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Shyam Narayanan
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2020 – today
- 2024
- [j5]Sinho Chewi
, Jaume de Dios Pont
Query Lower Bounds for Log-concave Sampling. J. ACM 71(4): 29:1-29:42 (2024) - [c37]Sitan Chen, Shyam Narayanan:
A faster and simpler algorithm for learning shallow networks. COLT 2024: 981-994 - [c36]Shyam Narayanan, Václav Rozhon, Jakub Tetek, Mikkel Thorup:
Instance-Optimality in I/O-Efficient Sampling and Sequential Estimation. FOCS 2024: 658-688 - [c35]Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. SODA 2024: 3960-3996 - [i39]Shyam Narayanan:
Improved algorithms for learning quantum Hamiltonians, via flat polynomials. CoRR abs/2407.04540 (2024) - [i38]Shyam Narayanan, Václav Rozhon, Jakub Tetek, Mikkel Thorup:
Instance-Optimality in I/O-Efficient Sampling and Sequential Estimation. CoRR abs/2410.14643 (2024) - [i37]Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu:
Statistical-Computational Trade-offs for Density Estimation. CoRR abs/2410.23087 (2024) - 2023
- [c34]Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner:
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA 2023: 87-97 - [c33]Sepideh Mahabadi, Shyam Narayanan:
Improved Diversity Maximization Algorithms for Matching and Pseudoforest. APPROX/RANDOM 2023: 25:1-25:22 - [c32]Talya Eden, Jakob Bæk Tejs Houen, Shyam Narayanan, Will Rosenbaum, Jakub Tetek:
Bias Reduction for Sum Estimation. APPROX/RANDOM 2023: 62:1-62:21 - [c31]Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri:
SPAIC: A sub-μW/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders. BioCAS 2023: 1-5 - [c30]Ainesh Bakshi, Shyam Narayanan:
Krylov Methods are (nearly) Optimal for Low-Rank Approximation. FOCS 2023: 2093-2101 - [c29]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. FOCS 2023: 2139-2148 - [c28]Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan:
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. FOCS 2023: 2159-2168 - [c27]Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal:
Data Structures for Density Estimation. ICML 2023: 1-18 - [c26]Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan:
Differentially Private Approximate Near Neighbor Counting in High Dimensions. NeurIPS 2023 - [c25]Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
k-Means Clustering with Distance-Based Privacy. NeurIPS 2023 - [c24]Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu:
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. SODA 2023: 5040-5067 - [c23]Shyam Narayanan, Jakub Tetek:
Estimating the Effective Support Size in Constant Query Complexity. SOSA 2023: 242-252 - [c22]Talya Eden, Shyam Narayanan, Jakub Tetek:
Sampling an Edge in Sublinear Time Exactly and Optimally. SOSA 2023: 253-260 - [c21]Samuel B. Hopkins, Gautam Kamath
Robustness Implies Privacy in Statistical Estimation. STOC 2023: 497-506 - [i36]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. CoRR abs/2304.02599 (2023) - [i35]Ainesh Bakshi, Shyam Narayanan:
Krylov Methods are (nearly) Optimal for Low-Rank Approximation. CoRR abs/2304.03191 (2023) - [i34]Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner:
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR abs/2304.07652 (2023) - [i33]Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal:
Data Structures for Density Estimation. CoRR abs/2306.11312 (2023) - [i32]Sepideh Mahabadi, Shyam Narayanan:
Improved Diversity Maximization Algorithms for Matching and Pseudoforest. CoRR abs/2307.04329 (2023) - [i31]Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan:
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. CoRR abs/2307.10273 (2023) - [i30]Sitan Chen, Shyam Narayanan:
A faster and simpler algorithm for learning shallow networks. CoRR abs/2307.12496 (2023) - [i29]Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree. CoRR abs/2308.00503 (2023) - [i28]Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri:
SPAIC: A sub-μW/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders. CoRR abs/2309.03221 (2023) - [i27]Shyam Narayanan:
Better and Simpler Lower Bounds for Differentially Private Statistical Estimation. CoRR abs/2310.06289 (2023) - 2022
- [j4]Shyam Narayanan:
Three-wise independent random walks can be slightly unbounded. Random Struct. Algorithms 61(3): 573-598 (2022) - [c20]Shyam Narayanan:
Private High-Dimensional Hypothesis Testing. COLT 2022: 3979-4027 - [c19]William Kuszmaul, Shyam Narayanan:
Optimal Time-Backlog Tradeoffs for the Variable-Processor Cup Game. ICALP 2022: 85:1-85:20 - [c18]Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang:
Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR 2022 - [c17]Shyam Narayanan, Vahab S. Mirrokni, Hossein Esfandiari:
Tight and Robust Private Mean Estimation with Few Users. ICML 2022: 16383-16412 - [c16]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. ISCAS 2022: 476-480 - [c15]Shyam Narayanan, Erika Covi
A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices. ISCAS 2022: 717-721 - [c14]Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner:
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS 2022 - [c13]Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Near-Optimal Private and Scalable $k$-Clustering. NeurIPS 2022 - [c12]Piotr Indyk, Shyam Narayanan, David P. Woodruff:
Frequency Estimation with One-Sided Error. SODA 2022: 695-707 - [c11]Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan:
