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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Learning Theory
5312 directly classified papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
Improved Kernel Alignment Regret Bound for Online Kernel Learning
AAAI 2023
On the Complexity of PAC Learning in Hilbert Spaces
AAAI 2023
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets
NIPS 2023
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits
AAAI 2023
Understanding the Generalization Performance of Spectral Clustering Algorithms
AAAI 2023
Towards Understanding Generalization of Graph Neural Networks
ICML 2023
The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent
ICML 2023
A Parameterized Theory of PAC Learning
AAAI 2023
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
ICML 2023
Tree Learning: Optimal Sample Complexity and Algorithms
AAAI 2023
Partial-Label Regression
AAAI 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths
AAAI 2023
Adjective Scale Probe: Can Language Models Encode Formal Semantics Information?
AAAI 2023
A PDE approach for regret bounds under partial monitoring
JMLR 2023
Why do networks have inhibitory/negative connections?
ICCV 2023
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?
ICCV 2023
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
ICML 2023
Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance
ICCV 2023
Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective
ICCV 2023
What do neural networks learn in image classification? A frequency shortcut perspective
ICCV 2023
Mnemonist: Locating Model Parameters that Memorize Training Examples
UAI 2023
Environment-Invariant Curriculum Relation Learning for Fine-Grained Scene Graph Generation
ICCV 2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
ICML 2023
Will Large-scale Generative Models Corrupt Future Datasets?
ICCV 2023
Understanding Hessian Alignment for Domain Generalization
ICCV 2023
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