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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
Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving
NIPS 2024
Decorrelated Variable Importance
JMLR 2024
Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms
JMLR 2024
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation
NIPS 2024
Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?
NIPS 2024
The sample complexity of ERMs in stochastic convex optimization
AISTATS 2024
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization
JMLR 2024
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
NIPS 2024
LaSCal: Label-Shift Calibration without target labels
NIPS 2024
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts
AISTATS 2024
Improved Regret of Linear Ensemble Sampling
NIPS 2024
Piecewise-Stationary Bandits with Knapsacks
NIPS 2024
Rates of convergence for density estimation with generative adversarial networks
JMLR 2024
Mathematical Framework for Online Social Media Auditing
JMLR 2024
Spectral Learning of Shared Dynamics Between Generalized-Linear Processes
NIPS 2024
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM
NIPS 2024
Full Bayesian Significance Testing for Neural Networks in Traffic Forecasting
IJCAI 2024
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks
ACL 2024
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
NIPS 2024
Online Consistency of the Nearest Neighbor Rule
NIPS 2024
Data Thinning for Convolution-Closed Distributions
JMLR 2024
Online Distribution Learning with Local Privacy Constraints
AISTATS 2024
False discovery proportion envelopes with m-consistency
JMLR 2024
Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
NIPS 2024
Small coresets via negative dependence: DPPs, linear statistics, and concentration
NIPS 2024
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