Alan Mislove
Artificial Intelligence · 2005–2019
A researcher in the Science corpus: 21 papers; trusts 51 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 125 citations into it; #22,506 of 35,345 by trust here, #10,065 by citations
- Sociology and Political Science — 82 citations into it; #16,505 of 22,756 by trust here, #5,110 by citations
- Information Systems — 71 citations into it; #1,429 of 8,771 by trust here, #312 by citations
- Statistical and Nonlinear Physics — 71 citations into it; #1,183 of 10,127 by trust here, #292 by citations
- Computer Networks and Communications — 48 citations into it; #2,280 of 9,886 by trust here, #1,370 by citations
- AI Ethics, Fairness & Society — 29 citations into it
- Computer Vision and Pattern Recognition — 25 citations into it
- Natural Language Processing — 18 citations into it; #3,006 of 5,688 by trust here, #2,695 by citations
Whom Alan Mislove trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- Aaron Clauset
- Yoshua Bengio
- Jon M. Kleinberg
- Antony Ian Taylor Rowstron
- Michael M. Mitzenmacher
- Alan M. Frieze
- Lada A. Adamic
- Diederik P. Kingma
- Duncan J. Watts
Who trusts Alan Mislove overall
- Momin M. Malik
- Jaewon Yang
- Neil Zhenqiang Gong
- Jacob Eisenstein
- Eliav Buchnik
- David M. Beskow
- Jürgen Pfeffer
- Jure Leskovec
- Binghui Wang
- Emilio Ferrara
Papers from Alan Mislove's perspective
Ordered by how strongly the researchers Alan Mislove trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Understanding the Demographics of Twitter Users (2011) — 920 citations
- Bias in Online Freelance Marketplaces: Evidence from TaskRabbit and Fiverr (2017) — 325 citations
- Peeking Beneath the Hood of Uber (2015) — 305 citations
- Measuring Price Discrimination and Steering on E-commerce Web Sites (2014) — 347 citations
- Of Pins and Tweets: Investigating How Users Behave Across Image- and Text-Based Social Networks (2014) — 78 citations
- Investigating sources of PII used in Facebook’s targeted advertising (2018) — 56 citations
- Analyzing facebook privacy settings: user expectations vs. reality (2011) — 601 citations
- Discrimination through Optimization (2019) — 231 citations
- Machine behaviour (2019) — 1,247 citations
- Potential for Discrimination in Online Targeted Advertising (2018) — 199 citations
- Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm (2017) — 813 citations
- Strength in Numbers: Robust Tamper Detection in Crowd Computations (2015) — 46 citations
- The Tweets They Are a-Changin: Evolution of Twitter Users and Behavior (2014) — 160 citations
- Towards Detecting Anomalous User Behavior in Online Social Networks (2014) — 299 citations
- Measuring personalization of web search (2013) — 451 citations
- An analysis of social network-based Sybil defenses (2010) — 421 citations
- You are who you know: inferring user profiles in online social networks (2010) — 796 citations
- On the evolution of user interaction in Facebook (2009) — 1,561 citations
- Growth of the flickr social network (2008) — 473 citations
- Measurement and analysis of online social networks (2007) — 3,406 citations