Roberto Hirata Jr.

Artificial Intelligence · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Probabilistic & Bayesian Methods — 19 citations into it
• Statistical Learning Theory — 12 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Anomaly & Outlier Detection — 6 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Signal Processing — 6 citations into it
• Statistics and Probability — 6 citations into it

Whom Roberto Hirata Jr. trusts overall

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

1. Bernhard Schölkopf
2. Krikamol Muandet
3. Barnab'as P'oczos
4. Liang Xiong
5. Arthur Gretton
6. Kenji Fukumizu
7. Alex Smola
8. Risi Kondor
9. Tony Jebara
10. Jeff Schneider

Papers from Roberto Hirata Jr.'s perspective

Ordered by how strongly the researchers Roberto Hirata Jr. 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. GENERATIVE ADVERSARIAL NETS
7. Long Short-Term Memory
8. Distinctive Image Features from Scale-Invariant Keypoints
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Support Measure Data Description A One-Class Classifier for Group Anomaly Detection (2017)
• Support Measure Data Description for group anomaly detection (2015) — 15 citations