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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

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Showing 851–875 of 2050 papers

TitleStatusHype
Estimating Optimal Policy Value in General Linear Contextual Bandits—0
Linear Bandits with Memory: from Rotting to Rising—0
Infinite Action Contextual Bandits with Reusable Data ExhaustCode0
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 PILOT—0
On the Limitation and Experience Replay for GNNs in Continual Learning—0
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection—0
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationCode0
A Strong Baseline for Batch Imitation Learning—0
Penalized Quasi-likelihood Estimation and Model Selection in Time Series Models with Parameters on the Boundary—0
Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust—0
Empirical analysis in limit order book modeling for Nikkei 225 Stocks with Cox-type intensities—0
MLOps with enhanced performance control and observability—0
How to select predictive models for causal inference?—0
Dirichlet process mixture of Gaussian process functional regressions and its variational EM algorithm—0
Straight-Through meets Sparse Recovery: the Support Exploration Algorithm—0
Revisiting Bellman Errors for Offline Model SelectionCode0
A Deep Learning Method for Comparing Bayesian Hierarchical ModelsCode0
Warlock: an automated computational workflow for simulating spatially structured tumour evolutionCode0
The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks—0
Transformers as Algorithms: Generalization and Stability in In-context LearningCode0
Understanding Best Subset Selection: A Tale of Two C(omplex)ities—0
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