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Michael Mitzenmacher
Michael M. Mitzenmacher
Person information
- affiliation: Harvard School of Engineering and Applied Sciences, Cambridge, MA, USA
- award (2020): Paris Kanellakis Award
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2020 – today
- 2025
- [j92]Michael B. Dillencourt, Michael T. Goodrich
, Michael Mitzenmacher:
Leveraging parameterized Chernoff bounds for simplified algorithm analyses. Inf. Process. Lett. 187: 106516 (2025) - [c181]William Kuszmaul, Michael Mitzenmacher:
Efficient d-ary Cuckoo Hashing at High Load Factors by Bubbling Up. SODA 2025: 3931-3952 - 2024
- [c180]Wenchen Han
, Shay Vargaftik
, Michael Mitzenmacher
, Brad Karp
, Ran Ben Basat
:
Beyond Throughput and Compression Ratios: Towards High End-to-end Utility of Gradient Compression. HotNets 2024: 186-194 - [c179]Ran Ben-Basat, Shay Vargaftik, Amit Portnoy, Gil Einziger, Yaniv Ben-Itzhak, Michael Mitzenmacher:
Accelerating Federated Learning with Quick Distributed Mean Estimation. ICML 2024 - [c178]Ran Ben-Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Shay Vargaftik:
Optimal and Approximate Adaptive Stochastic Quantization. NeurIPS 2024 - [c177]Rana Shahout, Michael Mitzenmacher:
SkipPredict: When to Invest in Predictions for Scheduling. NeurIPS 2024 - [c176]Minghao Li, Ran Ben Basat, Shay Vargaftik, ChonLam Lao, Kevin Xu, Michael Mitzenmacher, Minlan Yu:
THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression. NSDI 2024 - [i102]Ran Ben-Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Shay Vargaftik:
Optimal and Near-Optimal Adaptive Vector Quantization. CoRR abs/2402.03158 (2024) - [i101]Rana Shahout, Michael Mitzenmacher:
SkipPredict: When to Invest in Predictions for Scheduling. CoRR abs/2402.03564 (2024) - [i100]Rana Shahout, Michael Mitzenmacher:
Learning-Based Heavy Hitters and Flow Frequency Estimation in Streams. CoRR abs/2406.16270 (2024) - [i99]Wenchen Han, Shay Vargaftik, Michael Mitzenmacher, Brad Karp, Ran Ben Basat:
Beyond Throughput and Compression Ratios: Towards High End-to-end Utility of Gradient Compression. CoRR abs/2407.01378 (2024) - [i98]Rana Shahout, Ibrahim Sabek, Michael Mitzenmacher:
Learning-Augmented Frequency Estimation in Sliding Windows. CoRR abs/2409.11516 (2024) - [i97]Rana Shahout, Eran Malach, Chunwei Liu, Weifan Jiang, Minlan Yu, Michael Mitzenmacher:
Don't Stop Me Now: Embedding Based Scheduling for LLMs. CoRR abs/2410.01035 (2024) - [i96]Rana Shahout, Cong Liang, Shiji Xin, Qianru Lao, Yong Cui, Minlan Yu, Michael Mitzenmacher:
Fast Inference for Augmented Large Language Models. CoRR abs/2410.18248 (2024) - 2023
- [j91]Elbert Du, Michael Mitzenmacher, David P. Woodruff, Guang Yang:
Separating k-Player from t-Player One-Way Communication, with Applications to Data Streams. Theory Comput. 19: 1-44 (2023) - [c175]Jonatan Langlet
, Ran Ben Basat
, Gabriele Oliaro
, Michael Mitzenmacher
, Minlan Yu
, Gianni Antichi
:
Direct Telemetry Access. SIGCOMM 2023: 832-849 - [i95]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 abs/2302.08545 (2023) - 2022
- [j90]Michael Mitzenmacher, Sergei Vassilvitskii:
Algorithms with predictions. Commun. ACM 65(7): 33-35 (2022) - [j89]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) - [j88]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) - [j87]Michael Mitzenmacher, Matteo Dell'Amico
:
