Optimistic Rates for Learning with a Smooth Loss

20 September 2010

Papers citing "Optimistic Rates for Learning with a Smooth Loss"

50 / 173 papers shown

Title
Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses Yuzhou Cao Han Bao Lei Feng Bo An 16 0 0 14 May 2025
Better Rates for Random Task Orderings in Continual Linear Models Itay Evron Ran Levinstein Matan Schliserman Uri Sherman Tomer Koren Daniel Soudry Nathan Srebro CLL 30 0 0 06 Apr 2025
Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning Liang Wu Ruixi Hu Yunwen Lei 45 0 0 03 Mar 2025
Do we really have to filter out random noise in pre-training data for language models? Jinghan Ru Yuxin Xie Xianwei Zhuang Yuguo Yin Yuexian Zou 83 2 0 10 Feb 2025
Shallow diffusion networks provably learn hidden low-dimensional structure Nicholas M. Boffi Arthur Jacot Stephen Tu Ingvar M. Ziemann DiffM 34 1 0 15 Oct 2024
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups Fengyu Gao Ruiquan Huang Jing Yang FedML 30 0 0 27 Sep 2024
Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition Mohamad Amin Mohamadi Zhiyuan Li Lei Wu Danica J. Sutherland 40 10 0 17 Jul 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 86 2 0 08 Jul 2024
Fully Unconstrained Online Learning Ashok Cutkosky Zakaria Mhammedi CLL 27 1 0 30 May 2024
Universal Online Convex Optimization with $1$ Projection per Round Wenhao Yang Yibo Wang Peng Zhao Lijun Zhang 32 2 0 30 May 2024
On the Rashomon ratio of infinite hypothesis sets Evzenie Coupkova Mireille Boutin 29 1 0 27 Apr 2024
On the Generalization Ability of Unsupervised Pretraining Yuyang Deng Junyuan Hong Jiayu Zhou M. Mahdavi SSL 47 4 0 11 Mar 2024
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers M. E. Ildiz Yixiao Huang Yingcong Li A. S. Rawat Samet Oymak 25 17 0 21 Feb 2024
Oracle-Efficient Differentially Private Learning with Public Data Adam Block Mark Bun Rathin Desai Abhishek Shetty Steven Wu FedML 16 2 0 13 Feb 2024
Tensor Completion via Integer Optimization Xin Chen S. Kudva Yongzheng Dai Anil Aswani Chen Chen 13 0 0 06 Feb 2024
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging C. Tsai Hao-Chung Cheng Yen-Huan Li 25 0 0 05 Nov 2023
Online Convex Optimization with Switching Cost and Delayed Gradients Spandan Senapati Rahul Vaze 79 2 0 18 Oct 2023
Stability and Generalization for Minibatch SGD and Local SGD Yunwen Lei Tao Sun Mingrui Liu 22 3 0 02 Oct 2023
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation Yuyang Deng Ilja Kuzborskij M. Mahdavi OOD 16 2 0 19 Sep 2023
Efficient Methods for Non-stationary Online Learning Peng Zhao Yan-Feng Xie Lijun Zhang Zhi-Hua Zhou 36 19 0 16 Sep 2023
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization Kaiyue Wen Zhiyuan Li Tengyu Ma FAtt 22 26 0 20 Jul 2023
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach Yu-Hu Yan Peng Zhao Zhiguang Zhou 16 8 0 17 Jul 2023
On the sample complexity of parameter estimation in logistic regression with normal design Daniel J. Hsu A. Mazumdar 11 5 0 09 Jul 2023
Accelerated stochastic approximation with state-dependent noise Sasila Ilandarideva A. Juditsky Guanghui Lan Tianjiao Li 30 8 0 04 Jul 2023
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization Khashayar Gatmiry Zhiyuan Li Ching-Yao Chuang Sashank J. Reddi Tengyu Ma Stefanie Jegelka ODL 17 11 0 22 Jun 2023
Nonparametric regression using over-parameterized shallow ReLU neural networks Yunfei Yang Ding-Xuan Zhou 24 6 0 14 Jun 2023
Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression Junfan Li Shizhong Liao 17 0 0 14 Jun 2023
Unconstrained Online Learning with Unbounded Losses Andrew Jacobsen Ashok Cutkosky 18 16 0 08 Jun 2023
The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent Lei Wu Weijie J. Su MLT 22 20 0 27 May 2023
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks Puyu Wang Yunwen Lei Di Wang Yiming Ying Ding-Xuan Zhou MLT 22 3 0 26 May 2023
Data-Dependent Bounds for Online Portfolio Selection Without Lipschitzness and Smoothness C. Tsai Ying-Ting Lin Yen-Huan Li 26 4 0 23 May 2023
Margin theory for the scenario-based approach to robust optimization in high dimension Fabien Lauer 16 1 0 07 Mar 2023
Tight Risk Bounds for Gradient Descent on Separable Data Matan Schliserman Tomer Koren 10 4 0 02 Mar 2023
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime Hilal Asi Vitaly Feldman Tomer Koren Kunal Talwar 21 9 0 27 Feb 2023
Generalization Analysis for Contrastive Representation Learning Yunwen Lei Tianbao Yang Yiming Ying Ding-Xuan Zhou 23 8 0 24 Feb 2023
Stability-based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning Jiahuan Wang Jun Chen H. Chen Bin Gu Weifu Li Xinwei Tang MLT 11 2 0 20 Feb 2023
On the Stability and Generalization of Triplet Learning Jun Chen H. Chen Xue Jiang Bin Gu Weifu Li Tieliang Gong Feng Zheng 24 4 0 20 Feb 2023
Minimizing Dynamic Regret on Geodesic Metric Spaces Zihao Hu Guanghui Wang Jacob D. Abernethy 12 6 0 17 Feb 2023
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence Ruichen Jiang Qiujiang Jin Aryan Mokhtari 11 16 0 16 Feb 2023
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization Sijia Chen Yu-Jie Zhang Wei-Wei Tu Peng Zhao Lijun Zhang 8 16 0 09 Feb 2023
On Dynamic Regret and Constraint Violations in Constrained Online Convex Optimization R. Vaze 6 4 0 24 Jan 2023
Sampling-based Nyström Approximation and Kernel Quadrature Satoshi Hayakawa Harald Oberhauser Terry Lyons 21 13 0 23 Jan 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 32 2 0 09 Jan 2023
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 21 4 0 28 Dec 2022
Improved Kernel Alignment Regret Bound for Online Kernel Learning Junfan Li Shizhong Liao 13 2 0 26 Dec 2022
Private optimization in the interpolation regime: faster rates and hardness results Hilal Asi Karan N. Chadha Gary Cheng John C. Duchi 32 5 0 31 Oct 2022
Stochastic Mirror Descent for Large-Scale Sparse Recovery Sasila Ilandarideva Yannis Bekri A. Juditsky Vianney Perchet 17 1 0 23 Oct 2022
Transfer learning with affine model transformation Shunya Minami Kenji Fukumizu Yoshihiro Hayashi Ryo Yoshida 11 1 0 18 Oct 2022
Adaptive Oracle-Efficient Online Learning Guanghui Wang Zihao Hu Vidya Muthukumar Jacob D. Abernethy 25 4 0 17 Oct 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Satyen Kale Jason D. Lee Chris De Sa Ayush Sekhari Karthik Sridharan 19 4 0 13 Oct 2022