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2020 – today
- 2024
[j7]Jeremiah Blocki, Peiyuan Liu, Ling Ren, Samson Zhou:
Bandwidth-Hard Functions: Reductions and Lower Bounds. J. Cryptol. 37(2): 16 (2024)- [j6]Rajesh Jayaram
, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data 2(2): 82 (2024) - [c61]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou:
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. ICML 2024 - [i67]Chunkai Fu, Jung Hoon Seo, Samson Zhou:
Learning-Augmented Skip Lists. CoRR abs/2402.10457 (2024) - [i66]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou:
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. CoRR abs/2404.10201 (2024) - [i65]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. CoRR abs/2406.06821 (2024) - [i64]Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford:
Fair Submodular Cover. CoRR abs/2407.04804 (2024) - [i63]Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou:
A Strong Separation for Adversarially Robust ℓ0 Estimation for Linear Sketches. CoRR abs/2409.16153 (2024) - 2023
- [c60]Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou:
Private Data Stream Analysis for Universal Symmetric Norm Estimation. APPROX/RANDOM 2023: 45:1-45:24 - [c59]Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou:
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. APPROX/RANDOM 2023: 59:1-59:24 - [c58]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou:
Differentially Private Aggregation via Imperfect Shuffling. ITC 2023: 17:1-17:22 - [c57]Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou:
On Differential Privacy and Adaptive Data Analysis with Bounded Space. EUROCRYPT (3) 2023: 35-65 - [c56]Vincent Cohen-Addad, David P. Woodruff, Samson Zhou:
Streaming Euclidean k-median and k-means with o(log n) Space. FOCS 2023: 883-908 - [c55]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR 2023 - [c54]Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou:
Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. ICLR 2023 - [c53]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR 2023 - [c52]Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman:
Provable Data Subset Selection For Efficient Neural Networks Training. ICML 2023: 34533-34555 - [c51]Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou:
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. ICML 2023: 34952-34977 - [c50]Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa Sanjay Parekh:
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. MIDL 2023: 1751-1764 - [c49]David P. Woodruff, Peilin Zhong, Samson Zhou:
Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS 2023 - [c48]David P. Woodruff, Fred Zhang, Samson Zhou:
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS 2023 - [c47]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. SODA 2023: 3959-4025 - [c46]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2023: 4026-4049 - [i62]Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou:
On Differential Privacy and Adaptive Data Analysis with Bounded Space. CoRR abs/2302.05707 (2023) - [i61]Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou:
Differentially Private L2-Heavy Hitters in the Sliding Window Model. CoRR abs/2302.11081 (2023) - [i60]Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh:
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. CoRR abs/2302.11510 (2023) - [i59]David P. Woodruff, Fred Zhang, Samson Zhou:
Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR abs/2303.01709 (2023) - [i58]Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman:
Provable Data Subset Selection For Efficient Neural Network Training. CoRR abs/2303.05151 (2023) - [i57]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR abs/2304.07413 (2023) - [i56]Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou:
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. CoRR abs/2306.01869 (2023) - [i55]Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou:
Private Data Stream Analysis for Universal Symmetric Norm Estimation. CoRR abs/2307.04249 (2023) - [i54]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou:
Differentially Private Aggregation via Imperfect Shuffling. CoRR abs/2308.14733 (2023) - [i53]Vincent Cohen-Addad, David P. Woodruff, Samson Zhou:
Streaming Euclidean k-median and k-means with o(log n) Space. CoRR abs/2310.02882 (2023) - [i52]David P. Woodruff, Peilin Zhong, Samson Zhou:
Near-Optimal k-Clustering in the Sliding Window Model. CoRR abs/2311.00642 (2023) - [i51]Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou:
On Differential Privacy and Adaptive Data Analysis with Bounded Space. IACR Cryptol. ePrint Arch. 2023: 171 (2023) - 2022
