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To understand deep learning we need to understand kernel learning

5 February 2018

Papers citing "To understand deep learning we need to understand kernel learning"

50 / 271 papers shown

Title
Deep Learning Generalization, Extrapolation, and Over-parameterization Roozbeh Yousefzadeh 31 1 0 19 Mar 2022
On the Generalization Mystery in Deep Learning S. Chatterjee Piotr Zielinski OOD 77 35 0 18 Mar 2022
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize Alexander Wei Wei Hu Jacob Steinhardt 112 72 0 11 Mar 2022
Chained Generalisation Bounds Eugenio Clerico Amitis Shidani George Deligiannidis Arnaud Doucet AI4CE FedML 76 13 0 02 Mar 2022
Memorize to Generalize: on the Necessity of Interpolation in High Dimensional Linear Regression Chen Cheng John C. Duchi Rohith Kuditipudi 56 12 0 20 Feb 2022
Geometric Regularization from Overparameterization Nicholas J. Teague 53 1 0 18 Feb 2022
Interpolation and Regularization for Causal Learning L. C. Vankadara Luca Rendsburg U. V. Luxburg Debarghya Ghoshdastidar CML 55 1 0 18 Feb 2022
On the Origins of the Block Structure Phenomenon in Neural Network Representations Thao Nguyen M. Raghu Simon Kornblith 93 13 0 15 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao Zixiang Chen M. Belkin Quanquan Gu MLT 93 90 0 14 Feb 2022
Learning Representation from Neural Fisher Kernel with Low-rank Approximation Ruixiang Zhang Shuangfei Zhai Etai Littwin J. Susskind SSL 72 3 0 04 Feb 2022
Faster Convergence of Local SGD for Over-Parameterized Models Tiancheng Qin S. Rasoul Etesami César A. Uribe FedML 88 6 0 30 Jan 2022
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions Mojtaba Sahraee-Ardakan M. Emami Parthe Pandit S. Rangan A. Fletcher 96 9 0 20 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 78 11 0 31 Dec 2021
Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points Armin Eftekhari 50 1 0 25 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks T. Getu 54 2 0 25 Nov 2021
Importance of Kernel Bandwidth in Quantum Machine Learning Ruslan Shaydulin Stefan M. Wild 99 39 0 09 Nov 2021
Harmless interpolation in regression and classification with structured features Andrew D. McRae Santhosh Karnik Mark A. Davenport Vidya Muthukumar 186 11 0 09 Nov 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander B. Atanasov Blake Bordelon Cengiz Pehlevan MLT 120 85 0 29 Oct 2021
Learning curves for Gaussian process regression with power-law priors and targets Hui Jin P. Banerjee Guido Montúfar 70 18 0 23 Oct 2021
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model A. Bodin N. Macris 126 13 0 22 Oct 2021
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 112 12 0 21 Oct 2021
Learning in High Dimension Always Amounts to Extrapolation Randall Balestriero J. Pesenti Yann LeCun 129 104 0 18 Oct 2021
NFT-K: Non-Fungible Tangent Kernels Sina Alemohammad Hossein Babaei C. Barberan Naiming Liu Lorenzo Luzi Blake Mason Richard G. Baraniuk AAML 46 0 0 11 Oct 2021
Kernel Interpolation as a Bayes Point Machine Jeremy Bernstein Alexander R. Farhang Yisong Yue BDL 71 4 0 08 Oct 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 81 1 0 06 Oct 2021
Spectral Bias in Practice: The Role of Function Frequency in Generalization Sara Fridovich-Keil Raphael Gontijo-Lopes Rebecca Roelofs 111 30 0 06 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 69 1 0 27 Sep 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 117 72 0 06 Sep 2021
When and how epochwise double descent happens Cory Stephenson Tyler Lee 82 15 0 26 Aug 2021
Interpolation can hurt robust generalization even when there is no noise Konstantin Donhauser Alexandru cTifrea Michael Aerni Reinhard Heckel Fanny Yang 93 16 0 05 Aug 2021
Mitigating deep double descent by concatenating inputs John Chen Qihan Wang Anastasios Kyrillidis BDL 37 3 0 02 Jul 2021
Assessing Generalization of SGD via Disagreement Yiding Jiang Vaishnavh Nagarajan Christina Baek J. Zico Kolter 111 115 0 25 Jun 2021
Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics Diego Agudelo-España Yassine Nemmour Bernhard Schölkopf Jia-Jie Zhu OOD BDL 48 0 0 24 Jun 2021
Compression Implies Generalization Allan Grønlund M. Hogsgaard Lior Kamma Kasper Green Larsen MLT AI4CE 23 0 0 15 Jun 2021
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions Bruno Loureiro G. Sicuro Cédric Gerbelot Alessandro Pacco Florent Krzakala Lenka Zdeborová 76 62 0 07 Jun 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi Zhou Arthur Gretton MLT 105 35 0 06 Jun 2021
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes Elvis Dohmatob 84 9 0 04 Jun 2021
Out-of-Distribution Generalization in Kernel Regression Abdulkadir Canatar Blake Bordelon Cengiz Pehlevan OODD OOD 57 13 0 04 Jun 2021
Framing RNN as a kernel method: A neural ODE approach Adeline Fermanian Pierre Marion Jean-Philippe Vert Gérard Biau 91 26 0 02 Jun 2021
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation M. Belkin 73 186 0 29 May 2021
Latent Gaussian Model Boosting Fabio Sigrist AI4CE 68 23 0 19 May 2021
Uniform Convergence, Adversarial Spheres and a Simple Remedy Gregor Bachmann Seyed-Mohsen Moosavi-Dezfooli Thomas Hofmann AAML 38 8 0 07 May 2021
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures Yuan Cao Quanquan Gu M. Belkin 81 53 0 28 Apr 2021
How rotational invariance of common kernels prevents generalization in high dimensions Konstantin Donhauser Mingqi Wu Fanny Yang 85 24 0 09 Apr 2021
Fitting Elephants P. Mitra 26 0 0 31 Mar 2021
Weighted Neural Tangent Kernel: A Generalized and Improved Network-Induced Kernel Lei Tan Shutong Wu Xiaolin Huang 28 2 0 22 Mar 2021
Comments on Leo Breiman's paper 'Statistical Modeling: The Two Cultures' (Statistical Science, 2001, 16(3), 199-231) Jelena Bradic Yinchu Zhu 27 0 0 21 Mar 2021
On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models Peizhong Ju Xiaojun Lin Ness B. Shroff MLT 71 10 0 09 Mar 2021
Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models Zitong Yang Yu Bai Song Mei 71 18 0 08 Mar 2021
Trading Signals In VIX Futures M. Avellaneda T. Li A. Papanicolaou Gaozhan Wang 22 4 0 02 Mar 2021