Andre Wibisono
Artificial Intelligence · 2013–2019
A researcher in the Science corpus: 7 papers; trusts 40 researchers and is trusted by 45 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 57 citations into it; #5,229 of 35,345 by trust here, #7,606 by citations
- Optimization & Training — 48 citations into it; #1,501 of 2,601 by trust here, #2,052 by citations
- Computational Mechanics — 30 citations into it; #2,270 of 10,001 by trust here, #2,942 by citations
- Numerical Analysis — 19 citations into it; #496 of 3,586 by trust here, #661 by citations
- Statistics and Probability — 19 citations into it
- Management Science and Operations Research — 15 citations into it; #6,878 of 11,946 by trust here, #3,825 by citations
- Probabilistic & Bayesian Methods — 15 citations into it; #759 of 1,525 by trust here, #618 by citations
- Mathematical Optimization — 14 citations into it
Whom Andre Wibisono trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Weijie Su
- Michel Baes
- E.J. Candes
- Cédric Villani
- Guanghui Lan
- Shun-ichi Amari
- Stephen P. Boyd
- Brendan O'Donoghue
- Felix Otto
Who trusts Andre Wibisono overall
- James Lucas
- Michael I. Jordan
- Richard S. Zemel
- Sanjeev Arora
- Ashia C. Wilson
- Bin Shi
- Chi Jin
- Chin-Wei Huang
- Qianxiao Li
- Michael Cohen
Papers from Andre Wibisono's perspective
Ordered by how strongly the researchers Andre Wibisono 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)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- 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
- Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations (2013) — 595 citations
- Streaming Variational Bayes (2013) — 368 citations
- A variational perspective on accelerated methods in optimization (2016) — 659 citations
- On Accelerated Methods in Optimization (2015) — 30 citations
- Last-iterate convergence rates for min-max optimization (2019) — 75 citations
- Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices (2019) — 353 citations
- Optimal rates for zero-order optimization: the power of two function evaluations (2013) — 9 citations