Rajesh Jayaram

92 papers A* 34Journal 55Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Chamfer-Linkage for Hierarchical Agglomerative Clustering. CoRR Kishen N. Gowda, Willem Fletcher, MohammadHossein Bateni, Laxman Dhulipala, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2026	J	`jnl`	JAG: Joint Attribute Graphs for Filtered Nearest Neighbor Search. CoRR Haike Xu, Guy E. Blelloch, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, Jakub Lacki
2026	J	`jnl`	PiPNN: Ultra-Scalable Graph-Based Nearest Neighbor Indexing. CoRR Tobias Rubel, Richard Wen, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, Jakub Lacki
2025	A*	`conf`	Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair. FOCS Lorenzo Beretta, Vincent Cohen-Addad, Rajesh Jayaram, Erik Waingarten
2025	J	`jnl`	Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair. CoRR Lorenzo Beretta, Vincent Cohen-Addad, Rajesh Jayaram, Erik Waingarten
2025	J	`jnl`	CRISP: Clustering Multi-Vector Representations for Denoising and Pruning. CoRR João Veneroso, Rajesh Jayaram, Jinmeng Rao, Gustavo Hernández Ábrego, Majid Hadian, Daniel Cer
2025	J	`jnl`	Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe. CoRR Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix X. Yu, Sanjiv Kumar
2025	A*	`conf`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. SODA Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
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`	Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams. COLT Ainesh Bakshi, Vincent Cohen-Addad, Rajesh Jayaram, Sam Hopkins, Silvio Lattanzi
2025	J	`jnl`	Parallel Hierarchical Agglomerative Clustering in Low Dimensions. CoRR MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2025	A*	`conf`	Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. ICML Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
2025	J	`jnl`	Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. CoRR Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
2025	J	`jnl`	Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search. Proc. VLDB Endow. Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram, Jakub Lacki
2024	A*	`conf`	Data-Dependent LSH for the Earth Mover's Distance. STOC Rajesh Jayaram, Erik Waingarten, Tian Zhang
2024	J	`jnl`	Data-Dependent LSH for the Earth Mover's Distance. CoRR Rajesh Jayaram, Erik Waingarten, Tian Zhang
2024	A*	`conf`	Dynamic PageRank: Algorithms and Lower Bounds. ICALP Rajesh Jayaram, Jakub Lacki, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski
2024	J	`jnl`	Dynamic PageRank: Algorithms and Lower Bounds. CoRR Rajesh Jayaram, Jakub Lacki, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski
2024	A*	`conf`	Efficient Centroid-Linkage Clustering. NeurIPS Mohammad Hossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2024	J	`jnl`	Efficient Centroid-Linkage Clustering. CoRR MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2024	A*	`conf`	Fully Dynamic Consistent SODA Jakub Lacki, Bernhard Haeupler, Christoph Grunau, Rajesh Jayaram, Václav Rozhon
2024	A*	`conf`	HyperAttention: Long-context Attention in Near-Linear Time. ICLR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2024	J	`jnl`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. CoRR Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
2024	A*	`conf`	It's Hard to HAC Average Linkage! ICALP MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2024	J	`jnl`	It's Hard to HAC with Average Linkage! CoRR MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
2024	A*	`conf`	MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding. NeurIPS Laxman Dhulipala, Majid Hadian, Rajesh Jayaram, Jason Lee, Vahab Mirrokni
2024	J	`jnl`	MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings. CoRR Laxman Dhulipala, Majid Hadian, Rajesh Jayaram, Jason Lee, Vahab Mirrokni
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`	Metric Clustering and MST with Strong and Weak Distance Oracles. COLT MohammadHossein Bateni, Prathamesh Dharangutte, Rajesh Jayaram, Chen Wang
2024	J	`jnl`	Streaming Algorithms with Few State Changes. CoRR Rajesh Jayaram, David P. Woodruff, Samson Zhou
2024	J	`jnl`	Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data Rajesh Jayaram, David P. Woodruff, Samson Zhou
2024	J	`jnl`	Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search. CoRR Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram, Jakub Lacki
2023	J	`jnl`	A Near-Linear Time Algorithm for the Chamfer Distance. CoRR Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	J	`jnl`	A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. CoRR Ainesh Bakshi, Vincent Cohen-Addad, Samuel B. Hopkins, Rajesh Jayaram, Silvio Lattanzi
2023	J	`jnl`	Fully Dynamic Consistent k-Center Clustering. CoRR Jakub Lacki, Bernhard Haeupler, Christoph Grunau, Václav Rozhon, Rajesh Jayaram
2023	J	`jnl`	HyperAttention: Long-context Attention in Near-Linear Time. CoRR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2023	J	`jnl`	Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. CoRR Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
2023	J	`jnl`	Metric Clustering and MST with Strong and Weak Distance Oracles. CoRR MohammadHossein Bateni, Prathamesh Dharangutte, Rajesh Jayaram, Chen Wang
2023	A*	`conf`	Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	A*	`conf`	Optimal Fully Dynamic SODA MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger, Rajesh Jayaram, Vahab Mirrokni, Andreas Wiese
2023	J	`jnl`	Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries. CoRR MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger, Rajesh Jayaram, Vahab Mirrokni, Andreas Wiese
2023	A*	`conf`	Streaming Euclidean MST to a Constant Factor. STOC Xi Chen, Vincent Cohen-Addad, Rajesh Jayaram, Amit Levi, Erik Waingarten
2023	J	`jnl`	Technical Perspective: Optimal Algorithms for Multiway Search on Partial Orders. SIGMOD Rec. Rajesh Jayaram