The Supermarket Model With Known and Predicted Service Times. IEEE Trans. Parallel Distributed Syst. 33(11): 2740-2751 (2022) - [c174]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 2022: 21984-22014 - [c173]Ziv Scully
, Isaac Grosof
, Michael Mitzenmacher:
Uniform Bounds for Scheduling with Job Size Estimates. ITCS 2022: 114:1-114:30 - [c172]Tianyi Chen, Brian Matejek, Michael Mitzenmacher, Charalampos E. Tsourakakis:
Algorithmic Tools for Understanding the Motif Structure of Networks. ECML/PKDD (2) 2022: 3-19 - [c171]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 - [i94]Jonatan Langlet, Ran Ben Basat, Sivaramakrishnan Ramanathan, Gabriele Oliaro, Michael Mitzenmacher, Minlan Yu, Gianni Antichi:
Direct Telemetry Access. CoRR abs/2202.02270 (2022) - [i93]Isaac Grosof, Michael Mitzenmacher:
Incentive Compatible Queues Without Money. CoRR abs/2202.05747 (2022) - [i92]Maximilian Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks:
Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference. CoRR abs/2203.02833 (2022) - [i91]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) - [i90]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) - [i89]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) - 2021
- [c170]Michael Mitzenmacher:
Queues with Small Advice. ACDA 2021: 1-12 - [c169]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 - [c168]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 - [c167]Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik:
SALSA: Self-Adjusting Lean Streaming Analytics. ICDE 2021: 864-875 - [c166]Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska:
Partitioned Learned Bloom Filters. ICLR 2021 - [c165]Elbert Du, Franklyn Wang, Michael Mitzenmacher:
Putting the "Learning" into Learning-Augmented Algorithms for Frequency Estimation. ICML 2021: 2860-2869 - [c164]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 2021: 5959-5968 - [c163]Shay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher:
DRIVE: One-bit Distributed Mean Estimation. NeurIPS 2021: 362-377 - [c162]Michael Mitzenmacher, Saeed Seddighin:
Improved Sublinear Time Algorithm for Longest Increasing Subsequence. SODA 2021: 1934-1947 - [i88]Michael Mitzenmacher, Saeed Seddighin:
Dynamic Longest Increasing Subsequence and the Erdös-Szekeres Partitioning Problem. CoRR abs/2101.07360 (2021) - [i87]Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik:
SALSA: Self-Adjusting Lean Streaming Analytics. CoRR abs/2102.12531 (2021) - [i86]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) - [i85]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 abs/2106.06089 (2021) - [i84]Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher:
Communication-Efficient Federated Learning via Robust Distributed Mean Estimation. CoRR abs/2108.08842 (2021) - [i83]Ziv Scully, Isaac Grosof, Michael Mitzenmacher:
Uniform Bounds for Scheduling with Job Size Estimates. CoRR abs/2110.00633 (2021) - [i82]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) - 2020
- [j86]Michael Mitzenmacher, Salvatore Pontarelli, Pedro Reviriego
:
Adaptive Cuckoo Filters. ACM J. Exp. Algorithmics 25: 1-20 (2020) - [c161]Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher:
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best. AISTATS 2020: 3717-3727 - [c160]Jan Kucera
, Ran Ben Basat, Mário Kuka, Gianni Antichi
, Minlan Yu, Michael Mitzenmacher:
