Josh Attenberg

Artificial Intelligence · with Dasgupta · 2009–2015

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it; #12,076 of 35,345 by trust here, #6,229 by citations

Whom Josh Attenberg trusts overall

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

1. Robert E. Schapire
2. Claudia Perlich
3. Hal Daumé Iii
4. Brian M. D’Alessandro
5. David D. Lewis

Who trusts Josh Attenberg overall

1. Kush R. Varshney
2. Alejandro Barredo Arrieta
3. Prem Gopalan
4. Edo Liberty
5. James T. Wilson
6. Mark Dredze
7. Ping Li
8. Kilian Q. Weinberger
9. Alekh Agarwal
10. Minmin Chen

Papers from Josh Attenberg's perspective

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

1. Get another label? improving data quality and data mining using multiple, noisy labelers
2. Frustratingly Easy Domain Adaptation
3. Supervised learning from multiple experts: whom to trust when everyone lies a bit (International Conference on Machine Learning)
4. Hash Kernels
5. A Brief Introduction to Boosting
6. Machine learning for targeted display advertising: transfer learning in action
7. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
8. Gradient-based learning applied to document recognition
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. ImageNet classification with deep convolutional neural networks

Their papers

• Feature hashing for large scale multitask learning (2009) — 1,095 citations
• Beat the Machine: Challenging Humans to Find a Predictive Model's “Unknown Unknowns” (2015) — 115 citations