Aleksandar Lazarevic

Artificial Intelligence · 2002–2007

A researcher in the Science corpus: 6 papers; trusts 43 researchers and is trusted by 79 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #2,852 of 35,345 by trust here, #4,489 by citations
• Signal Processing — 28 citations into it; #4,521 of 7,572 by trust here, #5,570 by citations
• Computer Networks and Communications — 21 citations into it; #9,477 of 9,886 by trust here, #2,424 by citations
• Computer Vision and Pattern Recognition — 11 citations into it
• Statistical Learning Theory — 11 citations into it
• Statistics and Probability — 10 citations into it; #1,641 of 12,932 by trust here, #3,703 by citations
• Information Systems — 7 citations into it
• Biomedical Engineering — 5 citations into it; #4,802 of 10,734 by trust here, #8,749 by citations

Whom Aleksandar Lazarevic trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Leo Breiman
2. Foster J. Provost
3. Nitesh V. Chawla
4. Yoav Freund
5. Spiros E. Papadimitriou
6. Eleazar Eskin
7. Charu C. Aggarwal
8. Tom Fawcett
9. Hans-Peter Kriegel
10. Robert E. Schapire

Who trusts Aleksandar Lazarevic overall

1. Charu C. Aggarwal
2. Dragoljub Pokrajac
3. Hongzhi Wang
4. Longin Jan Latecki
5. Arthur Zimek
6. Tomás Pevný
7. Jonathan J. Davis
8. Hans-Peter Kriegel
9. Ailin Deng
10. Nitesh V. Chawla

Papers from Aleksandar Lazarevic's perspective

Ordered by how strongly the researchers Aleksandar Lazarevic trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Et al
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection (2003) — 1,019 citations
• Feature bagging for outlier detection (2005) — 737 citations
• Outlier Detection with Kernel Density Functions (2007) — 325 citations
• Incremental Local Outlier Detection for Data Streams (2007) — 451 citations
• SMOTEBoost: Improving Prediction of the Minority Class in Boosting (2003) — 1,784 citations
• Data Mining for Network Intrusion Detection (2002) — 346 citations