- [j5]Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy:
Data-Independent Structured Pruning of Neural Networks via Coresets. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7829-7841 (2022) - [c45]Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman:
New Coresets for Projective Clustering and Applications. AISTATS 2022: 5391-5415 - [c44]Sepideh Mahabadi, David P. Woodruff, Samson Zhou:
Adaptive Sketches for Robust Regression with Importance Sampling. APPROX/RANDOM 2022: 31:1-31:21 - [c43]Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Learning-Augmented $k$-means Clustering. ICLR 2022 - [c42]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Fast Regression for Structured Inputs. ICLR 2022 - [c41]Eric Price, Sandeep Silwal, Samson Zhou:
Hardness and Algorithms for Robust and Sparse Optimization. ICML 2022: 17926-17944 - [c40]Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou:
Noisy Boolean Hidden Matching with Applications. ITCS 2022: 91:1-91:19 - [c39]Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou:
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS 2022 - [c38]Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou:
The White-Box Adversarial Data Stream Model. PODS 2022: 15-27 - [c37]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. PODS 2022: 29-40 - [c36]Agniva Chowdhury, Aritra Bose, Samson Zhou, David P. Woodruff, Petros Drineas:
A Fast, Provably Accurate Approximation Algorithm for Sparse Principal Component Analysis Reveals Human Genetic Variation Across the World. RECOMB 2022: 86-106 - [c35]Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou:
Memory bounds for the experts problem. STOC 2022: 1158-1171 - [i50]Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman:
New Coresets for Projective Clustering and Applications. CoRR abs/2203.04370 (2022) - [i49]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Fast Regression for Structured Inputs. CoRR abs/2203.07557 (2022) - [i48]Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou:
The White-Box Adversarial Data Stream Model. CoRR abs/2204.09136 (2022) - [i47]Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou:
Memory Bounds for the Experts Problem. CoRR abs/2204.09837 (2022) - [i46]Eric Price, Sandeep Silwal, Samson Zhou:
Hardness and Algorithms for Robust and Sparse Optimization. CoRR abs/2206.14354 (2022) - [i45]Sepideh Mahabadi, David P. Woodruff, Samson Zhou:
Adaptive Sketches for Robust Regression with Importance Sampling. CoRR abs/2207.07822 (2022) - [i44]Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou:
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR abs/2209.10614 (2022) - [i43]Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou:
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. CoRR abs/2210.03831 (2022) - [i42]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. CoRR abs/2211.06790 (2022) - [i41]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR abs/2211.09964 (2022) - [i40]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR abs/2212.00642 (2022) - 2021
- [j4]Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou:
Relaxed Locally Correctable Codes in Computationally Bounded Channels. IEEE Trans. Inf. Theory 67(7): 4338-4360 (2021) - [c34]Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou:
Efficient Coreset Constructions via Sensitivity Sampling. ACML 2021: 948-963 - [c33]Jeremiah Blocki, Seunghoon Lee, Samson Zhou:
On the Security of Proofs of Sequential Work in a Post-Quantum World. ITC 2021: 22:1-22:27 - [c32]Vladimir Braverman, Viska Wei, Samson Zhou:
Symmetric Norm Estimation and Regression on Sliding Windows. COCOON 2021: 528-539 - [c31]David P. Woodruff, Samson Zhou:
Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. FOCS 2021: 1183-1196 - [c30]David P. Woodruff, Samson Zhou:
Separations for Estimating Large Frequency Moments on Data Streams. ICALP 2021: 112:1-112:21 - [c29]Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou:
Learning a Latent Simplex in Input Sparsity Time. ICLR 2021 - [c28]Yuichi Yoshida, Samson Zhou:
Sensitivity Analysis of the Maximum Matching Problem. ITCS 2021: 58:1-58:20 - [c27]Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou:
Adversarial Robustness of Streaming Algorithms through Importance Sampling. NeurIPS 2021: 3544-3557 - [c26]Zachary Izzo, Sandeep Silwal, Samson Zhou:
Dimensionality Reduction for Wasserstein Barycenter. NeurIPS 2021: 15582-15594 - [i39]David P. Woodruff, Samson Zhou:
Separations for Estimating Large Frequency Moments on Data Streams. CoRR abs/2105.03773 (2021) - [i38]Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou:
