Generalization Error in Deep Learning

3 August 2018

Papers citing "Generalization Error in Deep Learning"

50 / 58 papers shown

Title
A Near Complete Nonasymptotic Generalization Theory For Multilayer Neural Networks: Beyond the Bias-Variance Tradeoff Hao Yu Xiangyang Ji AI4CE 58 0 0 03 Mar 2025
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise Bikram Khanal Pablo Rivas 87 0 0 16 Dec 2024
Generalization Error Bound for Quantum Machine Learning in NISQ Era -- A Survey Bikram Khanal Pablo Rivas Arun Sanjel Korn Sooksatra Ernesto Quevedo Alejandro Rodriguez 28 2 0 11 Sep 2024
Universal Novelty Detection Through Adaptive Contrastive Learning Hossein Mirzaei Mojtaba Nafez Mohammad Jafari Mohammad Bagher Soltani Mohammad Azizmalayeri Jafar Habibi Mohammad Sabokrou M. Rohban 29 4 0 20 Aug 2024
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks Amit Peleg Matthias Hein 39 0 0 04 Jul 2024
Neural Operators Learn the Local Physics of Magnetohydrodynamics Taeyoung Kim Youngsoo Ha Myungjoo Kang AI4CE 29 0 0 24 Apr 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 35 4 0 04 Apr 2024
Self-Correcting Self-Consuming Loops for Generative Model Training Nate Gillman Michael Freeman Daksh Aggarwal Chia-Hong Hsu Calvin Luo Yonglong Tian Chen Sun 33 13 0 11 Feb 2024
Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss Yahong Yang Juncai He AI4CE 32 7 0 31 Jan 2024
Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws Taeyoung Kim Myungjoo Kang AI4CE 25 2 0 03 Jan 2024
Understanding and Leveraging the Learning Phases of Neural Networks Johannes Schneider Mohit Prabhushankar AI4CE 14 0 0 11 Dec 2023
On the Stability of Iterative Retraining of Generative Models on their own Data Quentin Bertrand A. Bose Alexandre Duplessis Marco Jiralerspong Gauthier Gidel 24 43 0 30 Sep 2023
Optimization Guarantees of Unfolded ISTA and ADMM Networks With Smooth Soft-Thresholding Shaik Basheeruddin Shah Pradyumna Pradhan Wei Pu Ramunaidu Randhi Miguel R. D. Rodrigues Yonina C. Eldar 22 4 0 12 Sep 2023
Catching Image Retrieval Generalization Maksim Zhdanov I. Karpukhin VLM 19 0 0 23 Jun 2023
An information-Theoretic Approach to Semi-supervised Transfer Learning Daniel Jakubovitz David Uliel Miguel R. D. Rodrigues Raja Giryes 17 1 0 11 Jun 2023
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 24 6 0 06 Jun 2023
Generalization and Estimation Error Bounds for Model-based Neural Networks Avner Shultzman Eyar Azar M. Rodrigues Yonina C. Eldar 16 7 0 19 Apr 2023
Lipschitzness Effect of a Loss Function on Generalization Performance of Deep Neural Networks Trained by Adam and AdamW Optimizers M. Lashkari Amin Gheibi 19 3 0 29 Mar 2023
Unsupervised Layer-wise Score Aggregation for Textual OOD Detection Maxime Darrin Guillaume Staerman Eduardo Dadalto Camara Gomes Jackie CK Cheung Pablo Piantanida Pierre Colombo OODD 55 11 0 20 Feb 2023
Global Convergence Rate of Deep Equilibrium Models with General Activations Lan V. Truong 39 2 0 11 Feb 2023
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation Jose Antonio Lara Benitez Takashi Furuya F. Faucher Anastasis Kratsios X. Tricoche Maarten V. de Hoop 37 16 0 27 Jan 2023
Stretched and measured neural predictions of complex network dynamics V. Vasiliauskaite Nino Antulov-Fantulin 25 1 0 12 Jan 2023
Policy Learning for Nonlinear Model Predictive Control with Application to USVs Rizhong Wang Huiping Li Bin Liang Yang Shi Deming Xu 14 19 0 18 Nov 2022
Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems Muhammad Umar B. Niazi Johnson R. Cao Xu-yang Sun Amritam Das Karl H. Johansson OOD 13 22 0 04 Oct 2022
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL Fengzhuo Zhang Boyi Liu Kaixin Wang Vincent Y. F. Tan Zhuoran Yang Zhaoran Wang OffRL LRM 49 10 0 20 Sep 2022
Bounding the Rademacher Complexity of Fourier neural operators Taeyoung Kim Myung-joo Kang AI4CE 17 9 0 12 Sep 2022
On Rademacher Complexity-based Generalization Bounds for Deep Learning Lan V. Truong MLT 37 13 0 08 Aug 2022
Deep Learning and Symbolic Regression for Discovering Parametric Equations Michael Zhang Samuel Kim Peter Y. Lu M. Soljavcić 24 18 0 01 Jul 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 19 11 0 19 Apr 2022
Pyramid-BERT: Reducing Complexity via Successive Core-set based Token Selection Xin Huang A. Khetan Rene Bidart Zohar Karnin 19 14 0 27 Mar 2022
Combining Varied Learners for Binary Classification using Stacked Generalization Sruthi Nair Abhishek Gupta Raunak Joshi V. Chitre 23 8 0 17 Feb 2022
The learning phases in NN: From Fitting the Majority to Fitting a Few Johannes Schneider 9 0 0 16 Feb 2022
Generalization Error Bounds on Deep Learning with Markov Datasets Lan V. Truong 21 8 0 23 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks T. Getu 27 2 0 25 Nov 2021
HierMUD: Hierarchical Multi-task Unsupervised Domain Adaptation between Bridges for Drive-by Damage Diagnosis Jingxiao Liu Susu Xu Mario Bergés Hae Young Noh 14 19 0 23 Jul 2021
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions Juan Shu B. Xi Charles A. Kamhoua AAML 11 0 0 30 Jun 2021
Generalization bounds for graph convolutional neural networks via Rademacher complexity Shaogao Lv GNN 13 15 0 20 Feb 2021
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction Yuhang Li Ruihao Gong Xu Tan Yang Yang Peng Hu Qi Zhang F. Yu Wei Wang Shi Gu MQ 22 415 0 10 Feb 2021
Overestimation learning with guarantees Adrien Gauffriau Franccois Malgouyres Mélanie Ducoffe 11 3 0 26 Jan 2021
Leveraging Local Variation in Data: Sampling and Weighting Schemes for Supervised Deep Learning Paul Novello Gaël Poëtte D. Lugato P. Congedo 11 0 0 19 Jan 2021
A function space analysis of finite neural networks with insights from sampling theory Raja Giryes 14 6 0 15 Apr 2020
On the interplay between physical and content priors in deep learning for computational imaging Mo Deng Shuai Li Iksung Kang N. Fang George Barbastathis 39 26 0 14 Apr 2020
Vulnerabilities of Connectionist AI Applications: Evaluation and Defence Christian Berghoff Matthias Neu Arndt von Twickel AAML 22 23 0 18 Mar 2020
Towards Probability-based Safety Verification of Systems with Components from Machine Learning H. Kaindl Stefan Kramer 17 1 0 02 Mar 2020
Introduction to deep learning Lihi Shiloh-Perl Raja Giryes 24 0 0 29 Feb 2020
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters Jinlong Liu Guo-qing Jiang Yunzhi Bai Ting Chen Huayan Wang AI4CE 25 48 0 21 Jan 2020
Understanding Generalization in Deep Learning via Tensor Methods Jingling Li Yanchao Sun Jiahao Su Taiji Suzuki Furong Huang 17 27 0 14 Jan 2020
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 14 168 0 19 Dec 2019
Towards Quantifying Intrinsic Generalization of Deep ReLU Networks Shaeke Salman Canlin Zhang Xiuwen Liu W. Mio OOD 11 0 0 18 Oct 2019
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey Bin Qian Jie Su Z. Wen D. N. Jha Yinhao Li ... Albert Y. Zomaya Omer F. Rana Lizhe Wang Maciej Koutny R. Ranjan 20 4 0 11 Oct 2019