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ORCIDRajesh Jayaram
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2020 – today
- 2024
[j10]Rajesh Jayaram
, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data 2(2): 82 (2024)- [c29]MohammadHossein Bateni, Prathamesh Dharangutte, Rajesh Jayaram, Chen Wang:
Metric Clustering and MST with Strong and Weak Distance Oracles. COLT 2024: 498-550 - [c28]MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki:
It's Hard to HAC Average Linkage! ICALP 2024: 18:1-18:18 - [c27]Rajesh Jayaram, Jakub Lacki, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski:
Dynamic PageRank: Algorithms and Lower Bounds. ICALP 2024: 90:1-90:19 - [c26]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. ICLR 2024 - [c25]Jakub Lacki, Bernhard Haeupler, Christoph Grunau, Rajesh Jayaram, Václav Rozhon:
Fully Dynamic Consistent k-Center Clustering. SODA 2024: 3463-3484 - [c24]Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. SODA 2024: 3960-3996 - [c23]Rajesh Jayaram, Erik Waingarten, Tian Zhang:
Data-Dependent LSH for the Earth Mover's Distance. STOC 2024: 800-811 - [i36]Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram, Jakub Lacki:
Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search. CoRR abs/2403.01797 (2024) - [i35]Rajesh Jayaram, Erik Waingarten, Tian Zhang:
Data-Dependent LSH for the Earth Mover's Distance. CoRR abs/2403.05041 (2024) - [i34]MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki:
It's Hard to HAC with Average Linkage! CoRR abs/2404.14730 (2024) - [i33]Rajesh Jayaram, Jakub Lacki, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski:
Dynamic PageRank: Algorithms and Lower Bounds. CoRR abs/2404.16267 (2024) - [i32]Laxman Dhulipala, Majid Hadian, Rajesh Jayaram, Jason Lee, Vahab Mirrokni:
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings. CoRR abs/2405.19504 (2024) - [i31]MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki:
Efficient Centroid-Linkage Clustering. CoRR abs/2406.05066 (2024) - [i30]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. CoRR abs/2406.06821 (2024) - [i29]Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Lacki, Vahab Mirrokni, Peilin Zhong:
Massively Parallel Minimum Spanning Tree in General Metric Spaces. CoRR abs/2408.06455 (2024) - [i28]Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray:
Improved Spectral Density Estimation via Explicit and Implicit Deflation. CoRR abs/2410.21690 (2024) - 2023
- [j9]Rajesh Jayaram:
Technical Perspective: Optimal Algorithms for Multiway Search on Partial Orders. SIGMOD Rec. 52(1): 83 (2023) - [j8]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. ACM Trans. Algorithms 19(3): 27:1-27:35 (2023) - [c22]Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten:
Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS 2023 - [c21]MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger, Rajesh Jayaram, Vahab Mirrokni, Andreas Wiese:
Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries. SODA 2023: 2677-2727 - [c20]Xi Chen, Vincent Cohen-Addad, Rajesh Jayaram, Amit Levi, Erik Waingarten:
Streaming Euclidean MST to a Constant Factor. STOC 2023: 156-169 - [i27]MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger, Monika Henzinger, Rajesh Jayaram, Vahab Mirrokni, Andreas Wiese:
Optimal Fully Dynamic k-Center Clustering for Adaptive and Oblivious Adversaries. CoRR abs/2303.11843 (2023) - [i26]Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten:
A Near-Linear Time Algorithm for the Chamfer Distance. CoRR abs/2307.03043 (2023) - [i25]Jakub Lacki, Bernhard Haeupler, Christoph Grunau, Václav Rozhon, Rajesh Jayaram:
Fully Dynamic Consistent k-Center Clustering. CoRR abs/2307.13747 (2023) - [i24]Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. CoRR abs/2308.00503 (2023) - [i23]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. CoRR abs/2310.05869 (2023) - [i22]MohammadHossein Bateni, Prathamesh Dharangutte, Rajesh Jayaram, Chen Wang:
Metric Clustering and MST with Strong and Weak Distance Oracles. CoRR abs/2310.15863 (2023) - [i21]Ainesh Bakshi, Vincent Cohen-Addad, Samuel B. Hopkins, Rajesh Jayaram, Silvio Lattanzi:
A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. CoRR abs/2311.17840 (2023) - 2022
- [j7]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. J. ACM 69(2): 17:1-17:33 (2022) - [j6]Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu:
Differentially Oblivious Relational Database Operators. Proc. VLDB Endow. 16(4): 842-855 (2022) - [j5]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
Counting the Answers to a Query. SIGMOD Rec. 51(3): 6-17 (2022) - [c19]CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong:
Stars: Tera-Scale Graph Building for Clustering and Learning. NeurIPS 2022 - [c18]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. PODS 2022: 29-40 - [c17]Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten:
New streaming algorithms for high dimensional EMD and MST. STOC 2022: 222-233 - [i20]CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong:
Stars: Tera-Scale Graph Building for Clustering and Graph Learning. CoRR abs/2212.02635 (2022) - [i19]Lianke Qin, Rajesh Jayaram, Elaine Shi, Zhao Song, Danyang Zhuo, Shumo Chu:
Adore: Differentially Oblivious Relational Database Operators. CoRR abs/2212.05176 (2022) - [i18]Vincent Cohen-Addad, Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten:
Streaming Euclidean MST to a Constant Factor. CoRR abs/2212.06546 (2022) - 2021
- [b1]Rajesh Jayaram:
Sketching and Sampling Algorithms for High-Dimensional Data. Carnegie Mellon University, USA, 2021 - [j4]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
#NFA Admits an FPRAS: Efficient Enumeration, Counting, and Uniform Generation for Logspace Classes. J. ACM 68(6): 48:1-48:40 (2021) - [j3]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. SIAM J. Comput. 50(2): 382-439 (2021) - [j2]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. SIGMOD Rec. 50(1): 6-13 (2021) - [c16]Rajesh Jayaram, John Kallaugher:
An Optimal Algorithm for Triangle Counting in the Stream. APPROX-RANDOM 2021: 11:1-11:11 - [c15]Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten:
Learning and testing junta distributions with sub cube conditioning. COLT 2021: 1060-1113 - [c14]Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye:
In-Database Regression in Input Sparsity Time. ICML 2021: 4797-4806 - [c13]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
A polynomial-time approximation algorithm for counting words accepted by an NFA (invited paper). STOC 2021: 4 - [c12]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
When is approximate counting for conjunctive queries tractable? STOC 2021: 1015-1027 - [i17]Rajesh Jayaram, John Kallaugher:
An Optimal Algorithm for Triangle Counting. CoRR abs/2105.01785 (2021) - [i16]Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye:
In-Database Regression in Input Sparsity Time. CoRR abs/2107.05672 (2021) - [i15]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR abs/2108.12017 (2021) - [i14]Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten:
New Streaming Algorithms for High Dimensional EMD and MST. CoRR abs/2111.03528 (2021) - [i13]MohammadHossein Bateni, Hossein Esfandiari, Rajesh Jayaram, Vahab S. Mirrokni:
Optimal Fully Dynamic k-Centers Clustering. CoRR abs/2112.07050 (2021) - 2020
- [j1]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. SIGMOD Rec. 49(1): 52-59 (2020) - [c11]Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram:
Testing Positive Semi-Definiteness via Random Submatrices. FOCS 2020: 1191-1202 - [c10]Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang:
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. ICLR 2020 - [c9]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. PODS 2020: 63-80 - [i12]Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang:
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. CoRR abs/2002.08202 (2020) - [i11]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. CoRR abs/2003.14265 (2020) - [i10]Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten:
Learning and Testing Junta Distributions with Subcube Conditioning. CoRR abs/2004.12496 (2020) - [i9]Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram:
Testing Positive Semi-Definiteness via Random Submatrices. CoRR abs/2005.06441 (2020) - [i8]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
An FPRAS and Polynomial-Time Uniform Sampler for Tree Automata. CoRR abs/2005.10029 (2020)
2010 – 2019
- 2019
- [c8]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. APPROX-RANDOM 2019: 29:1-29:21 - [c7]Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff:
Learning Two Layer Rectified Neural Networks in Polynomial Time. COLT 2019: 195-268 - [c6]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. NeurIPS 2019: 4739-4750 - [c5]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. PODS 2019: 59-73 - [c4]Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff:
Weighted Reservoir Sampling from Distributed Streams. PODS 2019: 218-235 - [i7]Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff:
Weighted Reservoir Sampling from Distributed Streams. CoRR abs/1904.04126 (2019) - [i6]Marcelo Arenas, Luis Alberto Croquevielle, Rajesh Jayaram, Cristian Riveros:
Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation. CoRR abs/1906.09226 (2019) - [i5]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. CoRR abs/1907.05816 (2019) - [i4]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. CoRR abs/1909.13384 (2019) - 2018
- [c3]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. FOCS 2018: 544-555 - [c2]Rajesh Jayaram, David P. Woodruff:
Data Streams with Bounded Deletions. PODS 2018: 341-354 - [i3]Rajesh Jayaram, David P. Woodruff:
Data Streams with Bounded Deletions. CoRR abs/1803.08777 (2018) - [i2]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. CoRR abs/1808.05497 (2018) - [i1]Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff:
Learning Two Layer Rectified Neural Networks in Polynomial Time. CoRR abs/1811.01885 (2018) - 2017
- [c1]Rajesh Jayaram, Barna Saha:
Approximating Language Edit Distance Beyond Fast Matrix Multiplication: Ultralinear Grammars Are Where Parsing Becomes Hard!. ICALP 2017: 19:1-19:15
Coauthor Index
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