Daniel J. Sebald

IEEE Transactions on Signal Processing · 2000

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 3 researchers here, as inferred from the citation graph.

Whom Daniel J. Sebald trusts overall

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

1. Yuhai Wu
2. Bernhard Schölkopf
3. Luc Devroye

Who trusts Daniel J. Sebald overall

1. Yaakov Engel
2. Shie Mannor
3. R. Meir

Papers from Daniel J. Sebald's perspective

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

1. A Probabilistic Theory of Pattern Recognition
2. Advances in kernel methods: support vector learning
3. Fast Training of Support Vector Machines using Sequential Minimal Optimization
4. Statistical Learning Theory
5. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet classification with deep convolutional neural networks
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Support vector machine techniques for nonlinear equalization (2000) — 327 citations