David B. Smith

Artificial Intelligence · with Kâafar · 2019

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it

Whom David B. Smith trusts overall

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

1. Jaideep Vaidya
2. Kamalika Chaudhuri
3. Reza Shokri
4. Ohad Shamir

Papers from David B. Smith's perspective

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

1. The Algorithmic Foundations of Differential Privacy
2. Privacy Preserving Data Mining
3. CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
4. Privacy-preserving logistic regression
5. Practical Secure Aggregation for Privacy-Preserving Machine Learning
6. Privacy-preserving deep learning
7. Privacy preserving association rule mining in vertically partitioned data
8. Functional Mechanism: Regression Analysis under Differential Privacy
9. Signal Processing and Machine Learning with Differential Privacy
10. Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes

Their papers

• The Value of Collaboration in Convex Machine Learning with Differential Privacy (2019) — 112 citations
• The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car (2019) — 395 citations