Noboru Murata

Artificial Intelligence · 1993–2015

A researcher in the Science corpus: 8 papers; trusts 23 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it; #9,691 of 35,345 by trust here, #17,412 by citations
• Optimization & Training — 9 citations into it
• Model Architectures — 8 citations into it
• Statistics and Probability — 7 citations into it; #11,900 of 12,932 by trust here, #4,132 by citations
• Evaluation & Benchmarks — 5 citations into it
• Statistical Learning Theory — 5 citations into it; #548 of 1,038 by trust here, #417 by citations
• Scaling & Learning Theory — 5 citations into it; #200 of 428 by trust here, #329 by citations

Whom Noboru Murata trusts overall

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

1. Shun-ichi Amari
2. Hirotugu Akaike
3. Jean-François Cardoso
4. Eric B. Baum
5. S. Helgason
6. Jorma Rissanen
7. Antoine Souloumiac
8. David E. Rumelhart
9. Geoffrey E. Hinton
10. L. Shepp

Who trusts Noboru Murata overall

1. Hiroshi Sawada
2. Soo-Young Lee
3. Seungjin Choi
4. Shun-ichi Amari
5. Taesu Kim
6. Thomas G. Dietterich
7. J. Urgen Schmidhuber
8. Emmanuel Vincent
9. K. Müller
10. Lutz Prechelt

Papers from Noboru Murata's perspective

Ordered by how strongly the researchers Noboru Murata 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. Learning internal representations by error propagation
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Neural Network with Unbounded Activation Functions is Universal Approximator (2015) — 367 citations
• Asymptotic statistical theory of overtraining and cross-validation (1997)
• Robust Boosting Algorithm Against Mislabeling in Multiclass Problems (2008) — 26 citations
• A Gaussian Process Robust Regression (2005) — 4 citations
• An approach to blind source separation based on temporal structure of speech signals (2001) — 618 citations
• A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks (1996)
• Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? (1995)
• Statistical Theory of Learning Curves under Entropic Loss Criterion (1993)