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← Core Methods
Machine Learning
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Core Methods
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Model Selection
13 directly classified papers
Papers per year
2009: 1
2010: 2
2012: 1
2015: 1
2019: 1
2021: 1
2022: 3
2023: 2
2025: 1
Papers
Determine the Number of States in Hidden Markov Models via Marginal Likelihood
JMLR 2025
Bayesian Data Selection
JMLR 2023
Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
NIPS 2023
Joint Continuous and Discrete Model Selection via Submodularity
JMLR 2022
AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control
NIPS 2022
Oracle Inequalities for Model Selection in Offline Reinforcement Learning
NIPS 2022
MultiLink: Multi-Class Structure Recovery via Agglomerative Clustering and Model Selection
CVPR 2021
Topological Data Analysis of Decision Boundaries with Application to Model Selection
ICML 2019
A New Generalized Error Path Algorithm for Model Selection
ICML 2015
On Estimation and Selection for Topic Models
AISTATS 2012
Extended Bayesian Information Criteria for Gaussian Graphical Models
NIPS 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
NIPS 2010
Data-driven calibration of linear estimators with minimal penalties
NIPS 2009
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