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Partitioned Learned Bloom Filter.
Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher: Partitioned Learned Bloom Filter. CoRR abs/2006.03176 (2020)
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Faster and More Accurate Measurement through Additive-Error Counters.
Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik: Faster and More Accurate Measurement through Additive-Error Counters. CoRR abs/2004.10332 (2020)
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Joint Alignment From Pairwise Differences with a Noisy Oracle.
Michael Mitzenmacher, Charalampos E. Tsourakakis: Joint Alignment From Pairwise Differences with a Noisy Oracle. CoRR abs/2003.06076 (2020)
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Algorithms with Predictions.
Michael Mitzenmacher, Sergei Vassilvitskii: Algorithms with Predictions. Beyond the Worst-Case Analysis of Algorithms 2020: 646-662
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When Simple Hash Functions Suffice.
Kai-Min Chung, Michael Mitzenmacher, Salil P. Vadhan: When Simple Hash Functions Suffice. Beyond the Worst-Case Analysis of Algorithms 2020: 567-585
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Clustering with a faulty oracle.
Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis: Clustering with a faulty oracle. WWW 2020: 2831-2834
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Dynamic algorithms for LIS and distance to monotonicity.
Michael Mitzenmacher, Saeed Seddighin: Dynamic algorithms for LIS and distance to monotonicity. STOC 2020: 671-684
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PINT: Probabilistic In-band Network Telemetry.
Ran Ben Basat, Sivaramakrishnan Ramanathan, Yuliang Li, Gianni Antichi, Minlan Yu, Michael Mitzenmacher: PINT: Probabilistic In-band Network Telemetry. SIGCOMM 2020: 662-680
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Optimal Learning of Joint Alignments with a Faulty Oracle.
Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis: Optimal Learning of Joint Alignments with a Faulty Oracle. ITA 2020: 1-10
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Optimal Learning of Joint Alignments with a Faulty Oracle.
Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis: Optimal Learning of Joint Alignments with a Faulty Oracle. ISIT 2020: 2492-2497
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Scheduling with Predictions and the Price of Misprediction.
Michael Mitzenmacher: Scheduling with Predictions and the Price of Misprediction. ITCS 2020: 14:1-14:18
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Faster and More Accurate Measurement through Additive-Error Counters.
Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik: Faster and More Accurate Measurement through Additive-Error Counters. INFOCOM 2020: 1251-1260
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DISCOvering the heavy hitters with disaggregated sketches.
Valerio Bruschi, Ran Ben Basat, Zaoxing Liu, Gianni Antichi, Giuseppe Bianchi, Michael Mitzenmacher: DISCOvering the heavy hitters with disaggregated sketches. CoNEXT 2020: 536-537
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Detecting routing loops in the data plane.
Jan Kucera, Ran Ben Basat, Mário Kuka, Gianni Antichi, Minlan Yu, Michael Mitzenmacher: Detecting routing loops in the data plane. CoNEXT 2020: 466-473
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Prophets, Secretaries, and Maximizing the Probability of Choosing the Best.
Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher: Prophets, Secretaries, and Maximizing the Probability of Choosing the Best. AISTATS 2020: 3717-3727
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Adaptive Cuckoo Filters.
Michael Mitzenmacher, Salvatore Pontarelli, Pedro Reviriego: Adaptive Cuckoo Filters. ACM J. Exp. Algorithmics 25: 1-20 (2020)
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Zero-CPU Collection with Direct Telemetry Access.
Jonatan Langlet, Ran Ben Basat, Sivaramakrishnan Ramanathan, Gabriele Oliaro, Michael Mitzenmacher, Minlan Yu, Gianni Antichi: Zero-CPU Collection with Direct Telemetry Access. CoRR abs/2110.05438 (2021)
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Uniform Bounds for Scheduling with Job Size Estimates.
Ziv Scully, Isaac Grosof, Michael Mitzenmacher: Uniform Bounds for Scheduling with Job Size Estimates. CoRR abs/2110.00633 (2021)
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Communication-Efficient Federated Learning via Robust Distributed Mean...
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher: Communication-Efficient Federated Learning via Robust Distributed Mean Estimation. CoRR...
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Gradient Disaggregation: Breaking Privacy in Federated Learning by...
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher: Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix. CoRR...
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DRIVE: One-bit Distributed Mean Estimation.
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher: DRIVE: One-bit Distributed Mean Estimation. CoRR abs/2105.08339 (2021)
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SALSA: Self-Adjusting Lean Streaming Analytics.
Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik: SALSA: Self-Adjusting Lean Streaming Analytics. CoRR abs/2102.12531 (2021)
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Dynamic Longest Increasing Subsequence and the Erdös-Szekeres Partitioning...
Michael Mitzenmacher, Saeed Seddighin: Dynamic Longest Increasing Subsequence and the Erdös-Szekeres Partitioning Problem. CoRR abs/2101.07360 (2021)
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Improved Sublinear Time Algorithm for Longest Increasing Subsequence.
Michael Mitzenmacher, Saeed Seddighin: Improved Sublinear Time Algorithm for Longest Increasing Subsequence. SODA 2021: 1934-1947
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DRIVE: One-bit Distributed Mean Estimation.
Shay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher: DRIVE: One-bit Distributed Mean Estimation. NeurIPS 2021: 362-377
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Gradient Disaggregation: Breaking Privacy in Federated Learning by...
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher: Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix. ICML...
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Putting the "Learning" into Learning-Augmented Algorithms for Frequency...
