2024	J	`jnl`	Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth. CoRR Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, Peilin Zhong
2024	A*	`conf`	Perturb-and-Project: Differentially Private Similarities and Marginals. ICML Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong
2024	J	`jnl`	Perturb-and-Project: Differentially Private Similarities and Marginals. CoRR Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong
2024	A*	`conf`	PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels. ICML Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
2024	J	`jnl`	Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
2023	B	`conf`	Brief Announcement: Streaming Balanced Clustering. SPAA Hossein Esfandiari, Vahab Mirrokni, Peilin Zhong
2023	J	`jnl`	Differentially Private Clustering in Data Streams. CoRR Alessandro Epasto, Tamalika Mukherjee, Peilin Zhong
2023	A	`conf`	Differentially Private Continual Releases of Streaming Frequency Moment Estimations. ITCS Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2023	J	`jnl`	Differentially Private Continual Releases of Streaming Frequency Moment Estimations. CoRR Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2023	J	`jnl`	Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. CoRR Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
2023	B	`conf`	Massively Parallel Tree Embeddings for High Dimensional Spaces. SPAA AmirMohsen Ahanchi, Alexandr Andoni, MohammadTaghi Hajiaghayi, Marina Knittel, Peilin Zhong
2023	J	`jnl`	Measuring Re-identification Risk. CoRR CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andrés Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
2023	J	`jnl`	Measuring Re-identification Risk. Proc. ACM Manag. Data CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
2023	A*	`conf`	Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS David P. Woodruff, Peilin Zhong, Samson Zhou
2023	J	`jnl`	Near-Optimal k-Clustering in the Sliding Window Model. CoRR David P. Woodruff, Peilin Zhong, Samson Zhou
2023	J	`jnl`	PolySketchFormer: Fast Transformers via Sketches for Polynomial Kernels. CoRR Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
2023	A*	`conf`	k-Means Clustering with Distance-Based Privacy. NeurIPS Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
2022	A*	`conf`	Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
2022	J	`jnl`	Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
2022	A*	`conf`	Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. SODA Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
2022	A*	`conf`	Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. SODA Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
2022	A*	`conf`	Massively Parallel k-Means Clustering for Perturbation Resilient Instances. ICML Vincent Cohen-Addad, Vahab S. Mirrokni, Peilin Zhong
2022	A*	`conf`	Near-Optimal Private and Scalable $k$-Clustering. NeurIPS Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
2022	J	`jnl`	Stars: Tera-Scale Graph Building for Clustering and Graph Learning. CoRR CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong
2022	A*	`conf`	Stars: Tera-Scale Graph Building for Clustering and Learning. NeurIPS CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong
2021	A*	`conf`	Almost Linear Time Density Level Set Estimation via DBSCAN. AAAI Hossein Esfandiari, Vahab S. Mirrokni, Peilin Zhong
2021	J	`jnl`	Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. CoRR Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
2021	J	`jnl`	Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. CoRR Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
2021	—	`—`	New Primitives for Tackling Graph Problems and Their Applications in Parallel Computing. Peilin Zhong
2020	J	`jnl`	Average Case Column Subset Selection for Entrywise 𝓁 CoRR Zhao Song, David P. Woodruff, Peilin Zhong
2020	B	`conf`	Connected Components on a PRAM in Log Diameter Time. SPAA Sixue Cliff Liu, Robert E. Tarjan, Peilin Zhong
2020	J	`jnl`	Connected Components on a PRAM in Log Diameter Time. CoRR S. Cliff Liu, Robert E. Tarjan, Peilin Zhong
