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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
Model Analysis & Evaluation for Ambiguous Question Answering
ACL 2023
Rethinking Translation Memory Augmented Neural Machine Translation
ACL 2023
Revisit PCA-based Technique for Out-of-Distribution Detection
ICCV 2023
Local Intrinsic Dimensional Entropy
AAAI 2023
State and parameter learning with PARIS particle Gibbs
ICML 2023
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems
ICML 2023
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation
NSDI 2023
Identifying Selection Bias from Observational Data
AAAI 2023
Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels
ICML 2023
Distributional Offline Policy Evaluation with Predictive Error Guarantees
ICML 2023
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space
ICML 2023
Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction
ICML 2023
Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping
ICML 2023
Generalization Analysis for Contrastive Representation Learning
ICML 2023
Training Normalizing Flows from Dependent Data
ICML 2023
Proper Losses for Discrete Generative Models
ICML 2023
Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions
ICML 2023
Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
ICML 2023
One-Shot Federated Conformal Prediction
ICML 2023
Conditionally Strongly Log-Concave Generative Models
ICML 2023
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances
ICML 2023
Generalized Disparate Impact for Configurable Fairness Solutions in ML
ICML 2023
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity
ICML 2023
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift
ICML 2023
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
ICML 2023
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