Norm-Based Capacity Control in Neural Networks

27 February 2015

Papers citing "Norm-Based Capacity Control in Neural Networks"

50 / 119 papers shown

Title
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models Yinan Liang Zehua Wang Xiuwei Xu Jie Zhou Jiwen Lu VLM LRM 51 0 0 19 Mar 2025
Regularization can make diffusion models more efficient Mahsa Taheri Johannes Lederer 98 0 0 13 Feb 2025
Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning Rémy Hosseinkhan Boucher Onofrio Semeraro L. Mathelin 82 0 0 28 Jan 2025
Layer-Adaptive State Pruning for Deep State Space Models Minseon Gwak Seongrok Moon Joohwan Ko PooGyeon Park 25 0 0 05 Nov 2024
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices Yuka Hashimoto Tomoharu Iwata 28 0 0 03 Oct 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 91 2 0 08 Jul 2024
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? Weijie Tu Weijian Deng Liang Zheng Tom Gedeon 40 0 0 14 Jun 2024
Spectral Truncation Kernels: Noncommutativity in $C^*$ -algebraic Kernel Machines Yuka Hashimoto Ayoub Hafid Masahiro Ikeda Hachem Kadri 41 1 0 28 May 2024
Hidden Synergy: $L_1$ Weight Normalization and 1-Path-Norm Regularization Aditya Biswas 41 0 0 29 Apr 2024
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks Fanghui Liu L. Dadi V. Cevher 82 2 0 29 Apr 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis Paul Viallard George Deligiannidis Umut Simsekli 48 2 0 26 Apr 2024
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration Mike Heddes Narayan Srinivasa T. Givargis Alexandru Nicolau 91 0 0 12 Jan 2024
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Jiancong Xiao Ruoyu Sun Zhimin Luo AAML 38 6 0 09 Oct 2023
Understanding Deep Neural Networks via Linear Separability of Hidden Layers Chao Zhang Xinyuan Chen Wensheng Li Lixue Liu Wei Wu Dacheng Tao 28 3 0 26 Jul 2023
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks Puyu Wang Yunwen Lei Di Wang Yiming Ying Ding-Xuan Zhou MLT 29 3 0 26 May 2023
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models Suzanna Parkinson Greg Ongie Rebecca Willett 65 6 0 24 May 2023
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization Geng Li G. Wang Jie Ding 31 3 0 07 May 2023
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap Weiyang Liu L. Yu Adrian Weller Bernhard Schölkopf 37 17 0 11 Mar 2023
Koopman-based generalization bound: New aspect for full-rank weights Yuka Hashimoto Sho Sonoda Isao Ishikawa Atsushi Nitanda Taiji Suzuki 11 2 0 12 Feb 2023
On the Lipschitz Constant of Deep Networks and Double Descent Matteo Gamba Hossein Azizpour Marten Bjorkman 31 7 0 28 Jan 2023
Statistical guarantees for sparse deep learning Johannes Lederer 13 11 0 11 Dec 2022
Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov Andrei Filatov Teresa Yeo Ajay Sohmshetty Amir Zamir OOD 45 10 0 01 Dec 2022
On the Sample Complexity of Two-Layer Networks: Lipschitz vs. Element-Wise Lipschitz Activation Amit Daniely Elad Granot MLT 17 1 0 17 Nov 2022
Do highly over-parameterized neural networks generalize since bad solutions are rare? Julius Martinetz T. Martinetz 27 1 0 07 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 49 8 0 25 Oct 2022
Approximate Description Length, Covering Numbers, and VC Dimension Amit Daniely Gal Katzhendler 16 0 0 26 Sep 2022
On the Implicit Bias in Deep-Learning Algorithms Gal Vardi FedML AI4CE 34 72 0 26 Aug 2022
On Rademacher Complexity-based Generalization Bounds for Deep Learning Lan V. Truong MLT 41 13 0 08 Aug 2022
Integral Probability Metrics PAC-Bayes Bounds Ron Amit Baruch Epstein Shay Moran Ron Meir 27 18 0 01 Jul 2022
Learning sparse features can lead to overfitting in neural networks Leonardo Petrini Francesco Cagnetta Eric Vanden-Eijnden M. Wyart MLT 42 23 0 24 Jun 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 33 3 0 14 Jun 2022
Trajectory-dependent Generalization Bounds for Deep Neural Networks via Fractional Brownian Motion Chengli Tan Jiang Zhang Junmin Liu 35 1 0 09 Jun 2022
Towards Size-Independent Generalization Bounds for Deep Operator Nets Pulkit Gopalani Sayar Karmakar Dibyakanti Kumar Anirbit Mukherjee AI4CE 24 5 0 23 May 2022
Investigating Generalization by Controlling Normalized Margin Alexander R. Farhang Jeremy Bernstein Kushal Tirumala Yang Liu Yisong Yue 31 6 0 08 May 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 52 7 0 07 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial nets Zhenyu Zhu Fabian Latorre Grigorios G. Chrysos V. Cevher 21 10 0 10 Feb 2022
Understanding Value Decomposition Algorithms in Deep Cooperative Multi-Agent Reinforcement Learning Zehao Dou J. Kuba Yaodong Yang FAtt 22 5 0 10 Feb 2022
The no-free-lunch theorems of supervised learning T. Sterkenburg Peter Grünwald FedML 24 56 0 09 Feb 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 88 17 0 06 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks Felix Biggs Benjamin Guedj BDL 30 26 0 03 Feb 2022
Learning from Heterogeneous Data Based on Social Interactions over Graphs Virginia Bordignon Stefan Vlaski Vincenzo Matta Ali H. Sayed 46 16 0 17 Dec 2021
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Lun Du Xiaozhou Shi Qiang Fu Xiaojun Ma Hengyu Liu Shi Han Dongmei Zhang 40 104 0 29 Oct 2021
Coarse-Grained Smoothness for RL in Metric Spaces Giorgio Giannone Kavosh Asadi Cameron Allen Sam Lobel George Konidaris Michael Littman 40 3 0 23 Oct 2021
Inductive Biases and Variable Creation in Self-Attention Mechanisms Benjamin L. Edelman Surbhi Goel Sham Kakade Cyril Zhang 27 116 0 19 Oct 2021
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks Tolga Ergen Mert Pilanci 32 16 0 18 Oct 2021
Block Contextual MDPs for Continual Learning Shagun Sodhani Franziska Meier Joelle Pineau Amy Zhang CLL 33 25 0 13 Oct 2021
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications Ziqiao Wang Yongyi Mao FedML MLT 37 22 0 07 Oct 2021
Ridgeless Interpolation with Shallow ReLU Networks in $1D$ is Nearest Neighbor Curvature Extrapolation and Provably Generalizes on Lipschitz Functions Boris Hanin MLT 38 9 0 27 Sep 2021