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Meta-learning PINN loss functions


Jul 12, 2021
Apostolos F Psaros, Kenji Kawaguchi, George Em Karniadakis


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Discrete-Valued Neural Communication


Jul 10, 2021
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio


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Understanding Dynamics of Nonlinear Representation Learning and Its Application


Jun 28, 2021
Kenji Kawaguchi, Linjun Zhang, Zhun Deng


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Adversarial Training Helps Transfer Learning via Better Representations


Jun 18, 2021
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou


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MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift


Jun 07, 2021
Siddharth Bhatia, Arjit Jain, Shivin Srivastava, Kenji Kawaguchi, Bryan Hooi


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Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth


May 26, 2021
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi


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Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions


May 20, 2021
Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis

* 26 pages, 13 figures 

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A Recipe for Global Convergence Guarantee in Deep Neural Networks


Apr 15, 2021
Kenji Kawaguchi, Qingyun Sun

* Published in AAAI 2021 

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CAC: A Clustering Based Framework for Classification


Feb 23, 2021
Shivin Srivastava, Siddharth Bhatia, Lingxiao Huang, Lim Jun Heng, Kenji Kawaguchi, Vaibhav Rajan


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On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers


Feb 18, 2021
Kenji Kawaguchi

* ICLR 2021. Selected for ICLR Spotlight (top 6% submissions) 

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A Simple Deep Equilibrium Model Converges to Global Optima with Weight Tying


Feb 15, 2021
Kenji Kawaguchi

* ICLR 2021. Selected for ICLR Spotlight (top 6% submissions) 

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When and How Mixup Improves Calibration


Feb 11, 2021
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou


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Towards Domain-Agnostic Contrastive Learning


Nov 09, 2020
Vikas Verma, Minh-Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le


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Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time


Oct 14, 2020
Ferran Alet, Kenji Kawaguchi, Maria Bauza, Nurullah Giray Kuru, Tomas Lozano-Perez, Leslie Pack Kaelbling


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How Does Mixup Help With Robustness and Generalization?


Oct 09, 2020
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou


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Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks


Oct 18, 2019
Ameya D. Jagtap, Kenji Kawaguchi, George Em Karniadakis

* 19 pages, 13 figures 

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Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes


Aug 05, 2019
Kenji Kawaguchi, Jiaoyang Huang

* Accepted to appear in IEEE Proc. of the 57th Allerton Conference, UIUC, Illinois, USA 

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A Stochastic First-Order Method for Ordered Empirical Risk Minimization


Jul 09, 2019
Kenji Kawaguchi, Haihao Lu

* code available at: https://github.com/kenjikawaguchi/qSGD 

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Every Local Minimum is a Global Minimum of an Induced Model


Apr 07, 2019
Kenji Kawaguchi, Leslie Pack Kaelbling


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Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit


Jan 12, 2019
Jascha Sohl-Dickstein, Kenji Kawaguchi


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Elimination of All Bad Local Minima in Deep Learning


Jan 02, 2019
Kenji Kawaguchi, Leslie Pack Kaelbling


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Effect of Depth and Width on Local Minima in Deep Learning


Nov 20, 2018
Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling


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Depth with Nonlinearity Creates No Bad Local Minima in ResNets


Oct 21, 2018
Kenji Kawaguchi, Yoshua Bengio


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