Nikos Karampatziakis
Artificial Intelligence · 2010–2024
A researcher in the Science corpus: 9 papers; trusts 47 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 119 citations into it; #11,634 of 35,345 by trust here, #9,641 by citations
- Computer Vision and Pattern Recognition — 41 citations into it; #11,338 of 21,575 by trust here, #13,269 by citations
- Natural Language Processing — 34 citations into it
- Optimization & Training — 34 citations into it; #1,471 of 2,601 by trust here, #1,365 by citations
- Evaluation & Benchmarks — 26 citations into it
- Computer Networks and Communications — 17 citations into it
- Management Science and Operations Research — 16 citations into it; #3,031 of 11,946 by trust here, #3,705 by citations
- Computational Mechanics — 12 citations into it
Whom Nikos Karampatziakis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John C. Duchi
- Geoffrey E. Hinton
- J. Langford
- Robert E. Schapire
- David D. Lewis
- Yurii E. Nesterov
- Yoram Singer
- Yoav Freund
- Yoshua Bengio
- Alex Krizhevsky
Who trusts Nikos Karampatziakis overall
- Alekh Agarwal
- Alberto Bietti
- J. Langford
- Abhishek Bhowmick
- Tzu-Kuo Huang
- Deepesh Data
- John C. Duchi
- Zachary B. Charles
- Olivier Chapelle
- Miroslav Dud'ik
Papers from Nikos Karampatziakis's perspective
Ordered by how strongly the researchers Nikos Karampatziakis trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Online Importance Weight Aware Updates (2010) — 81 citations
- Efficient Optimal Learning for Contextual Bandits (2011) — 325 citations
- Least Squares Revisited: Scalable Approaches for Multi-class Prediction (2013) — 31 citations
- Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone (2024) — 2,340 citations
- AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (2023) — 404 citations
- Meet in the Middle: A New Pre-training Paradigm (2023) — 28 citations
- Lessons from Real-World Reinforcement Learning in a Customer Support Bot (2019) — 4 citations
- Gradient Coding: Avoiding Stragglers in Distributed Learning (2017) — 541 citations
- Gradient Coding (2016) — 78 citations