Jaka Demsar
Artificial Intelligence · 2004–2019
A researcher in the Science corpus: 8 papers; trusts 41 researchers and is trusted by 609 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 36 citations into it; #14,915 of 35,345 by trust here, #17,412 by citations
- Molecular Biology — 17 citations into it; #6,533 of 17,773 by trust here, #16,150 by citations
- Statistics and Probability — 17 citations into it
- Evaluation & Benchmarks — 11 citations into it; #23 of 3,147 by trust here, #314 by citations
- Information Systems — 7 citations into it
- Management Science and Operations Research — 7 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it; #7,191 of 21,575 by trust here, #9,722 by citations
- Statistical and Nonlinear Physics — 6 citations into it; #4,536 of 10,127 by trust here, #8,564 by citations
Whom Jaka Demsar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- William S. Cleveland
- Thomas G. Dietterich
- Pat Langley
- Albert Bifet
- João Gama
- Lloyd S. Shapley
- Usama M. Fayyad
- John K. Kruschke
- Igor Kononenko
- Gerhard Widmer
Who trusts Jaka Demsar overall
- Salvador Garcia
- Alberto Fernández
- Francisco Herrera
- Octavio Loyola-González
- Gavin C. Cawley
- Weiwei Cheng
- Meelis Kull
- Peter A. Flach
- Krzysztof Dembczynski
- Gonzalo Martínez-Muñoz
Papers from Jaka Demsar's perspective
Ordered by how strongly the researchers Jaka Demsar trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- The Nature of Statistical Learning Theory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Orange: From Experimental Machine Learning to Interactive Data Mining (2004) — 522 citations
- A combinatorial approach to graphlet counting (2014) — 242 citations
- scOrange—a tool for hands-on training of concepts from single-cell data analytics (2019) — 13 citations
- Detecting concept drift in data streams using model explanation (2018) — 101 citations
- Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis (2016) — 496 citations
- Orange: data mining toolbox in python (2013) — 2,143 citations
- Statistical Comparisons of Classifiers over Multiple Data Sets (2006) — 13,306 citations
- Nomograms for visualizing support vector machines (2005) — 92 citations