Detecting routing loops in the data plane. CoNEXT 2020: 466-473 - [c159]Valerio Bruschi, Ran Ben Basat, Zaoxing Liu, Gianni Antichi
, Giuseppe Bianchi, Michael Mitzenmacher:
DISCOvering the heavy hitters with disaggregated sketches. CoNEXT 2020: 536-537 - [c158]Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik:
Faster and More Accurate Measurement through Additive-Error Counters. INFOCOM 2020: 1251-1260 - [c157]Michael Mitzenmacher:
Scheduling with Predictions and the Price of Misprediction. ITCS 2020: 14:1-14:18 - [c156]Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis:
Optimal Learning of Joint Alignments with a Faulty Oracle. ISIT 2020: 2492-2497 - [c155]Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis:
Optimal Learning of Joint Alignments with a Faulty Oracle. ITA 2020: 1-10 - [c154]Ran Ben Basat, Sivaramakrishnan Ramanathan, Yuliang Li, Gianni Antichi
, Minlan Yu, Michael Mitzenmacher:
PINT: Probabilistic In-band Network Telemetry. SIGCOMM 2020: 662-680 - [c153]Michael Mitzenmacher, Saeed Seddighin
:
Dynamic algorithms for LIS and distance to monotonicity. STOC 2020: 671-684 - [c152]Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis:
Clustering with a faulty oracle. WWW 2020: 2831-2834 - [p5]Kai-Min Chung, Michael Mitzenmacher, Salil P. Vadhan:
When Simple Hash Functions Suffice. Beyond the Worst-Case Analysis of Algorithms 2020: 567-585 - [p4]Michael Mitzenmacher, Sergei Vassilvitskii:
Algorithms with Predictions. Beyond the Worst-Case Analysis of Algorithms 2020: 646-662 - [i81]Michael Mitzenmacher, Charalampos E. Tsourakakis:
Joint Alignment From Pairwise Differences with a Noisy Oracle. CoRR abs/2003.06076 (2020) - [i80]Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik:
Faster and More Accurate Measurement through Additive-Error Counters. CoRR abs/2004.10332 (2020) - [i79]Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher:
Partitioned Learned Bloom Filter. CoRR abs/2006.03176 (2020) - [i78]Michael Mitzenmacher, Sergei Vassilvitskii:
Algorithms with Predictions. CoRR abs/2006.09123 (2020) - [i77]Michael Mitzenmacher:
Queues with Small Advice. CoRR abs/2006.15463 (2020) - [i76]Ran Ben Basat, Sivaramakrishnan Ramanathan, Yuliang Li, Gianni Antichi, Minlan Yu, Michael Mitzenmacher:
PINT: Probabilistic In-band Network Telemetry. CoRR abs/2007.03731 (2020) - [i75]Ran Ben-Basat, Michael Mitzenmacher, Shay Vargaftik:
How to send a real number using a single bit (and some shared randomness). CoRR abs/2010.02331 (2020) - [i74]Michael Mitzenmacher, Saeed Seddighin:
Erdös-Szekeres Partitioning Problem. CoRR abs/2011.10870 (2020)
2010 – 2019
- 2019
- [j85]John W. Byers, Michael Luby, Michael Mitzenmacher:
A digital fountain retrospective. Comput. Commun. Rev. 49(5): 82-85 (2019) - [c151]Hossein Esfandiari, Mohammad Taghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher:
Online Pandora's Boxes and Bandits. AAAI 2019: 1885-1892 - [c150]Michael Mitzenmacher:
Arithmetic Progression Hypergraphs: Examining the Second Moment Method. ANALCO 2019: 127-134 - [c149]Michael Mitzenmacher, Tom Morgan:
Robust Set Reconciliation via Locality Sensitive Hashing. PODS 2019: 164-181 - [e5]Jeremy T. Fineman, Michael Mitzenmacher:
2nd Symposium on Simplicity in Algorithms, SOSA 2019, January 8-9, 2019, San Diego, CA, USA. OASIcs 69, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2019, ISBN 978-3-95977-099-6 [contents] - [i73]Michael Mitzenmacher:
