Vladimir Kunc

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Vladimir Kunc trusts overall

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

  1. Chih-Jen Lin
  2. Raghu Bollapragada
  3. Wes McKinney

Papers from Vladimir Kunc's perspective

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

  1. LIBSVM: A library for support vector machines
  2. Optimization Methods for Large-Scale Machine Learning
  3. Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming
  4. Stochastic Approximation and Recursive Algorithms and Applications
  5. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
  6. Exact and Inexact Subsampled Newton Methods for Optimization
  7. Accelerated Methods for Non-Convex Optimization
  8. Newton Sketch: A Near Linear-Time Optimization Algorithm with Linear-Quadratic Convergence
  9. ImageNet classification with deep convolutional neural networks
  10. Gradient-based learning applied to document recognition

Their papers