Learning without Concentration

1 January 2014

Papers citing "Learning without Concentration"

50 / 51 papers shown

Title
Do we really need the Rademacher complexities? Daniel Bartl S. Mendelson 63 0 0 24 Feb 2025
Evaluating Model Performance Under Worst-case Subpopulations Mike Li Hongseok Namkoong Shangzhou Xia 37 17 0 01 Jul 2024
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss Ingvar M. Ziemann Stephen Tu George J. Pappas Nikolai Matni 52 8 0 08 Feb 2024
A Tutorial on the Non-Asymptotic Theory of System Identification Ingvar M. Ziemann Anastasios Tsiamis Bruce D. Lee Yassir Jedra Nikolai Matni George J. Pappas 30 25 0 07 Sep 2023
On the Concentration of the Minimizers of Empirical Risks Paul Escande 23 2 0 03 Apr 2023
Uniform Risk Bounds for Learning with Dependent Data Sequences Fabien Lauer 20 1 0 21 Mar 2023
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models Lijia Zhou Frederic Koehler Pragya Sur Danica J. Sutherland Nathan Srebro 83 9 0 21 Oct 2022
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency Wenlong Mou Martin J. Wainwright Peter L. Bartlett OffRL 28 10 0 26 Sep 2022
Statistical Learning Theory for Control: A Finite Sample Perspective Anastasios Tsiamis Ingvar M. Ziemann Nikolai Matni George J. Pappas 23 73 0 12 Sep 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 27 4 0 24 Aug 2022
Learning with little mixing Ingvar M. Ziemann Stephen Tu 13 27 0 16 Jun 2022
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition Varun Kanade Patrick Rebeschini Tomas Vaskevicius 19 10 0 23 Feb 2022
Posterior concentration and fast convergence rates for generalized Bayesian learning L. Ho Binh T. Nguyen Vu C. Dinh D. M. Nguyen 23 5 0 19 Nov 2021
Optimal convex lifted sparse phase retrieval and PCA with an atomic matrix norm regularizer Andrew D. McRae J. Romberg Mark A. Davenport 25 8 0 08 Nov 2021
Beyond Independent Measurements: General Compressed Sensing with GNN Application Alireza Naderi Y. Plan 23 4 0 30 Oct 2021
Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction C. Brownlees Jordi Llorens-Terrazas AI4TS 14 3 0 11 Aug 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting Frederic Koehler Lijia Zhou Danica J. Sutherland Nathan Srebro 21 55 0 17 Jun 2021
AdaBoost and robust one-bit compressed sensing Geoffrey Chinot Felix Kuchelmeister Matthias Löffler Sara van de Geer 32 5 0 05 May 2021
On Monte-Carlo methods in convex stochastic optimization Daniel Bartl S. Mendelson 23 8 0 19 Jan 2021
Improved rates for prediction and identification of partially observed linear dynamical systems Holden Lee 13 10 0 19 Nov 2020
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory Paria Rashidinejad Jiantao Jiao Stuart J. Russell 24 11 0 12 Oct 2020
Robust Compressed Sensing using Generative Models A. Jalal Liu Liu A. Dimakis C. Caramanis 21 39 0 16 Jun 2020
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability D. Simchi-Levi Yunzong Xu OffRL 39 107 0 28 Mar 2020
Finite-time Identification of Stable Linear Systems: Optimality of the Least-Squares Estimator Yassir Jedra Alexandre Proutière 19 42 0 17 Mar 2020
Robust $k$ -means Clustering for Distributions with Two Moments Yegor Klochkov Alexey Kroshnin Nikita Zhivotovskiy 18 19 0 06 Feb 2020
Convex Reconstruction of Structured Matrix Signals from Linear Measurements (I): Theoretical Results Yuan Tian 17 2 0 19 Oct 2019
Robust high dimensional learning for Lipschitz and convex losses Geoffrey Chinot Guillaume Lecué M. Lerasle 23 18 0 10 May 2019
Sample Complexity Lower Bounds for Linear System Identification Yassir Jedra Alexandre Proutière 11 40 0 25 Mar 2019
Robust learning and complexity dependent bounds for regularized problems Geoffrey Chinot 16 2 0 06 Feb 2019
Agnostic Sample Compression Schemes for Regression Idan Attias Steve Hanneke A. Kontorovich Menachem Sadigurschi 24 4 0 03 Oct 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 26 34 0 13 Feb 2018
Learning Compact Neural Networks with Regularization Samet Oymak MLT 27 39 0 05 Feb 2018
Lifting high-dimensional nonlinear models with Gaussian regressors Christos Thrampoulidis A. S. Rawat 8 8 0 11 Dec 2017
Convergence rates of least squares regression estimators with heavy-tailed errors Q. Han J. Wellner 15 44 0 07 Jun 2017
Localized Gaussian width of $M$ -convex hulls with applications to Lasso and convex aggregation Pierre C. Bellec 8 17 0 30 May 2017
Towards the study of least squares estimators with convex penalty Pierre C. Bellec Guillaume Lecué Alexandre B. Tsybakov 20 11 0 31 Jan 2017
Learning from MOM's principles: Le Cam's approach Lecué Guillaume Lerasle Matthieu 38 52 0 08 Jan 2017
Distribution-dependent concentration inequalities for tighter generalization bounds Xinxing Wu Junping Zhang 19 1 0 19 Jul 2016
Optimal Rates of Statistical Seriation Nicolas Flammarion Cheng Mao Philippe Rigollet 23 59 0 08 Jul 2016
On optimality of empirical risk minimization in linear aggregation Adrien Saumard 20 21 0 11 May 2016
Rate-Distortion Bounds on Bayes Risk in Supervised Learning M. Nokleby Ahmad Beirami Robert Calderbank 23 9 0 08 May 2016
Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes Peter Grünwald Nishant A. Mehta 30 71 0 01 May 2016
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning Niloofar Yousefi Yunwen Lei Marius Kloft M. Mollaghasemi G. Anagnostopoulos 17 27 0 18 Feb 2016
High-Dimensional Estimation of Structured Signals from Non-Linear Observations with General Convex Loss Functions Martin Genzel 8 45 0 10 Feb 2016
A Geometric View on Constrained M-Estimators Yen-Huan Li Ya-Ping Hsieh N. Zerbib V. Cevher 19 6 0 26 Jun 2015
On the gap between RIP-properties and sparse recovery conditions S. Dirksen Guillaume Lecué Holger Rauhut 121 18 0 20 Apr 2015
`local' vs. `global' parameters -- breaking the gaussian complexity barrier S. Mendelson 30 24 0 09 Apr 2015
On aggregation for heavy-tailed classes S. Mendelson 42 28 0 25 Feb 2015
Learning without Concentration for General Loss Functions S. Mendelson 55 65 0 13 Oct 2014
Performance of empirical risk minimization in linear aggregation Guillaume Lecué S. Mendelson FedML 51 40 0 24 Feb 2014