2023	J	`jnl`	Towards Optimal Moment Estimation in Streaming and Distributed Models. ACM Trans. Algorithms Rajesh Jayaram, David P. Woodruff
2022	J	`jnl`	A Framework for Adversarially Robust Streaming Algorithms. J. ACM Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev
2022	J	`jnl`	Adore: Differentially Oblivious Relational Database Operators. CoRR Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu
2022	J	`jnl`	Counting the Answers to a Query. SIGMOD Rec. Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2022	J	`jnl`	Differentially Oblivious Relational Database Operators. Proc. VLDB Endow. Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu
2022	A*	`conf`	New streaming algorithms for high dimensional EMD and MST. STOC Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten
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
2022	J	`jnl`	Streaming Euclidean MST to a Constant Factor. CoRR Vincent Cohen-Addad, Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten
2022	A*	`conf`	Truly Perfect Samplers for Data Streams and Sliding Windows. PODS Rajesh Jayaram, David P. Woodruff, Samson Zhou
2021	J	`jnl`	#NFA Admits an FPRAS: Efficient Enumeration, Counting, and Uniform Generation for Logspace Classes. J. ACM Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2021	J	`jnl`	A Framework for Adversarially Robust Streaming Algorithms. SIGMOD Rec. Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev
2021	A*	`conf`	A polynomial-time approximation algorithm for counting words accepted by an NFA (invited paper). STOC Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2021	—	`conf`	An Optimal Algorithm for Triangle Counting in the Stream. APPROX-RANDOM Rajesh Jayaram, John Kallaugher
2021	J	`jnl`	An Optimal Algorithm for Triangle Counting. CoRR Rajesh Jayaram, John Kallaugher
2021	A*	`conf`	In-Database Regression in Input Sparsity Time. ICML Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye
2021	J	`jnl`	In-Database Regression in Input Sparsity Time. CoRR Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye
2021	A*	`conf`	Learning and testing junta distributions with sub cube conditioning. COLT Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten
2021	J	`jnl`	New Streaming Algorithms for High Dimensional EMD and MST. CoRR Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten
2021	J	`jnl`	Optimal Fully Dynamic k-Centers Clustering. CoRR MohammadHossein Bateni, Hossein Esfandiari, Rajesh Jayaram, Vahab S. Mirrokni
2021	J	`jnl`	Perfect L SIAM J. Comput. Rajesh Jayaram, David P. Woodruff
2021	—	`—`	Sketching and Sampling Algorithms for High-Dimensional Data. Rajesh Jayaram
2021	J	`jnl`	Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR Rajesh Jayaram, David P. Woodruff, Samson Zhou
2021	A*	`conf`	When is approximate counting for conjunctive queries tractable? STOC Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2020	A*	`conf`	A Framework for Adversarially Robust Streaming Algorithms. PODS Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev
2020	J	`jnl`	A Framework for Adversarially Robust Streaming Algorithms. CoRR Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev
2020	J	`jnl`	An FPRAS and Polynomial-Time Uniform Sampler for Tree Automata. CoRR Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2020	J	`jnl`	Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. SIGMOD Rec. Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2020	J	`jnl`	Learning and Testing Junta Distributions with Subcube Conditioning. CoRR Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten
2020	A*	`conf`	Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. ICLR Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang
2020	J	`jnl`	Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. CoRR Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang
2020	A*	`conf`	Testing Positive Semi-Definiteness via Random Submatrices. FOCS Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
2020	J	`jnl`	Testing Positive Semi-Definiteness via Random Submatrices. CoRR Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
2019	A*	`conf`	Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. PODS Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2019	J	`jnl`	Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. CoRR Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros
2019	A*	`conf`	Learning Two Layer Rectified Neural Networks in Polynomial Time. COLT Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
2019	A*	`conf`	Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. NeurIPS Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff
2019	J	`jnl`	Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. CoRR Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff
2019	—	`conf`	Towards Optimal Moment Estimation in Streaming and Distributed Models. APPROX-RANDOM Rajesh Jayaram, David P. Woodruff
2019	J	`jnl`	Towards Optimal Moment Estimation in Streaming and Distributed Models. CoRR Rajesh Jayaram, David P. Woodruff
2019	A*	`conf`	Weighted Reservoir Sampling from Distributed Streams. PODS Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff
2019	J	`jnl`	Weighted Reservoir Sampling from Distributed Streams. CoRR Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff
2018	A*	`conf`	Data Streams with Bounded Deletions. PODS Rajesh Jayaram, David P. Woodruff
2018	J	`jnl`	Data Streams with Bounded Deletions. CoRR Rajesh Jayaram, David P. Woodruff
2018	J	`jnl`	Learning Two Layer Rectified Neural Networks in Polynomial Time. CoRR Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
2018	J	`jnl`	Perfect L CoRR Rajesh Jayaram, David P. Woodruff
2018	A*	`conf`	Perfect Lp Sampling in a Data Stream. FOCS Rajesh Jayaram, David P. Woodruff
2017	A*	`conf`	Approximating Language Edit Distance Beyond Fast Matrix Multiplication: Ultralinear Grammars Are Where Parsing Becomes Hard!. ICALP Rajesh Jayaram, Barna Saha