Kenji Kawaguchi

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Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Leslie KaelblingVerified email at csail.mit.edu
Vikas VermaAalto University/ MILA/ Google BrainVerified email at google.com
George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and EngineeringVerified email at brown.edu
Ameya D. JagtapAssistant Professor of Applied Mathematics (Research), Brown University, USAVerified email at brown.edu
Jiaoyang HuangNew York UniversityVerified email at nyu.edu
Tomas Lozano-PerezProfessor of Computer Science, MITVerified email at mit.edu
TOMASO POGGIOMcDermott Professor in Brain Sciences, MITVerified email at ai.mit.edu
Haihao (Sean) LuAssistant Professor, University of ChicagoVerified email at chicagobooth.edu
Linjun ZhangAssistant Professor of Statistics, Rutgers UniversityVerified email at rutgers.edu
James ZouStanford UniversityVerified email at stanford.edu
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaVerified email at unige.it
Jack HidaryAlphabet (Google) XVerified email at google.com
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
Minh-Thang LuongStaff Research Scientist at GoogleVerified email at google.com
Hieu PhamResearch Scientist, Google BrainVerified email at google.com
Ferran AletMITVerified email at mit.edu
Dianbo LiuMILA/Harvard University/MITVerified email at hms.harvard.edu
Michael MozerGoogle Research, Brain Team; University of ColoradoVerified email at colorado.edu
Keyulu XuMITVerified email at mit.edu

Kenji Kawaguchi

Presidential Young Professor, National University of Singapore

Verified email at nus.edu.sg - Homepage

Deep learning theory Machine learning theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep learning without poor local minima K Kawaguchi Advances In Neural Information Processing Systems (NeurIPS), 586-594, 2016	831	2016
Generalization in Deep Learning K Kawaguchi, LP Kaelbling, Y Bengio In Mathematics of Deep Learning, Cambridge University Press, to appear …, 2018	372	2018
Interpolation consistency training for semi-supervised learning V Verma, K Kawaguchi, A Lamb, J Kannala, A Solin, Y Bengio, ... Neural Networks 145, 90-106, 2022	347	2022
Adaptive activation functions accelerate convergence in deep and physics-informed neural networks AD Jagtap, K Kawaguchi, GE Karniadakis Journal of Computational Physics 404, 109136, 2020	206	2020
Theory of Deep Learning III: explaining the non-overfitting puzzle T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ... Massachusetts Institute of Technology, CBMM Memo No. 073, 2018	120*	2018
Bayesian optimization with exponential convergence K Kawaguchi, LP Kaelbling, T Lozano-Pérez Advances in Neural Information Processing Systems (NeurIPS) 28, 2809-2817, 2015	105	2015
Depth Creates No Bad Local Minima H Lu, K Kawaguchi arXiv preprint arXiv:1702.08580, 2017	101	2017
Locally adaptive activation functions with slope recovery for deep and physics-informed neural networks AD Jagtap, K Kawaguchi, G Em Karniadakis Proceedings of the Royal Society A 476 (2239), 20200334, 2020	84	2020
How Does Mixup Help With Robustness and Generalization? L Zhang, Z Deng, K Kawaguchi, A Ghorbani, J Zou International Conference on Learning Representations (ICLR), 2021	67	2021
GraphMix: Improved Training of GNNs for Semi-Supervised Learning V Verma, M Qu, K Kawaguchi, A Lamb, Y Bengio, J Kannala, J Tang Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021	66	2021
Interpolated adversarial training: Achieving robust neural networks without sacrificing too much accuracy A Lamb, V Verma, K Kawaguchi, J Kannala, Y Bengio arXiv preprint arXiv:1906.06784, 2019	52	2019
Depth with Nonlinearity Creates No Bad Local Minima in ResNets K Kawaguchi, Y Bengio Neural Networks 118, 167-174, 2019	50	2019
Elimination of all bad local minima in deep learning K Kawaguchi, L Kaelbling Artificial Intelligence and Statistics (AISTATS), 853-863, 2020	44	2020
Gradient descent finds global minima for generalizable deep neural networks of practical sizes K Kawaguchi, J Huang 2019 57th Annual Allerton Conference on Communication, Control, and …, 2019	40	2019
Effect of depth and width on local minima in deep learning K Kawaguchi, J Huang, LP Kaelbling Neural computation 31 (7), 1462-1498, 2019	40	2019
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning Q Liao, K Kawaguchi, T Poggio Massachusetts Institute of Technology, CBMM Memo No. 57, 2016	33	2016
Towards domain-agnostic contrastive learning V Verma, T Luong, K Kawaguchi, H Pham, Q Le International Conference on Machine Learning (ICML), 10530-10541, 2021	30	2021
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization K Kawaguchi, H Lu Artificial Intelligence and Statistics (AISTATS), 669-679, 2020	24	2020
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers K Kawaguchi International Conference on Learning Representations (ICLR), 2021	21	2021
Analysis for iodine release from unit 3 of Fukushima Dai-ichi nuclear power plant with consideration of water phase iodine chemistry J Ishikawa, K Kawaguchi, Y Maruyama Journal of Nuclear Science and Technology 52 (3), 308-314, 2015	21	2015

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