Michael J. Freedman
Computer Networks and Communications · 2000–2017
A researcher in the Science corpus: 18 papers; trusts 37 researchers and is trusted by 63 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 117 citations into it; #1,437 of 9,886 by trust here, #647 by citations
- Artificial Intelligence — 75 citations into it; #3,302 of 35,345 by trust here, #5,059 by citations
- Information Systems — 45 citations into it
- Privacy & Security — 27 citations into it; #266 of 709 by trust here, #434 by citations
- Statistical and Nonlinear Physics — 18 citations into it
- Computational Theory and Mathematics — 16 citations into it; #1,567 of 12,182 by trust here, #1,782 by citations
- Hardware and Architecture — 15 citations into it
- Signal Processing — 14 citations into it
Whom Michael J. Freedman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Moni Naor
- Ran Canetti
- Oded Goldreich
- Pascal Paillier
- Ion Stoica
- Benny Chor
- Eyal Kushilevitz
- Antony Ian Taylor Rowstron
- Helger Lipmaa
- Yan-Cheng Chang
Who trusts Michael J. Freedman overall
- Benny Pinkas
- Emiliano De Cristofaro
- Thomas Schneider
- Jaideep Vaidya
- Dan Boneh
- Carmit Hazay
- Yuval Ishai
- Vladimir Kolesnikov
- Arjun Narayan
- Keith B. Frikken
Papers from Michael J. Freedman's perspective
Ordered by how strongly the researchers Michael J. Freedman trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet: A large-scale hierarchical image database
- Untraceable electronic mail, return addresses, and digital pseudonyms
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Replication is not needed: single database, computationally-private information retrieval
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- New Directions in Cryptography
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
Their papers
- Efficient Private Matching and Set Intersection (2004) — 1,449 citations
- Keyword Search and Oblivious Pseudorandom Functions (2005) — 524 citations
- Ethane: taking control of the enterprise (2007) — 1,059 citations
- Live Video Analytics at Scale with Approximation and Delay-Tolerance (2017) — 485 citations
- Blockstack: A Global Naming and Storage System Secured by Blockchains (2016) — 520 citations
- CONIKS: Bringing Key Transparency to End Users (2015) — 318 citations
- Stronger Semantics for Low-Latency Geo-Replicated Storage (2013) — 306 citations
- Performance Isolation and Fairness for Multi-Tenant Cloud Storage (2012) — 313 citations
- Scalable Inference of Overlapping Communities (2012) — 118 citations
- Frenetic: a network programming language (2011) — 751 citations
- Don't settle for eventual: scalable causal consistency for wide-area storage with COPS (2011) — 701 citations
- Collaborative, Privacy-Preserving Data Aggregation at Scale (2010) — 64 citations
- SANE: A Protection Architecture for Enterprise Networks (2006) — 296 citations
- Democratizing Content Publication with Coral (2004) — 574 citations
- On-the-fly verification of rateless erasure codes for efficient content distribution (2004) — 417 citations
- Tarzan: a peer-to-peer anonymizing network layer (2002) — 823 citations
- A peer-to-peer anonymizing network layer (2002) — 59 citations
- The Free Haven Project: Distributed Anonymous Storage Service (2000) — 438 citations