A Model for Learned Bloom Filters, and Optimizing by Sandwiching. CoRR abs/1901.00902 (2019) - [i72]Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher:
Online Pandora's Boxes and Bandits. CoRR abs/1901.10698 (2019) - [i71]Michael Mitzenmacher:
Scheduling with Predictions and the Price of Misprediction. CoRR abs/1902.00732 (2019) - [i70]Michael Mitzenmacher:
The Supermarket Model with Known and Predicted Service Times. CoRR abs/1905.12155 (2019) - [i69]Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis:
Optimal Learning of Joint Alignments with a Faulty Oracle. CoRR abs/1909.09912 (2019) - [i68]Hossein Esfandiari, Mohammad Taghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher:
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best. CoRR abs/1910.03798 (2019) - 2018
- [j84]Michael Mitzenmacher, Rasmus Pagh:
Simple multi-party set reconciliation. Distributed Comput. 31(6): 441-453 (2018) - [j83]Salvatore Pontarelli
, Pedro Reviriego
, Michael Mitzenmacher:
EMOMA: Exact Match in One Memory Access. IEEE Trans. Knowl. Data Eng. 30(11): 2120-2133 (2018) - [j82]Michael Mitzenmacher, Rajmohan Rajaraman, Scott T. Roche:
Better Bounds for Coalescing-Branching Random Walks. ACM Trans. Parallel Comput. 5(1): 2:1-2:23 (2018) - [c148]Michael Mitzenmacher, Salvatore Pontarelli, Pedro Reviriego:
Adaptive Cuckoo Filters. ALENEX 2018: 36-47 - [c147]Max Hopkins, Michael Mitzenmacher, Sebastian Wagner-Carena:
Simulated Annealing for JPEG Quantization. DCC 2018: 412 - [c146]Hossein Esfandiari, Michael Mitzenmacher:
Metric Sublinear Algorithms via Linear Sampling. FOCS 2018: 11-22 - [c145]Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander M. Rush
, Gu-Yeon Wei, David Brooks:
Weightless: Lossy weight encoding for deep neural network compression. ICLR (Workshop) 2018 - [c144]Brandon Reagen, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander M. Rush
, Gu-Yeon Wei, David Brooks:
Weightless: Lossy weight encoding for deep neural network compression. ICML 2018: 4321-4330 - [c143]Michael Mitzenmacher:
A Model for Learned Bloom Filters and Optimizing by Sandwiching. NeurIPS 2018: 462-471 - [c142]Diana Cai, Michael Mitzenmacher, Ryan P. Adams:
A Bayesian Nonparametric View on Count-Min Sketch. NeurIPS 2018: 8782-8791 - [c141]Michael Mitzenmacher, Tom Morgan:
Reconciling Graphs and Sets of Sets. PODS 2018: 33-47 - [c140]Michael Mitzenmacher, Konstantinos Panagiotou, Stefan Walzer
:
Load Thresholds for Cuckoo Hashing with Double Hashing. SWAT 2018: 29:1-29:9 - [c139]Michael Mitzenmacher, Charalampos E. Tsourakakis:
Joint Alignment from Pairwise Differences with a Noisy Oracle. WAW 2018: 59-69 - [r2]Michael Mitzenmacher:
Bloom Filters. Encyclopedia of Database Systems (2nd ed.) 2018 - [i67]Michael Mitzenmacher:
A Model for Learned Bloom Filters and Related Structures. CoRR abs/1802.00884 (2018) - [i66]Michael Mitzenmacher:
Optimizing Learned Bloom Filters by Sandwiching. CoRR abs/1803.01474 (2018) - [i65]Hossein Esfandiari, Michael Mitzenmacher:
Metric Sublinear Algorithms via Linear Sampling. CoRR abs/1807.09302 (2018) - [i64]Michael Mitzenmacher, Tom Morgan:
Directory Reconciliation. CoRR abs/1807.09686 (2018) - [i63]Michael Mitzenmacher, Tom Morgan:
Robust Set Reconciliation via Locality Sensitive Hashing. CoRR abs/1807.09694 (2018) - 2017
- [j81]Michael Mitzenmacher:
Technical Perspective: Building a better hash function. Commun. ACM 60(7): 93 (2017) - [c138]Michael T. Goodrich, Evgenios M. Kornaropoulos
