Todd Mytkowicz

Artificial Intelligence · 2009–2018

A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Todd Mytkowicz trusts overall

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

  1. Andy Georges
  2. Peter M. Bentler
  3. Woongki Baek
  4. Dimitris Achlioptas
  5. Hadi Esmaeilzadeh
  6. Parag Kulkarni
  7. Marta Z. Kwiatkowska
  8. John P. A. Ioannidis
  9. Adrian Sampson
  10. Dries Buytaert

Papers from Todd Mytkowicz's perspective

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

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  2. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Learning Multiple Layers of Features from Tiny Images
  6. Gradient-based learning applied to document recognition
  7. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Long Short-Term Memory

Their papers