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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

Showing 726750 of 2050 papers

TitleStatusHype
Evaluating Representations with Readout Model Switching0
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
Infinite Action Contextual Bandits with Reusable Data ExhaustCode0
Linear Bandits with Memory: from Rotting to Rising0
Best Arm Identification for Stochastic Rising BanditsCode0
When mitigating bias is unfair: multiplicity and arbitrariness in algorithmic group fairnessCode0
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLPCode0
What are the mechanisms underlying metacognitive learning?0
Fast Linear Model Trees by PILOT0
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection0
On the Limitation and Experience Replay for GNNs in Continual Learning0
A Strong Baseline for Batch Imitation Learning0
Penalized Quasi-likelihood Estimation and Model Selection in Time Series Models with Parameters on the Boundary0
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationCode0
Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust0
Empirical analysis in limit order book modeling for Nikkei 225 Stocks with Cox-type intensities0
MLOps with enhanced performance control and observability0
Dirichlet process mixture of Gaussian process functional regressions and its variational EM algorithm0
How to select predictive models for causal inference?0
Straight-Through meets Sparse Recovery: the Support Exploration Algorithm0
Revisiting Bellman Errors for Offline Model SelectionCode0
Specializing Smaller Language Models towards Multi-Step ReasoningCode2
A Deep Learning Method for Comparing Bayesian Hierarchical ModelsCode0
Warlock: an automated computational workflow for simulating spatially structured tumour evolutionCode0
Data thinning for convolution-closed distributionsCode1
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