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Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Statistical Learning
4076 directly classified papers
Papers per year
2001: 2
2002: 8
2003: 9
2004: 7
2005: 9
2006: 34
2007: 37
2008: 34
2009: 41
2010: 62
2011: 68
2012: 81
2013: 109
2014: 120
2015: 99
2016: 149
2017: 160
2018: 205
2019: 285
2020: 376
2021: 433
2022: 447
2023: 577
2024: 488
2025: 192
2026: 44
Papers
Unifying Cosine and PLDA Back-ends for Speaker Verification
INTERSPEECH 2022
Are reported accuracies in the clinical speech machine learning literature overoptimistic?
INTERSPEECH 2022
Learning Mixtures of Linear Dynamical Systems
ICML 2022
DNA: Domain Generalization with Diversified Neural Averaging
ICML 2022
Framework for Evaluating Faithfulness of Local Explanations
ICML 2022
Streaming Algorithms for High-Dimensional Robust Statistics
ICML 2022
Fast rates for noisy interpolation require rethinking the effect of inductive bias
ICML 2022
Investigating Generalization by Controlling Normalized Margin
ICML 2022
Label Ranking through Nonparametric Regression
ICML 2022
Achieving Minimax Rates in Pool-Based Batch Active Learning
ICML 2022
Robust Kernel Density Estimation with Median-of-Means principle
ICML 2022
Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards
ICML 2022
A Statistical Manifold Framework for Point Cloud Data
ICML 2022
Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert
ICML 2022
Least Squares Estimation using Sketched Data with Heteroskedastic Errors
ICML 2022
On the Finite-Time Performance of the Knowledge Gradient Algorithm
ICML 2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
ICML 2022
Rethinking Fano’s Inequality in Ensemble Learning
ICML 2022
On Learning Mixture of Linear Regressions in the Non-Realizable Setting
ICML 2022
A new similarity measure for covariate shift with applications to nonparametric regression
ICML 2022
Exploiting Independent Instruments: Identification and Distribution Generalization
ICML 2022
LSB: Local Self-Balancing MCMC in Discrete Spaces
ICML 2022
Intriguing Properties of Input-Dependent Randomized Smoothing
ICML 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
ICML 2022
Bregman Power k-Means for Clustering Exponential Family Data
ICML 2022
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