Ece Kamar
Artificial Intelligence · 2012–2023
A researcher in the Science corpus: 19 papers; trusts 198 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 255 citations into it; #8,791 of 35,345 by trust here, #2,453 by citations
- Safety, Robustness & Interpretability — 122 citations into it; #1,505 of 2,251 by trust here, #556 by citations
- Computer Vision and Pattern Recognition — 99 citations into it; #18,470 of 21,575 by trust here, #18,266 by citations
- Natural Language Processing — 86 citations into it
- Evaluation & Benchmarks — 59 citations into it
- Sociology and Political Science — 49 citations into it
- Safety Research — 39 citations into it
- Computer Science Applications — 35 citations into it
Whom Ece Kamar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Marco Tulio Ribeiro
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Kaiming He
- Ilya Sutskever
- Jimmy Ba
- Jia Deng
Who trusts Ece Kamar overall
- Besmira Nushi
- Adam Marcus
- Panagiotis G. Ipeirotis
- Gagan Bansal
- Olga Russakovsky
- Zana Buçinca
- Sina Mohseni
- Ranjay Krishna
- Ben Green
- Nadia Burkart
Papers from Ece Kamar's perspective
Ordered by how strongly the researchers Ece Kamar 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Sparks of Artificial General Intelligence: Early experiments with GPT-4 (2023) — 4,318 citations
- Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs (2021) — 98 citations
- ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection (2022) — 626 citations
- Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance (2020) — 965 citations
- Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration (2016) — 160 citations
- Interpretable & Explorable Approximations of Black Box Models (2017) — 259 citations
- Designing an Online Infrastructure for Collecting AI Data From People With Disabilities (2021) — 56 citations
- An Empirical Analysis of Backward Compatibility in Machine Learning Systems (2020) — 53 citations
- Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance (2019) — 564 citations
- Machine behaviour (2019) — 1,247 citations
- Faithful and Customizable Explanations of Black Box Models (2019) — 305 citations
- Software Engineering for Machine Learning: A Case Study (2019) — 1,033 citations
- Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff (2019) — 344 citations
- Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure (2018) — 155 citations
- Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets (2017) — 273 citations
- Communicating Context to the Crowd for Complex Writing Tasks (2017) — 37 citations
- On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems (2016) — 83 citations
- Interactive Teaching Strategies for Agent Training (2016) — 116 citations
- Combining human and machine intelligence in large-scale crowdsourcing (2012) — 412 citations