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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 726–750 of 2050 papers

TitleStatusHype
Experiment Planning with Function Approximation—0
Expert Finding in Community Question Answering: A Review—0
ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries—0
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations—0
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting—0
Explainable Multi-class Classification of Medical Data—0
Explain To Me: Salience-Based Explainability for Synthetic Face Detection Models—0
Federated Model Search via Reinforcement Learning—0
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference—0
Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology—0
Exploratory Hidden Markov Factor Models for Longitudinal Mobile Health Data: Application to Adverse Posttraumatic Neuropsychiatric Sequelae—0
DGSAC: Density Guided Sampling and Consensus—0
Exploring Dynamic Novel View Synthesis Technologies for Cinematography—0
Budgeted Online Model Selection and Fine-Tuning via Federated Learning—0
Exploring linguistic feature and model combination for speech recognition based automatic AD detection—0
Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics—0
Exploring the Potential of SSL Models for Sound Event Detection—0
Bayesian Hierarchical Community Discovery—0
Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs—0
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition—0
A New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization—0
Extending Variability-Aware Model Selection with Bias Detection in Machine Learning Projects—0
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study—0
Feedback-Controlled Sequential Lasso Screening—0
Few-shot Adaptation of Multi-modal Foundation Models: A Survey—0
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