2020	A*	`conf`	Enhancing Adversarial Defense by k-Winners-Take-All. ICLR Chang Xiao, Peilin Zhong, Changxi Zheng
2020	A*	`conf`	Parallel approximate undirected shortest paths via low hop emulators. STOC Alexandr Andoni, Clifford Stein, Peilin Zhong
2020	A*	`conf`	Planning with General Objective Functions: Going Beyond Total Rewards. NeurIPS Ruosong Wang, Peilin Zhong, Simon S. Du, Ruslan Salakhutdinov, Lin F. Yang
2019	A*	`conf`	Average Case Column Subset Selection for Entrywise 퓁 NeurIPS Zhao Song, David P. Woodruff, Peilin Zhong
2019	A*	`conf`	Efficient Symmetric Norm Regression via Linear Sketching. NeurIPS Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
2019	J	`jnl`	Efficient Symmetric Norm Regression via Linear Sketching. CoRR Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong
2019	A*	`conf`	Log Diameter Rounds Algorithms for 2-Vertex and 2-Edge Connectivity. ICALP Alexandr Andoni, Clifford Stein, Peilin Zhong
2019	J	`jnl`	Log Diameter Rounds Algorithms for 2-Vertex and 2-Edge Connectivity. CoRR Alexandr Andoni, Clifford Stein, Peilin Zhong
2019	J	`jnl`	Parallel Approximate Undirected Shortest Paths Via Low Hop Emulators. CoRR Alexandr Andoni, Clifford Stein, Peilin Zhong
2019	A*	`conf`	Relative Error Tensor Low Rank Approximation. SODA Zhao Song, David P. Woodruff, Peilin Zhong
2019	J	`jnl`	Resisting Adversarial Attacks by k-Winners-Take-All. CoRR Chang Xiao, Peilin Zhong, Changxi Zheng
2019	J	`jnl`	Rethinking Generative Coverage: A Pointwise Guaranteed Approach. CoRR Peilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen, Changxi Zheng
2019	A*	`conf`	Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach. NeurIPS Peilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen, Changxi Zheng
2019	J	`jnl`	Streaming Balanced Clustering. CoRR Hossein Esfandiari, Vahab S. Mirrokni, Peilin Zhong
2019	A*	`conf`	Towards a Zero-One Law for Column Subset Selection. NeurIPS Zhao Song, David P. Woodruff, Peilin Zhong
2018	A*	`conf`	BourGAN: Generative Networks with Metric Embeddings. NeurIPS Chang Xiao, Peilin Zhong, Changxi Zheng
2018	J	`jnl`	BourGAN: Generative Networks with Metric Embeddings. CoRR Chang Xiao, Peilin Zhong, Changxi Zheng
2018	A*	`conf`	Parallel Graph Connectivity in Log Diameter Rounds. FOCS Alexandr Andoni, Zhao Song, Clifford Stein, Zhengyu Wang, Peilin Zhong
2018	J	`jnl`	Parallel Graph Connectivity in Log Diameter Rounds. CoRR Alexandr Andoni, Clifford Stein, Zhao Song, Zhengyu Wang, Peilin Zhong
2018	J	`jnl`	Relative Error Tensor Low Rank Approximation. Electron. Colloquium Comput. Complex. Zhao Song, David P. Woodruff, Peilin Zhong
2018	J	`jnl`	Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to k-Clustering. CoRR Zhao Song, Lin F. Yang, Peilin Zhong
2018	A*	`conf`	Subspace Embedding and Linear Regression with Orlicz Norm. ICML Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong
2018	J	`jnl`	Subspace Embedding and Linear Regression with Orlicz Norm. CoRR Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong
2018	J	`jnl`	Towards a Zero-One Law for Entrywise Low Rank Approximation. CoRR Zhao Song, David P. Woodruff, Peilin Zhong
2017	A*	`conf`	Low rank approximation with entrywise l STOC Zhao Song, David P. Woodruff, Peilin Zhong
2017	J	`jnl`	Relative Error Tensor Low Rank Approximation. CoRR Zhao Song, David P. Woodruff, Peilin Zhong
2016	J	`jnl`	Distributed Low Rank Approximation of Implicit Functions of a Matrix. CoRR David P. Woodruff, Peilin Zhong
2016	A*	`conf`	Distributed low rank approximation of implicit functions of a matrix. ICDE David P. Woodruff, Peilin Zhong
2016	J	`jnl`	Low Rank Approximation with Entrywise ℓ CoRR Zhao Song, David P. Woodruff, Peilin Zhong
2016	A*	`conf`	Optimal principal component analysis in distributed and streaming models. STOC Christos Boutsidis, David P. Woodruff, Peilin Zhong
2014	Misc	`conf`	Deep learning of feature representation with multiple instance learning for medical image analysis. ICASSP Yan Xu, Tao Mo, Qiwei Feng, Peilin Zhong, Maode Lai, Eric I-Chao Chang