Almost Tight Approximation Algorithms for Explainable Clustering. SODA 2022: 2641-2663 - [c10]Vincent Cohen-Addad, Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan:
Improved approximations for Euclidean k-means and k-median, via nested quasi-independent sets. STOC 2022: 1621-1628 - [i26]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand:
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. CoRR abs/2201.10409 (2022) - [i25]Shyam Narayanan, Erika Covi, Viktor Havel, Charlotte Frenkel, Suzanne Lancaster, Quang T. Duong, Stefan Slesazeck, Thomas Mikolajick, Melika Payvand, Giacomo Indiveri:
A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices. CoRR abs/2202.04049 (2022) - [i24]Shyam Narayanan:
Private High-Dimensional Hypothesis Testing. CoRR abs/2203.01537 (2022) - [i23]Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang:
Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR abs/2203.09572 (2022) - [i22]Justin Y. Chen, Shyam Narayanan, Yinzhan Xu:
All-Pairs Shortest Path Distances with Differential Privacy: Improved Algorithms for Bounded and Unbounded Weights. CoRR abs/2204.02335 (2022) - [i21]Vincent Cohen-Addad, Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan:
Improved Approximations for Euclidean k-means and k-median, via Nested Quasi-Independent Sets. CoRR abs/2204.04828 (2022) - [i20]William Kuszmaul, Shyam Narayanan:
Optimal Time-Backlog Tradeoffs for the Variable-Processor Cup Game. CoRR abs/2205.01722 (2022) - [i19]Talya Eden, Jakob Bæk Tejs Houen, Shyam Narayanan, Will Rosenbaum, Jakub Tetek:
Bias Reduction for Sum Estimation. CoRR abs/2208.01197 (2022) - [i18]Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner:
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR abs/2211.03232 (2022) - [i17]Talya Eden, Shyam Narayanan, Jakub Tetek:
Sampling an Edge in Sublinear Time Exactly and Optimally. CoRR abs/2211.04981 (2022) - [i16]Shyam Narayanan, Jakub Tetek:
Estimating the Effective Support Size in Constant Query Complexity. CoRR abs/2211.11344 (2022) - [i15]Samuel B. Hopkins, Gautam Kamath
Robustness Implies Privacy in Statistical Estimation. CoRR abs/2212.05015 (2022) - 2021
- [j3]Shyam Narayanan, Alec Sun:
Bounds on expected propagation time of probabilistic zero forcing. Eur. J. Comb. 98: 103405 (2021) - [c9]William Kuszmaul, Shyam Narayanan:
Stochastic and Worst-Case Generalized Sorting Revisited. FOCS 2021: 1056-1067 - [c8]Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner:
Learning-based Support Estimation in Sublinear Time. ICLR 2021 - [c7]Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir:
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. ICML 2021: 7948-7957 - [c6]Shyam Narayanan, Michael Ren:
Circular Trace Reconstruction. ITCS 2021: 18:1-18:18 - [c5]Shyam Narayanan:
On Tolerant Distribution Testing in the Conditional Sampling Model. SODA 2021: 357-373 - [c4]Shyam Narayanan:
Improved Algorithms for Population Recovery from the Deletion Channel. SODA 2021: 1259-1278 - [i14]Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner:
Learning-based Support Estimation in Sublinear Time. CoRR abs/2106.08396 (2021) - [i13]Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan:
Almost Tight Approximation Algorithms for Explainable Clustering. CoRR abs/2107.00774 (2021) - [i12]Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir:
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. CoRR abs/2107.01804 (2021) - [i11]Hossein Esfandiari, Vahab S. Mirrokni, Shyam Narayanan:
Tight and Robust Private Mean Estimation with Few Users. CoRR abs/2110.11876 (2021) - [i10]Piotr Indyk, Shyam Narayanan, David P. Woodruff:
Frequency Estimation with One-Sided Error. CoRR abs/2111.03953 (2021) - [i9]William Kuszmaul, Shyam Narayanan:
Stochastic and Worst-Case Generalized Sorting Revisited. CoRR abs/2111.07222 (2021) - 2020
- [j2]Shyam Narayanan:
Functions on antipower prefix lengths of the Thue-Morse word. Discret. Math. 343(2): 111675 (2020) - [i8]Shyam Narayanan:
Population Recovery from the Deletion Channel: Nearly Matching Trace Reconstruction Bounds. CoRR abs/2004.06828 (2020) - [i7]Shyam Narayanan:
Tolerant Distribution Testing in the Conditional Sampling Model. CoRR abs/2007.09895 (2020) - [i6]Shyam Narayanan, Michael Ren:
Circular Trace Reconstruction. CoRR abs/2009.01346 (2020) - [i5]Timothy Chu, Gary L. Miller, Shyam Narayanan, Mark Sellke:
Functions that Preserve Manhattan Distances. CoRR abs/2011.11503 (2020)
2010 – 2019
- 2019
- [c3]Shyam Narayanan:
Pairwise Independent Random Walks Can Be Slightly Unbounded. APPROX-RANDOM 2019: 63:1-63:19 - [c2]Shyam Narayanan, Jelani Nelson:
Optimal terminal dimensionality reduction in Euclidean space. STOC 2019: 1064-1069 - [i4]Shyam Narayanan, Alec Sun:
Bounds on expected propagation time of probabilistic zero forcing. CoRR abs/1909.04482 (2019) - 2018
- [j1]Evan Chen, Shyam Narayanan:
The 26 Wilf-equivalence classes of length five quasi-consecutive patterns. Discret. Math. Theor. Comput. Sci. 20(2) (2018) - [c1]Shyam Narayanan:
Deterministic O(1)-Approximation Algorithms to 1-Center Clustering with Outliers. APPROX-RANDOM 2018: 21:1-21:19 - [i3]Shyam Narayanan:
Deterministic O(1)-Approximation Algorithms to 1-Center Clustering with Outliers. CoRR abs/1806.07356 (2018) - [i2]Shyam Narayanan:
Pairwise Independent Random Walks can be Slightly Unbounded. CoRR abs/1807.04910 (2018) - [i1]Shyam Narayanan, Jelani Nelson:
Optimal terminal dimensionality reduction in Euclidean space. CoRR abs/1810.09250 (2018)
Coauthor Index
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