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1707.05947
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Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
19 July 2017
Wenlong Mou
Liwei Wang
Xiyu Zhai
Kai Zheng
MLT
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Papers citing
"Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints"
50 / 107 papers shown
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Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel
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Zhichao Wang
Wei Huang
Andi Han
Taiji Suzuki
Arya Mazumdar
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305
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12 Jun 2025
Algorithm- and Data-Dependent Generalization Bounds for Diffusion Models
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Dario Shariatian
Maxime Haddouche
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Umut Simsekli
248
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04 Jun 2025
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526
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Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
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Yonathan Wolanowsky
Gal Vardi
Nathan Srebro
Daniel Soudry
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471
2
0
25 May 2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou
Yunwen Lei
Ata Kabán
400
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0
03 Apr 2025
Towards Auto-Regressive Next-Token Prediction: In-Context Learning Emerges from Generalization
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Zixuan Gong
Xiaolin Hu
Huayi Tang
Yong Liu
360
3
0
24 Feb 2025
Understanding Generalization in Transformers: Error Bounds and Training Dynamics Under Benign and Harmful Overfitting
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Zhikai Wu
Jian Li
Wenshu Fan
MLT
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273
3
0
18 Feb 2025
Generalization Bounds for Markov Algorithms through Entropy Flow Computations
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Maxime Haddouche
George Deligiannidis
Umut Simsekli
369
1
0
11 Feb 2025
Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes
IEEE International Joint Conference on Neural Network (IJCNN), 2024
Julius Martinetz
C. Linse
Thomas Martinetz
395
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0
22 Oct 2024
Generalization and Robustness of the Tilted Empirical Risk
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Amir R. Asadi
Tian Li
Ahmad Beirami
Gesine Reinert
Samuel N. Cohen
517
1
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28 Sep 2024
Information-theoretic Generalization Analysis for Expected Calibration Error
Futoshi Futami
Masahiro Fujisawa
UQCV
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400
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24 May 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets
Benjamin Dupuis
Paul Viallard
George Deligiannidis
Umut Simsekli
382
6
0
26 Apr 2024
Tighter Generalisation Bounds via Interpolation
Paul Viallard
Maxime Haddouche
Umut Simsekli
Benjamin Guedj
355
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0
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Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
Ossi Raisa
Hibiki Ito
Antti Honkela
316
9
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Adam-like Algorithm with Smooth Clipping Attains Global Minima: Analysis Based on Ergodicity of Functional SDEs
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234
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29 Nov 2023
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Naoki Sato
Hideaki Iiduka
437
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15 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications
Huayi Tang
Yong Liu
553
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08 Nov 2023
Time-Independent Information-Theoretic Generalization Bounds for SGLD
Neural Information Processing Systems (NeurIPS), 2023
Futoshi Futami
Masahiro Fujisawa
452
12
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02 Nov 2023
Generalization Bounds for Label Noise Stochastic Gradient Descent
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jung Eun Huh
Patrick Rebeschini
377
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Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds
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Ziqiao Wang
Yongyi Mao
402
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Minibatch and Local SGD: Algorithmic Stability and Linear Speedup in Generalization
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573
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A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
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Yi Zhang
Yuying Zhao
Zhaoqing Li
Xueqi Cheng
Yu Wang
Olivera Kotevska
Philip S. Yu
Hanyu Wang
464
40
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31 Aug 2023
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Xiaoge Deng
Li Shen
Shengwei Li
Tao Sun
Dongsheng Li
Dacheng Tao
492
3
0
18 Aug 2023
Power-law Dynamic arising from machine learning
Wei Chen
Weitao Du
Zhi-Ming Ma
Qi Meng
244
0
0
16 Jun 2023
Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Zhenyu Sun
Xiaochun Niu
Ermin Wei
FedML
MLT
288
35
0
06 Jun 2023
Stochastic Gradient Langevin Dynamics Based on Quantization with Increasing Resolution
Jinwuk Seok
Chang-Jae Cho
376
0
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30 May 2023
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks
Neural Computation (Neural Comput.), 2023
Puyu Wang
Yunwen Lei
Di Wang
Yiming Ying
Ding-Xuan Zhou
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366
8
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26 May 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
Neural Information Processing Systems (NeurIPS), 2023
Lingjiong Zhu
Mert Gurbuzbalaban
Anant Raj
Umut Simsekli
321
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20 May 2023
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Amin Karbasi
Dionysis Kalogerias
399
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Shengrui Li
Xueting Han
Jing Bai
AI4CE
229
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19 Apr 2023
Benign Overfitting for Two-layer ReLU Convolutional Neural Networks
International Conference on Machine Learning (ICML), 2023
Yiwen Kou
Zi-Yuan Chen
Yuanzhou Chen
Quanquan Gu
MLT
261
32
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07 Mar 2023
Geometric ergodicity of SGLD via reflection coupling
Stochastics and Dynamics (SD), 2023
Lei Li
Jian‐Guo Liu
Yuliang Wang
182
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17 Jan 2023
Do highly over-parameterized neural networks generalize since bad solutions are rare?
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Julius Martinetz
T. Martinetz
531
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0
07 Nov 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds
Neural Information Processing Systems (NeurIPS), 2022
Itai Gat
Yossi Adi
Alex Schwing
Tamir Hazan
BDL
326
6
0
12 Oct 2022
Differentially Private Deep Learning with ModelMix
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Jun Wan
S. Devadas
280
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Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability
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Peisong Wen
Qianqian Xu
Zhiyong Yang
Yuan He
Qingming Huang
335
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27 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes
International Conference on Algorithmic Learning Theory (ALT), 2022
Eugenio Clerico
Tyler Farghly
George Deligiannidis
Benjamin Guedj
Arnaud Doucet
504
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Super-model ecosystem: A domain-adaptation perspective
Fengxiang He
Dacheng Tao
DiffM
208
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A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics
CSIAM Transactions on Applied Mathematics (TCAM), 2022
Lei Li
Yuliang Wang
439
16
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19 Jul 2022
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence
International Conference on Learning Representations (ICLR), 2022
Margalit Glasgow
Colin Wei
Mary Wootters
Tengyu Ma
372
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16 Jun 2022
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems
Annual Conference Computational Learning Theory (COLT), 2022
Yunwen Lei
322
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Generalization Error Bounds for Deep Neural Networks Trained by SGD
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Chao Ma
174
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Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares
International Conference on Algorithmic Learning Theory (ALT), 2022
Anant Raj
Melih Barsbey
Mert Gurbuzbalaban
Lingjiong Zhu
Umut Simsekli
310
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Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
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Xu Luo
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389
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Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing
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Weak Convergence of Approximate reflection coupling and its Application to Non-convex Optimization
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318
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Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
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Konstantinos E. Nikolakakis
Farzin Haddadpour
Amin Karbasi
Dionysios S. Kalogerias
555
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26 Apr 2022
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