Functional Risk Minimization

31 December 2024

Leslie Pack Kaelbling

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Papers citing "Functional Risk Minimization"

23 / 23 papers shown

Title
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 124 27 0 06 Dec 2021
Efficient and Modular Implicit Differentiation Mathieu Blondel Quentin Berthet Marco Cuturi Roy Frostig Stephan Hoyer Felipe Llinares-López Fabian Pedregosa Jean-Philippe Vert 114 238 0 31 May 2021
Deep learning: a statistical viewpoint Peter L. Bartlett Andrea Montanari Alexander Rakhlin 84 279 0 16 Mar 2021
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 239 1,361 0 03 Oct 2020
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time Ferran Alet Maria Bauza Kenji Kawaguchi Nurullah Giray Kuru Tomas Lozano-Perez L. Kaelbling AI4CE 115 16 0 22 Sep 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 418 1,998 0 11 Apr 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 133 948 0 04 Dec 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 139 417 0 06 Nov 2019
Integrals over Gaussians under Linear Domain Constraints A. Gessner Oindrila Kanjilal Philipp Hennig 69 30 0 21 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 99 96 0 29 Sep 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 165 859 0 10 Sep 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 266 2,249 0 05 Jul 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 305 1,665 0 28 Dec 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 376 3,226 0 20 Jun 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 260 2,240 0 08 Mar 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 102 510 0 26 Jan 2018
Theory of Deep Learning III: explaining the non-overfitting puzzle T. Poggio Kenji Kawaguchi Q. Liao Brando Miranda Lorenzo Rosasco Xavier Boix Jack Hidary H. Mhaskar ODL 101 128 0 30 Dec 2017
Noisy Networks for Exploration Meire Fortunato M. G. Azar Bilal Piot Jacob Menick Ian Osband ... Rémi Munos Demis Hassabis Olivier Pietquin Charles Blundell Shane Legg 116 897 0 30 Jun 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 389 7,619 0 02 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 372 4,639 0 10 Nov 2016
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 377 5,398 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 228 2,542 0 02 Nov 2016
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger C. Grosse ODL 153 1,025 0 19 Mar 2015