Takuya Hayashi

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Takuya Hayashi trusts overall

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

  1. Kristin E. Lauter
  2. Jorge Nocedal
  3. Richard Lindner
  4. Joppe W. Bos
  5. Thore Graepel
  6. Alhassan F. Khedr
  7. Michael Naehrig
  8. Jun Zhang

Who trusts Takuya Hayashi overall

  1. Qiang Yang
  2. Lingjuan Lyu
  3. Yang Liu
  4. Miran Kim
  5. Stephen Hardy
  6. Shengwen Yang
  7. Tianjian Chen
  8. Richard Nock
  9. Le Trieu Phong
  10. David Enthoven

Papers from Takuya Hayashi's perspective

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

  1. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  2. Better Key Sizes (and Attacks) for LWE-Based Encryption
  3. Can homomorphic encryption be practical?
  4. Deep Learning with Differential Privacy
  5. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  6. CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
  7. The Algorithmic Foundations of Differential Privacy
  8. Machine Learning Classification over Encrypted Data
  9. ML Confidential: Machine Learning on Encrypted Data
  10. A fully homomorphic encryption scheme

Their papers