Diego Klabjan
Artificial Intelligence · 2006–2020
A researcher in the Science corpus: 6 papers; trusts 47 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 41 citations into it; #11,137 of 35,345 by trust here, #20,836 by citations
- Computer Vision and Pattern Recognition — 23 citations into it
- Optimization & Training — 15 citations into it
- Computational Mechanics — 8 citations into it
- Management Science and Operations Research — 8 citations into it; #2,822 of 11,946 by trust here, #6,024 by citations
- Meta & Continual Learning — 8 citations into it
- Statistics and Probability — 5 citations into it
Whom Diego Klabjan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Thomas C. Rindflesch
- Yurii E. Nesterov
- Ilya Sutskever
- Ni Lao
- Soham De
- Yoshua Bengio
- Yann LeCun
- Martin Jaggi
Who trusts Diego Klabjan overall
- Matthew F. Dixon
- Avraam Tsantekidis
- A. Ozbayoglu
- Omer Berat Sezer
- Sid Ghoshal
- Bernardo Almada-Lobo
- M. Ugur Gudelek
- Luigi Troiano
- Eleonora Borgia
- Fuli Feng
Papers from Diego Klabjan's perspective
Ordered by how strongly the researchers Diego Klabjan 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Efficient Architecture Search for Continual Learning (2020) — 75 citations
- Classification-based financial markets prediction using deep neural networks (2016) — 199 citations
- Guns and guardians: Comparative cluster analysis and behavioral profiling in destiny (2016) — 31 citations
- A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations (2018)
- Single machine multi-product capacitated lot sizing with sequence-dependent setups (2007) — 132 citations
- Warehousing and Analyzing Massive RFID Data Sets (2006) — 303 citations