Ting Kei Pong
Computational Mechanics · 2010–2016
A researcher in the Science corpus: 4 papers; trusts 61 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 53 citations into it; #2,281 of 10,001 by trust here, #2,407 by citations
- Numerical Analysis — 31 citations into it; #2,415 of 3,586 by trust here, #2,644 by citations
- Computational Theory and Mathematics — 23 citations into it; #6,942 of 12,182 by trust here, #6,463 by citations
- Artificial Intelligence — 17 citations into it; #10,452 of 35,345 by trust here, #14,181 by citations
- Computer Vision and Pattern Recognition — 15 citations into it
- Mathematical Optimization — 15 citations into it
- Optimization & Training — 12 citations into it; #1,355 of 2,601 by trust here, #1,624 by citations
- Signal Processing — 12 citations into it
Whom Ting Kei Pong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Paul Tseng
- E.J. Candes
- Nati Srebro
- Zhi-Quan Tom Luo
- Jonathan Baxter
- Guillaume Obozinski
- R. Caruana
- Hédy Attouch
- Francis R. Bach
Who trusts Ting Kei Pong overall
- Yu Zhang
- Qiang Yang
- Yu Zhang
- Junfeng Yang
- Meng Fang
- Maryam Fazel
- Dacheng Tao
- Chi Zhang
- Hamed Karimi
- Hédy Attouch
Papers from Ting Kei Pong's perspective
Ordered by how strongly the researchers Ting Kei Pong 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Calculus of the Exponent of Kurdyka–Łojasiewicz Inequality and Its Applications to Linear Convergence of First-Order Methods (2016) — 366 citations
- Hankel Matrix Rank Minimization with Applications to System Identification and Realization (2013) — 544 citations
- Global Convergence of Splitting Methods for Nonconvex Composite Optimization (2014) — 446 citations
- Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning (2010) — 239 citations