Learning a Latent Simplex in Input-Sparsity Time. CoRR abs/2105.08005 (2021) - [i37]Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou:
Adversarial Robustness of Streaming Algorithms through Importance Sampling. CoRR abs/2106.14952 (2021) - [i36]Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou:
Noisy Boolean Hidden Matching with Applications. CoRR abs/2107.02578 (2021) - [i35]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR abs/2108.12017 (2021) - [i34]Vladimir Braverman, Viska Wei, Samson Zhou:
Symmetric Norm Estimation and Regression on Sliding Windows. CoRR abs/2109.01635 (2021) - [i33]Zachary Izzo, Sandeep Silwal, Samson Zhou:
Dimensionality Reduction for Wasserstein Barycenter. CoRR abs/2110.08991 (2021) - [i32]Jon Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Learning-Augmented k-means Clustering. CoRR abs/2110.14094 (2021) - 2020
- [j3]Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Periodicity in Data Streams with Wildcards. Theory Comput. Syst. 64(1): 177-197 (2020) - [c25]Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin:
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. AISTATS 2020: 3263-3274 - [c24]Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford:
Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. APOCS 2020: 31-44 - [c23]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS 2020: 517-528 - [c22]Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou:
On Locally Decodable Codes in Resource Bounded Channels. ITC 2020: 16:1-16:23 - [c21]Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman:
Data-Independent Neural Pruning via Coresets. ICLR 2020 - [c20]Jeremiah Blocki, Seunghoon Lee, Samson Zhou:
Approximating Cumulative Pebbling Cost Is Unique Games Hard. ITCS 2020: 13:1-13:27 - [c19]Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou:
Computationally Data-Independent Memory Hard Functions. ITCS 2020: 36:1-36:28 - [c18]Grigory Yaroslavtsev, Samson Zhou:
Fast Fourier Sparsity Testing. SOSA 2020: 57-68 - [c17]Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou:
Non-adaptive adaptive sampling on turnstile streams. STOC 2020: 1251-1264 - [i31]Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou:
Non-Adaptive Adaptive Sampling on Turnstile Streams. CoRR abs/2004.10969 (2020) - [i30]Jeremiah Blocki, Benjamin Harsha, Samson Zhou:
On the Economics of Offline Password Cracking. CoRR abs/2006.05023 (2020) - [i29]Jeremiah Blocki, Seunghoon Lee, Samson Zhou:
On the Security of Proofs of Sequential Work in a Post-Quantum World. CoRR abs/2006.10972 (2020) - [i28]Agniva Chowdhury, Petros Drineas, David P. Woodruff, Samson Zhou:
Approximation Algorithms for Sparse Principal Component Analysis. CoRR abs/2006.12748 (2020) - [i27]Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy:
Data-Independent Structured Pruning of Neural Networks via Coresets. CoRR abs/2008.08316 (2020) - [i26]Yuichi Yoshida, Samson Zhou:
Sensitivity Analysis of the Maximum Matching Problem. CoRR abs/2009.04556 (2020) - [i25]David P. Woodruff, Samson Zhou:
Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. CoRR abs/2011.07471 (2020)
2010 – 2019
- 2019
- [j2]Marc Bury, Elena Grigorescu, Andrew McGregor, Morteza Monemizadeh, Chris Schwiegelshohn, Sofya Vorotnikova, Samson Zhou:
Structural Results on Matching Estimation with Applications to Streaming. Algorithmica 81(1): 367-392 (2019) - [j1]Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou:
Nearly Optimal Sparse Group Testing. IEEE Trans. Inf. Theory 65(5): 2760-2773 (2019) - [c16]Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou:
Improved Algorithms for Time Decay Streams. APPROX-RANDOM 2019: 27:1-27:17 - [c15]Grigory Yaroslavtsev, Samson Zhou:
Approximate F2-Sketching of Valuation Functions. APPROX-RANDOM 2019: 69:1-69:21 - [c14]Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou:
Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. CRYPTO (2) 2019: 573-607 - [c13]Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou:
Relaxed Locally Correctable Codes in Computationally Bounded Channels. ISIT 2019: 2414-2418 - [c12]Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou:
Adversarially Robust Submodular Maximization under Knapsack Constraints. KDD 2019: 148-156 - [i24]Jeremiah Blocki, Seunghoon Lee, Samson Zhou:
Approximating Cumulative Pebbling Cost is Unique Games Hard. CoRR abs/1904.08078 (2019) - [i23]Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou:
Adversarially Robust Submodular Maximization under Knapsack Constraints. CoRR abs/1905.02367 (2019) - [i22]Grigory Yaroslavtsev, Samson Zhou:
Approximate F2-Sketching of Valuation Functions. CoRR abs/1907.00524 (2019) - [i21]Ben Mussay, Samson Zhou, Vladimir Braverman, Dan Feldman:
On Activation Function Coresets for Network Pruning. CoRR abs/1907.04018 (2019) - [i20]Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou:
Improved Algorithms for Time Decay Streams. CoRR abs/1907.07574 (2019) - [i19]Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou:
On Locally Decodable Codes in Resource Bounded Channels. CoRR abs/1909.11245 (2019) - [i18]Dmitrii Avdiukhin, Grigory Yaroslavtsev, Samson Zhou:
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. CoRR abs/1910.05646 (2019) - [i17]Grigory Yaroslavtsev, Samson Zhou:
Fast Fourier Sparsity Testing. CoRR abs/1910.05686 (2019) - [i16]Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou:
Computationally Data-Independent Memory Hard Functions. CoRR abs/1911.06790 (2019) - [i15]Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford:
Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. CoRR abs/1911.06951 (2019) - 2018
- [b1]Samson Zhou:
Approximating Properties of Data Streams. Purdue University, USA, 2018 - [c11]Vladimir Braverman, Elena Grigorescu, Harry Lang, David P. Woodruff, Samson Zhou:
Nearly Optimal Distinct Elements and Heavy Hitters on Sliding Windows. APPROX-RANDOM 2018: 7:1-7:22 - [c10]Jeremiah Blocki, Ling Ren, Samson Zhou:
Bandwidth-Hard Functions: Reductions and Lower Bounds. CCS 2018: 1820-1836 - [c9]Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Periodicity in Data Streams with Wildcards. CSR 2018: 90-105 - [c8]Jeremiah Blocki, Samson Zhou:
On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling. Financial Cryptography 2018: 329-346 - [c7]Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou:
Brief Announcement: Relaxed Locally Correctable Codes in Computationally Bounded Channels. ICALP 2018: 106:1-106:4 - [c6]Jeremiah Blocki, Benjamin Harsha, Samson Zhou:
On the Economics of Offline Password Cracking. IEEE Symposium on Security and Privacy 2018: 853-871 - [i14]Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Periodicity in Data Streams with Wildcards. CoRR abs/1802.07375 (2018) - [i13]Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou:
Relaxed Locally Correctable Codes in Computationally Bounded Channels. CoRR abs/1803.05652 (2018) - [i12]Vladimir Braverman, Elena Grigorescu, Harry Lang, David P. Woodruff, Samson Zhou:
Nearly Optimal Distinct Elements and Heavy Hitters on Sliding Windows. CoRR abs/1805.00212 (2018) - [i11]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. CoRR abs/1805.03765 (2018) - [i10]Jeremiah Blocki, Ling Ren, Samson Zhou:
Bandwidth-Hard Functions: Reductions and Lower Bounds. IACR Cryptol. ePrint Arch. 2018: 221 (2018) - [i9]Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou:
Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. IACR Cryptol. ePrint Arch. 2018: 944 (2018) - 2017
- [c5]Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Longest alignment with edits in data streams. Allerton 2017: 405-412 - [c4]Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Streaming Periodicity with Mismatches. APPROX-RANDOM 2017: 42:1-42:21 - [c3]Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Streaming for Aibohphobes: Longest Palindrome with Mismatches. FSTTCS 2017: 31:1-31:13 - [c2]Jeremiah Blocki, Samson Zhou:
On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i. TCC (1) 2017: 445-465 - [i8]Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Streaming for Aibohphobes: Longest Palindrome with Mismatches. CoRR abs/1705.01887 (2017) - [i7]Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou:
Nearly Optimal Sparse Group Testing. CoRR abs/1708.03429 (2017) - [i6]Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Streaming Periodicity with Mismatches. CoRR abs/1708.04381 (2017) - [i5]Greg N. Frederickson, Samson Zhou:
Optimal Parametric Search for Path and Tree Partitioning. CoRR abs/1711.00599 (2017) - [i4]Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou:
Longest Alignment with Edits in Data Streams. CoRR abs/1711.04367 (2017) - [i3]Jeremiah Blocki, Samson Zhou:
On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i. IACR Cryptol. ePrint Arch. 2017: 442 (2017) - 2016
- [c1]Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou:
Nearly optimal sparse group testing. Allerton 2016: 401-408 - [i2]Elena Grigorescu, Morteza Monemizadeh, Samson Zhou:
Estimating Weighted Matchings in o(n) Space. CoRR abs/1604.07467 (2016) - [i1]Jeremiah Blocki, Samson Zhou:
On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling. CoRR abs/1609.04449 (2016)
Coauthor Index
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last updated on 2024-10-17 20:31 CEST by the dblp team
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