, Michael Mitzenmacher, Roberto Tamassia
:
Auditable Data Structures. EuroS&P 2017: 285-300 - [c137]Brian Matejek, Daniel Haehn
, Fritz Lekschas
, Michael Mitzenmacher, Hanspeter Pfister
:
Compresso: Efficient Compression of Segmentation Data for Connectomics. MICCAI (1) 2017: 781-788 - [c136]David Eppstein, Michael T. Goodrich, Michael Mitzenmacher, Manuel R. Torres:
2-3 Cuckoo Filters for Faster Triangle Listing and Set Intersection. PODS 2017: 247-260 - [c135]Charalampos E. Tsourakakis
, Jakub Pachocki, Michael Mitzenmacher:
Scalable Motif-aware Graph Clustering. WWW 2017: 1451-1460 - [i62]Michael Mitzenmacher, Salvatore Pontarelli, Pedro Reviriego:
Adaptive Cuckoo Filters. CoRR abs/1704.06818 (2017) - [i61]Michael Mitzenmacher, Tom Morgan:
Reconciling Graphs and Sets of Sets. CoRR abs/1707.05867 (2017) - [i60]Max Hopkins, Michael Mitzenmacher, Sebastian Wagner-Carena:
Simulated Annealing for JPEG Quantization. CoRR abs/1709.00649 (2017) - [i59]Salvatore Pontarelli, Pedro Reviriego, Michael Mitzenmacher:
EMOMA: Exact Match in One Memory Access. CoRR abs/1709.04711 (2017) - [i58]Charalampos E. Tsourakakis, Michael Mitzenmacher, Jaroslaw Blasiok, Ben Lawson, Preetum Nakkiran, Vasileios Nakos:
Predicting Positive and Negative Links with Noisy Queries: Theory & Practice. CoRR abs/1709.07308 (2017) - [i57]Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David M. Brooks:
Weightless: Lossy Weight Encoding For Deep Neural Network Compression. CoRR abs/1711.04686 (2017) - [i56]Michael Mitzenmacher:
Arithmetic Progression Hypergraphs: Examining the Second Moment Method. CoRR abs/1712.01781 (2017) - [i55]Martin Dietzfelbinger, Michael Mitzenmacher, Rasmus Pagh, David P. Woodruff, Martin Aumüller:
Theory and Applications of Hashing (Dagstuhl Seminar 17181). Dagstuhl Reports 7(5): 1-21 (2017) - 2016
- [j80]Michael Mitzenmacher, Justin Thaler:
Technical Perspective: Catching lies (and mistakes) in offloaded computation. Commun. ACM 59(2): 102 (2016) - [j79]Michael Mitzenmacher, Vikram Nathan:
Hardness of peeling with stashes. Inf. Process. Lett. 116(11): 682-688 (2016) - [j78]Yakir A. Reshef, David N. Reshef, Hilary K. Finucane, Pardis C. Sabeti, Michael Mitzenmacher:
Measuring Dependence Powerfully and Equitably. J. Mach. Learn. Res. 17: 212:1-212:63 (2016) - [j77]Michael Mitzenmacher, Pedro Reviriego
, Salvatore Pontarelli:
OMASS: One Memory Access Set Separation. IEEE Trans. Knowl. Data Eng. 28(7): 1940-1943 (2016) - [j76]Jiayang Jiang, Michael Mitzenmacher, Justin Thaler:
Parallel Peeling Algorithms. ACM Trans. Parallel Comput. 3(1): 7:1-7:27 (2016) - [c134]Michael Mitzenmacher:
Analyzing distributed Join-Idle-Queue: A fluid limit approach. Allerton 2016: 312-318 - [c133]Michael Mitzenmacher:
More Analysis of Double Hashing for Balanced Allocations. ANALCO 2016: 1-9 - [c132]Michael Mitzenmacher:
A New Approach to Analyzing Robin Hood Hashing. ANALCO 2016: 10-24 - [c131]Michael T. Goodrich, Evgenios M. Kornaropoulos
, Michael Mitzenmacher, Roberto Tamassia
:
More Practical and Secure History-Independent Hash Tables. ESORICS (2) 2016: 20-38 - [c130]Meena Boppana, Rani Hod
, Michael Mitzenmacher, Tom Morgan:
Voronoi Choice Games. ICALP 2016: 23:1-23:13 - [c129]David Eppstein, Michael T. Goodrich, Jenny Lam, Nil Mamano, Michael Mitzenmacher, Manuel R. Torres:
Models and Algorithms for Graph Watermarking. ISC 2016: 283-301 - [c128]