Approximating Language Edit Distance Beyond Fast Matrix Multiplication: Ultralinear Grammars Are Where Parsing Becomes Hard!. - Rajesh Jayaram; Barna Saha (ICALP, 2017)

Perfect Lp Sampling in a Data Stream. - Rajesh Jayaram; David P. Woodruff (FOCS, 2018)

Data Streams with Bounded Deletions. - Rajesh Jayaram; David P. Woodruff (PODS, 2018)

Learning Two Layer Rectified Neural Networks in Polynomial Time. - Ainesh Bakshi; Rajesh Jayaram; David P. Woodruff (COLT, 2019)

Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. - Huaian Diao; Rajesh Jayaram; Zhao Song 002; Wen Sun; David P. Woodruff (NeurIPS, 2019)

Weighted Reservoir Sampling from Distributed Streams. - Rajesh Jayaram; Gokarna Sharma; Srikanta Tirthapura; David P. Woodruff (PODS, 2019)

Testing Positive Semi-Definiteness via Random Submatrices. - Ainesh Bakshi; Nadiia Chepurko; Rajesh Jayaram (FOCS, 2020)

Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. - Rajesh Jayaram; David P. Woodruff; Qiuyi Zhang 001 (ICLR, 2020)

Learning and Testing Junta Distributions with Subcube Conditioning. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (CoRR, 2020)

An FPRAS and Polynomial-Time Uniform Sampler for Tree Automata. - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (CoRR, 2020)

Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (SIGMOD Rec., 2020)

An Optimal Algorithm for Triangle Counting in the Stream. - Rajesh Jayaram; John Kallaugher (APPROX-RANDOM, 2021)

Learning and testing junta distributions with sub cube conditioning. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (COLT, 2021)

In-Database Regression in Input Sparsity Time. - Rajesh Jayaram; Alireza Samadian; David P. Woodruff; Peng Ye 005 (ICML, 2021)

A polynomial-time approximation algorithm for counting words accepted by an NFA (invited paper). - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (STOC, 2021)

When is approximate counting for conjunctive queries tractable? - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (STOC, 2021)

An Optimal Algorithm for Triangle Counting. - Rajesh Jayaram; John Kallaugher (CoRR, 2021)

Optimal Fully Dynamic k-Centers Clustering. - MohammadHossein Bateni; Hossein Esfandiari; Rajesh Jayaram; Vahab S. Mirrokni (CoRR, 2021)

#NFA Admits an FPRAS: Efficient Enumeration, Counting, and Uniform Generation for Logspace Classes. - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (J. ACM, 2021)

Perfect Lp Sampling in a Data Stream. - Rajesh Jayaram; David P. Woodruff (SIAM J. Comput., 2021)

A Framework for Adversarially Robust Streaming Algorithms. - Omri Ben-Eliezer; Rajesh Jayaram; David P. Woodruff; Eylon Yogev (SIGMOD Rec., 2021)

Sketching and Sampling Algorithms for High-Dimensional Data. - Rajesh Jayaram (2021)

Stars: Tera-Scale Graph Building for Clustering and Learning. - CJ Carey; Jonathan Halcrow; Rajesh Jayaram; Vahab Mirrokni; Warren Schudy; Peilin Zhong (NeurIPS, 2022)

Truly Perfect Samplers for Data Streams and Sliding Windows. - Rajesh Jayaram; David P. Woodruff; Samson Zhou (PODS, 2022)

New streaming algorithms for high dimensional EMD and MST. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (STOC, 2022)

Stars: Tera-Scale Graph Building for Clustering and Graph Learning. - CJ Carey; Jonathan Halcrow; Rajesh Jayaram; Vahab Mirrokni; Warren Schudy; Peilin Zhong (CoRR, 2022)

Adore: Differentially Oblivious Relational Database Operators. - Lianke Qin; Rajesh Jayaram; Elaine Shi; Zhao Song 002; Danyang Zhuo; Shumo Chu (CoRR, 2022)

Differentially Oblivious Relational Database Operators. - Lianke Qin; Rajesh Jayaram; Elaine Shi; Zhao Song 002; Danyang Zhuo; Shumo Chu (Proc. VLDB Endow., 2022)

Counting the Answers to a Query. - Marcelo Arenas; Luis Alberto Croquevielle; Rajesh Jayaram; Cristian Riveros (SIGMOD Rec., 2022)

Near-Linear Time Algorithm for the Chamfer Distance. - Ainesh Bakshi; Piotr Indyk; Rajesh Jayaram; Sandeep Silwal; Erik Waingarten (NeurIPS, 2023)

Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries. - MohammadHossein Bateni; Hossein Esfandiari; Hendrik Fichtenberger; Monika Henzinger; Rajesh Jayaram; Vahab Mirrokni; Andreas Wiese (SODA, 2023)

