A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

29 July 2017

Srinadh Bhojanapalli

Papers citing "A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks"

50 / 156 papers shown

Title
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 67 7 0 07 Mar 2022
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms Romain Chor A. Gohari Gaël Richard Umut Simsekli 25 23 0 04 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Benefit of Interpolation in Nearest Neighbor Algorithms Yue Xing Qifan Song Guang Cheng 14 28 0 23 Feb 2022
On PAC-Bayesian reconstruction guarantees for VAEs Badr-Eddine Chérief-Abdellatif Yuyang Shi Arnaud Doucet Benjamin Guedj DRL 53 17 0 23 Feb 2022
On change of measure inequalities for $f$ -divergences Antoine Picard-Weibel Benjamin Guedj 30 13 0 11 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial nets Zhenyu Zhu Fabian Latorre Grigorios G. Chrysos V. Cevher 24 10 0 10 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 94 17 0 06 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 76 44 0 06 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks Felix Biggs Benjamin Guedj BDL 30 26 0 03 Feb 2022
Partition-Based Active Learning for Graph Neural Networks Jiaqi Ma Ziqiao Ma Joyce Chai Qiaozhu Mei 24 15 0 23 Jan 2022
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators Carles Domingo-Enrich MLT MDE 31 0 0 27 Dec 2021
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks Feiqing Huang Yuefeng Si Yao Zheng Guodong Li 39 1 0 09 Dec 2021
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks Ekkehard Schnoor Arash Behboodi Holger Rauhut 24 13 0 08 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 46 16 0 05 Dec 2021
Information-Theoretic Bayes Risk Lower Bounds for Realizable Models M. Nokleby Ahmad Beirami 59 1 0 08 Nov 2021
Improved Regularization and Robustness for Fine-tuning in Neural Networks Dongyue Li Hongyang R. Zhang NoLa 55 54 0 08 Nov 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 64 197 0 21 Oct 2021
Inductive Biases and Variable Creation in Self-Attention Mechanisms Benjamin L. Edelman Surbhi Goel Sham Kakade Cyril Zhang 27 117 0 19 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
On the Impact of Stable Ranks in Deep Nets B. Georgiev L. Franken Mayukh Mukherjee Georgios Arvanitidis 21 3 0 05 Oct 2021
Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization Chiyuan Zhang M. Raghu Jon M. Kleinberg Samy Bengio OOD 32 30 0 27 Jul 2021
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering Nairouz Mrabah Mohamed Bouguessa M. Touati Riadh Ksantini 35 63 0 19 Jul 2021
Initialization and Regularization of Factorized Neural Layers M. Khodak Neil A. Tenenholtz Lester W. Mackey Nicolò Fusi 65 56 0 03 May 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg Sivaraman Balakrishnan J. Zico Kolter Zachary Chase Lipton 30 30 0 01 May 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 36 13 0 29 Apr 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 39 43 0 28 Mar 2021
LocalDrop: A Hybrid Regularization for Deep Neural Networks Ziqing Lu Chang Xu Bo Du Takashi Ishida Lefei Zhang Masashi Sugiyama 33 14 0 01 Mar 2021
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability Alec Farid Anirudha Majumdar 27 34 0 12 Feb 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning Yiding Jiang Pierre Foret Scott Yak Daniel M. Roy H. Mobahi Gintare Karolina Dziugaite Samy Bengio Suriya Gunasekar Isabelle M Guyon Behnam Neyshabur Google Research OOD 24 55 0 14 Dec 2020
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks Bohan Wang Qi Meng Wei Chen Tie-Yan Liu 30 33 0 11 Dec 2020
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent Kangqiao Liu Liu Ziyin Masakuni Ueda MLT 61 37 0 07 Dec 2020
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks Zhiqi Bu Shiyun Xu Kan Chen 33 17 0 25 Oct 2020
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings Elliot Meyerson Risto Miikkulainen 21 12 0 05 Oct 2020
Complexity Measures for Neural Networks with General Activation Functions Using Path-based Norms Zhong Li Chao Ma Lei Wu 28 24 0 14 Sep 2020
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems Donsub Rim Luca Venturi Joan Bruna Benjamin Peherstorfer 28 9 0 28 Jul 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 20 102 0 25 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks Kyungsu Kim A. Lozano Eunho Yang AAML 35 0 0 02 Jul 2020
PAC-Bayes Analysis Beyond the Usual Bounds Omar Rivasplata Ilja Kuzborskij Csaba Szepesvári John Shawe-Taylor 33 80 0 23 Jun 2020
On the role of data in PAC-Bayes bounds Gintare Karolina Dziugaite Kyle Hsu W. Gharbieh Gabriel Arpino Daniel M. Roy 14 76 0 19 Jun 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 31 29 0 10 Jun 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
What Information Does a ResNet Compress? L. N. Darlow Amos Storkey SSL 30 11 0 13 Mar 2020
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 639 0 20 Feb 2020
Generalization and Representational Limits of Graph Neural Networks Vikas K. Garg Stefanie Jegelka Tommi Jaakkola GNN 26 304 0 14 Feb 2020
On the distance between two neural networks and the stability of learning Jeremy Bernstein Arash Vahdat Yisong Yue Xuan Li ODL 200 57 0 09 Feb 2020
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors Jeffrey Negrea Gintare Karolina Dziugaite Daniel M. Roy AI4CE 40 64 0 09 Dec 2019