Martin Scholz

Information Systems · 2006–2010

A researcher in the Science corpus: 5 papers; trusts 21 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 29 citations into it; #587 of 8,771 by trust here, #480 by citations
• Artificial Intelligence — 18 citations into it; #5,259 of 35,345 by trust here, #5,533 by citations
• Computational Theory and Mathematics — 11 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Recommender Systems — 7 citations into it; #119 of 233 by trust here, #65 by citations
• Evaluation & Benchmarks — 6 citations into it
• Management Science and Operations Research — 6 citations into it
• Algorithms & Complexity — 5 citations into it

Whom Martin Scholz trusts overall

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

1. Thomas Hofmann
2. Leo Breiman
3. Nati Srebro
4. David D. Lewis
5. Abhinandan Das
6. Rong Pan
7. Yunhong Zhou
8. Tommi S. Jaakkola
9. Mark A. Hall
10. William W. Cohen

Who trusts Martin Scholz overall

1. Annamaria Mesaros
2. Steffen Rendle
3. Christian Stab
4. Sebastian Stein
5. Chen-Kuang Cheng
6. Xiaodong Zheng
7. Yanen Li
8. Sharath Adavanne
9. Toni Heittola
10. Yue Shi

Papers from Martin Scholz's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Their papers

• One-Class Collaborative Filtering (2008) — 1,084 citations
• YALE: rapid prototyping for complex data mining tasks (2006) — 1,275 citations
• Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement (2010) — 424 citations
• Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering (2009) — 170 citations
• From Local Patterns to Global Models: The LeGo Approach to Data Mining (2008) — 107 citations