Jonathan Larson

Statistical Learning Theory · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 11 citations into it

Whom Jonathan Larson trusts overall

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

1. Vladimir Naumovich Vapnik
2. Leslie G. Valiant

Who trusts Jonathan Larson overall

1. Brandon Duderstadt
2. Hayden S. Helm

Papers from Jonathan Larson's perspective

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

1. Gradient-based learning applied to document recognition
2. Learning Multiple Layers of Features from Tiny Images
3. Attention is All you Need (Neural Information Processing Systems)
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
5. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
6. Multitask Learning
7. Intriguing properties of neural networks
8. Information Theory: 1948-1998 - Guest Editorial
9. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
10. Is Learning The n-th Thing Any Easier Than Learning The First?

Their papers

• Omnidirectional Transfer for Quasilinear Lifelong Learning (2021)
• Dynamic Silos: Modularity in intra-organizational communication networks before and during the Covid-19 pandemic (2021)
• Dynamic Silos: Increased Modularity in Intra-organizational Communication Networks during the Covid-19 Pandemic (2021)
• A general approach to progressive learning (2020) — 10 citations