Elbert Du, Franklyn Wang, Michael Mitzenmacher: Putting the "Learning" into Learning-Augmented Algorithms for Frequency Estimation. ICML 2021: 2860-2869
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Partitioned Learned Bloom Filters.
Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska: Partitioned Learned Bloom Filters. ICLR 2021
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SALSA: Self-Adjusting Lean Streaming Analytics.
Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik: SALSA: Self-Adjusting Lean Streaming Analytics. ICDE 2021: 864-875
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How to Send a Real Number Using a Single Bit (And Some Shared Randomness).
Ran Ben Basat, Michael Mitzenmacher, Shay Vargaftik: How to Send a Real Number Using a Single Bit (And Some Shared Randomness). ICALP 2021: 25:1-25:20
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Zero-CPU Collection with Direct Telemetry Access.
Jonatan Langlet, Ran Ben-Basat, Sivaramakrishnan Ramanathan, Gabriele Oliaro, Michael Mitzenmacher, Minlan Yu, Gianni Antichi: Zero-CPU Collection with Direct Telemetry Access. HotNets 2021: 108-115
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Queues with Small Advice.
Michael Mitzenmacher: Queues with Small Advice. ACDA 2021: 1-12
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Proteus: A Self-Designing Range Filter.
Eric R. Knorr, Baptiste Lemaire, Andrew Lim, Siqiang Luo, Huanchen Zhang, Stratos Idreos, Michael Mitzenmacher: Proteus: A Self-Designing Range Filter. CoRR abs/2207.01503 (2022)
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QUIC-FL: Quick Unbiased Compression for Federated Learning.
Ran Ben Basat, Shay Vargaftik, Amit Portnoy, Gil Einziger, Yaniv Ben-Itzhak, Michael Mitzenmacher: QUIC-FL: Quick Unbiased Compression for Federated Learning. CoRR abs/2205.13341 (2022)
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FRANCIS: Fast Reaction Algorithms for Network Coordination In Switches.
Wenchen Han, Vic Feng, Gregory Schwartzman, Michael Mitzenmacher, Minlan Yu, Ran Ben-Basat: FRANCIS: Fast Reaction Algorithms for Network Coordination In Switches. CoRR abs/2204.14138 (2022)
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Tabula: Efficiently Computing Nonlinear Activation Functions for Secure...
Maximilian Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks: Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference. CoRR...
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Incentive Compatible Queues Without Money.
Isaac Grosof, Michael Mitzenmacher: Incentive Compatible Queues Without Money. CoRR abs/2202.05747 (2022)
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Direct Telemetry Access.
Jonatan Langlet, Ran Ben Basat, Sivaramakrishnan Ramanathan, Gabriele Oliaro, Michael Mitzenmacher, Minlan Yu, Gianni Antichi: Direct Telemetry Access. CoRR abs/2202.02270 (2022)
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Proteus: A Self-Designing Range Filter.
Eric R. Knorr, Baptiste Lemaire, Andrew Lim, Siqiang Luo, Huanchen Zhang, Stratos Idreos, Michael Mitzenmacher: Proteus: A Self-Designing Range Filter. SIGMOD Conference 2022: 1670-1684
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Algorithmic Tools for Understanding the Motif Structure of Networks.
Tianyi Chen, Brian Matejek, Michael Mitzenmacher, Charalampos E. Tsourakakis: Algorithmic Tools for Understanding the Motif Structure of Networks. ECML/PKDD (2) 2022: 3-19
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Uniform Bounds for Scheduling with Job Size Estimates.
Ziv Scully, Isaac Grosof, Michael Mitzenmacher: Uniform Bounds for Scheduling with Job Size Estimates. ITCS 2022: 114:1-114:30
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EDEN: Communication-Efficient and Robust Distributed Mean Estimation for...
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher: EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning. ICML...
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The Supermarket Model With Known and Predicted Service Times.
Michael Mitzenmacher, Matteo Dell'Amico: The Supermarket Model With Known and Predicted Service Times. IEEE Trans. Parallel Distributed Syst. 33(11): 2740-2751 (2022)
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Can Learned Models Replace Hash Functions?
Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, Tim Kraska: Can Learned Models Replace Hash Functions? Proc. VLDB Endow. 16(3): 532-545 (2022)
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SNARF: A Learning-Enhanced Range Filter.
Kapil Vaidya, Tim Kraska, Subarna Chatterjee, Eric R. Knorr, Michael Mitzenmacher, Stratos Idreos: SNARF: A Learning-Enhanced Range Filter. Proc. VLDB Endow. 15(8): 1632-1644 (2022)
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Algorithms with predictions.
Michael Mitzenmacher, Sergei Vassilvitskii: Algorithms with predictions. Commun. ACM 65(7): 33-35 (2022)
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THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic...
Minghao Li, Ran Ben Basat, Shay Vargaftik, ChonLam Lao, Kevin Xu, Xinran Tang, Michael Mitzenmacher, Minlan Yu: THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression. CoRR...
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Direct Telemetry Access.
Jonatan Langlet, Ran Ben Basat, Gabriele Oliaro, Michael Mitzenmacher, Minlan Yu, Gianni Antichi: Direct Telemetry Access. SIGCOMM 2023: 832-849
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SkipPredict: When to Invest in Predictions for Scheduling.
Rana Shahout, Michael Mitzenmacher: SkipPredict: When to Invest in Predictions for Scheduling. CoRR abs/2402.03564 (2024)
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Optimal and Near-Optimal Adaptive Vector Quantization.
Ran Ben-Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Shay Vargaftik: Optimal and Near-Optimal Adaptive Vector Quantization. CoRR abs/2402.03158 (2024)
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