Streaming Euclidean MST to a Constant Factor. - Xi Chen 001; Vincent Cohen-Addad; Rajesh Jayaram; Amit Levi; Erik Waingarten (STOC, 2023)

Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries. - MohammadHossein Bateni; Hossein Esfandiari; Hendrik Fichtenberger; Monika Henzinger; Rajesh Jayaram; Vahab Mirrokni; Andreas Wiese (CoRR, 2023)

Fully Dynamic Consistent k-Center Clustering. - Jakub Lacki; Bernhard Haeupler; Christoph Grunau; Václav Rozhon; Rajesh Jayaram (CoRR, 2023)

A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. - Ainesh Bakshi; Vincent Cohen-Addad; Samuel B. Hopkins 001; Rajesh Jayaram; Silvio Lattanzi (CoRR, 2023)

Technical Perspective: Optimal Algorithms for Multiway Search on Partial Orders. - Rajesh Jayaram (SIGMOD Rec., 2023)

Towards Optimal Moment Estimation in Streaming and Distributed Models. - Rajesh Jayaram; David P. Woodruff (ACM Trans. Algorithms, 2023)

Metric Clustering and MST with Strong and Weak Distance Oracles. - MohammadHossein Bateni; Prathamesh Dharangutte; Rajesh Jayaram; Chen Wang (COLT, 2024)

It's Hard to HAC Average Linkage! - MohammadHossein Bateni; Laxman Dhulipala; Kishen N. Gowda; D. Ellis Hershkowitz; Rajesh Jayaram; Jakub Lacki (ICALP, 2024)

Dynamic PageRank: Algorithms and Lower Bounds. - Rajesh Jayaram; Jakub Lacki; Slobodan Mitrovic; Krzysztof Onak; Piotr Sankowski (ICALP, 2024)

HyperAttention: Long-context Attention in Near-Linear Time. - Insu Han; Rajesh Jayaram; Amin Karbasi; Vahab Mirrokni; David P. Woodruff; Amir Zandieh (ICLR, 2024)

Efficient Centroid-Linkage Clustering. - Mohammad Hossein Bateni 001; Laxman Dhulipala; Willem Fletcher; Kishen N. Gowda; D. Ellis Hershkowitz; Rajesh Jayaram; Jakub Lacki (NeurIPS, 2024)

MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding. - Rajesh Jayaram; Laxman Dhulipala; Majid Hadian; Jason Lee; Vahab Mirrokni (NeurIPS, 2024)

Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. - Rajesh Jayaram; Vahab Mirrokni; Shyam Narayanan; Peilin Zhong (SODA, 2024)

Fully Dynamic Consistent k-Center Clustering. - Jakub Lacki; Bernhard Haeupler; Christoph Grunau; Rajesh Jayaram; Václav Rozhon (SODA, 2024)

Data-Dependent LSH for the Earth Mover's Distance. - Rajesh Jayaram; Erik Waingarten; Tian Zhang (STOC, 2024)

MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings. - Laxman Dhulipala; Majid Hadian; Rajesh Jayaram; Jason Lee; Vahab Mirrokni (CoRR, 2024)

Streaming Algorithms with Few State Changes. - Rajesh Jayaram; David P. Woodruff; Samson Zhou (Proc. ACM Manag. Data, 2024)

Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams. - Ainesh Bakshi; Vincent Cohen-Addad; Rajesh Jayaram; Sam Hopkins 001; Silvio Lattanzi (COLT, 2025)

Massively Parallel Minimum Spanning Tree in General Metric Spaces. - Amir Azarmehr; Soheil Behnezhad; Rajesh Jayaram; Jakub Lacki; Vahab Mirrokni; Peilin Zhong (SODA, 2025)

Improved Spectral Density Estimation via Explicit and Implicit Deflation. - Rajarshi Bhattacharjee; Rajesh Jayaram; Cameron Musco; Christopher Musco; Archan Ray (SODA, 2025)

Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search. - Lars Gottesbüren; Laxman Dhulipala; Rajesh Jayaram; Jakub Lacki (Proc. VLDB Endow., 2025)

CRISP: Clustering Multi-Vector Representations for Denoising and Pruning. - João Veneroso; Rajesh Jayaram; Jinmeng Rao; Gustavo Hernández Ábrego; Majid Hadian; Daniel Cer (CoRR, 2025)

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. - Jie Gao; Rajesh Jayaram; Benedikt Kolbe; Shay Sapir; Chris Schwiegelshohn; Sandeep Silwal; Erik Waingarten (CoRR, 2025)

Parallel Hierarchical Agglomerative Clustering in Low Dimensions. - MohammadHossein Bateni; Laxman Dhulipala; Willem Fletcher; Kishen N. Gowda; D. Ellis Hershkowitz; Rajesh Jayaram; Jakub Lacki (CoRR, 2025)

Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair. - Lorenzo Beretta 001; Vincent Cohen-Addad; Rajesh Jayaram; Erik Waingarten (CoRR, 2025)