Mert Pilanci
Artificial Intelligence · 2015
A researcher in the Science corpus: 2 papers; trusts 45 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 19 citations into it; #5,010 of 35,345 by trust here, #16,166 by citations
- Computational Mechanics — 19 citations into it; #894 of 10,001 by trust here, #3,275 by citations
- Statistics and Probability — 17 citations into it
- Statistical Learning Theory — 13 citations into it
- Optimization & Training — 13 citations into it; #575 of 2,601 by trust here, #1,585 by citations
- Computational Theory and Mathematics — 7 citations into it
- Numerical Analysis — 7 citations into it
- Applied Mathematics — 5 citations into it
Whom Mert Pilanci trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Michel Ledoux
- Jelani Nelson
- Trevor J. Hastie
- Robert Tibshirani
- Jorge Nocedal
- Nir Ailon
- Joel A. Tropp
- Michael W. Mahoney
- Daniel A. Spielman
Who trusts Mert Pilanci overall
- Peter Richtárik
- Robert Mansel Gower
- Farbod Roosta-Khorasani
- Peng Xu
- Albert S. Berahas
- Julie Nutini
- Michael W. Mahoney
- Mark Eisen
- Shusen Wang
- Christina Heinze
Papers from Mert Pilanci's perspective
Ordered by how strongly the researchers Mert Pilanci trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Regression Shrinkage and Selection via the Lasso
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Newton Sketch: A Near Linear-Time Optimization Algorithm with Linear-Quadratic Convergence (2015) — 294 citations
- Randomized sketches for kernels: Fast and optimal non-parametric regression (2015) — 188 citations