Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate

13 June 2018

Papers citing "Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate"

50 / 60 papers shown

Title
Skeletonization of neuronal processes using Discrete Morse techniques from computational topology Samik Banerjee Caleb Stam Daniel J. Tward Steven Savoia Yusu Wang Partha P.Mitra 36 0 0 12 May 2025
Beyond Benign Overfitting in Nadaraya-Watson Interpolators Daniel Barzilai Guy Kornowski Ohad Shamir 80 0 0 11 Feb 2025
On Memorization of Large Language Models in Logical Reasoning Chulin Xie Yangsibo Huang Chiyuan Zhang Da Yu Xinyun Chen Bill Yuchen Lin Bo Li Badih Ghazi Ravi Kumar LRM 58 24 0 30 Oct 2024
Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning Tyler Chang Andrew Gillette R. Maulik 54 2 0 04 Apr 2024
Universality of max-margin classifiers Andrea Montanari Feng Ruan Basil Saeed Youngtak Sohn 31 4 0 29 Sep 2023
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences A. F. Pour H. Ashtiani 27 0 0 28 May 2023
Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method Siwei Wang S. Palmer 35 2 0 19 May 2023
Do Neural Networks Generalize from Self-Averaging Sub-classifiers in the Same Way As Adaptive Boosting? Michael Sun Peter Chatain AI4CE 29 0 0 14 Feb 2023
On the Lipschitz Constant of Deep Networks and Double Descent Matteo Gamba Hossein Azizpour Mårten Björkman 33 7 0 28 Jan 2023
Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning Gustavo de Rosa Mateus Roder João Paulo Papa C. F. G. Santos 36 2 0 19 Dec 2022
Private optimization in the interpolation regime: faster rates and hardness results Hilal Asi Karan N. Chadha Gary Cheng John C. Duchi 49 5 0 31 Oct 2022
Bridging the visual gap in VLN via semantically richer instructions Joaquín Ossandón Benjamín Earle Alvaro Soto 37 0 0 27 Oct 2022
Interpolating Discriminant Functions in High-Dimensional Gaussian Latent Mixtures Xin Bing M. Wegkamp 21 1 0 25 Oct 2022
Bit Error and Block Error Rate Training for ML-Assisted Communication Reinhard Wiesmayr Gian Marti C. Dick Haochuan Song Christoph Studer 38 9 0 25 Oct 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 20 5 0 14 Oct 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Mårten Björkman Hossein Azizpour 63 11 0 21 Sep 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do Niladri S. Chatterji Philip M. Long 23 8 0 19 Sep 2022
Membership Inference Attacks via Adversarial Examples Hamid Jalalzai Elie Kadoche Rémi Leluc Vincent Plassier AAML FedML MIACV 45 7 0 27 Jul 2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting Neil Rohit Mallinar James B. Simon Amirhesam Abedsoltan Parthe Pandit M. Belkin Preetum Nakkiran 26 37 0 14 Jul 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 35 3 0 14 Jun 2022
Neural Collapse: A Review on Modelling Principles and Generalization Vignesh Kothapalli 30 74 0 08 Jun 2022
Benefit of Interpolation in Nearest Neighbor Algorithms Yue Xing Qifan Song Guang Cheng 17 28 0 23 Feb 2022
A generalization gap estimation for overparameterized models via the Langevin functional variance Akifumi Okuno Keisuke Yano 50 1 0 07 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 51 16 0 05 Dec 2021
A manifold learning approach for gesture recognition from micro-Doppler radar measurements Eric Mason H. Mhaskar A. Guo 28 2 0 04 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 36 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 38 71 0 06 Sep 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
Jitter: Random Jittering Loss Function Zhicheng Cai Chenglei Peng S. Du 21 3 0 25 Jun 2021
RDA: Robust Domain Adaptation via Fourier Adversarial Attacking Jiaxing Huang Dayan Guan Aoran Xiao Shijian Lu AAML 43 76 0 05 Jun 2021
Provable Super-Convergence with a Large Cyclical Learning Rate Samet Oymak 35 12 0 22 Feb 2021
Learning Curve Theory Marcus Hutter 146 59 0 08 Feb 2021
SGD Generalizes Better Than GD (And Regularization Doesn't Help) I Zaghloul Amir Tomer Koren Roi Livni 29 46 0 01 Feb 2021
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks Asaf Noy Yi Tian Xu Y. Aflalo Lihi Zelnik-Manor Rong Jin 41 3 0 12 Jan 2021
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization Karan N. Chadha Gary Cheng John C. Duchi 57 16 0 07 Jan 2021
A Topological Filter for Learning with Label Noise Pengxiang Wu Songzhu Zheng Mayank Goswami Dimitris N. Metaxas Chao Chen NoLa 30 112 0 09 Dec 2020
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 39 93 0 04 Nov 2020
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers Preetum Nakkiran Behnam Neyshabur Hanie Sedghi OffRL 29 11 0 16 Oct 2020
Prevalence of Neural Collapse during the terminal phase of deep learning training Vardan Papyan Xuemei Han D. Donoho 35 551 0 18 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 46 441 0 09 Aug 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 23 57 0 08 Jul 2020
On the Similarity between the Laplace and Neural Tangent Kernels Amnon Geifman A. Yadav Yoni Kasten Meirav Galun David Jacobs Ronen Basri 23 89 0 03 Jul 2020
Spectral Bias and Task-Model Alignment Explain Generalization in Kernel Regression and Infinitely Wide Neural Networks Abdulkadir Canatar Blake Bordelon Cengiz Pehlevan 27 181 0 23 Jun 2020
When Does Preconditioning Help or Hurt Generalization? S. Amari Jimmy Ba Roger C. Grosse Xuechen Li Atsushi Nitanda Taiji Suzuki Denny Wu Ji Xu 36 32 0 18 Jun 2020
Diversity sampling is an implicit regularization for kernel methods Michaël Fanuel J. Schreurs Johan A. K. Suykens 21 14 0 20 Feb 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar Cengiz Pehlevan 149 201 0 07 Feb 2020
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 27 77 0 10 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 39 145 0 13 Nov 2019
Sharper bounds for uniformly stable algorithms Olivier Bousquet Yegor Klochkov Nikita Zhivotovskiy 23 120 0 17 Oct 2019
The Implicit Regularization of Ordinary Least Squares Ensembles Daniel LeJeune Hamid Javadi Richard G. Baraniuk 18 43 0 10 Oct 2019