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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 1151–1200 of 2050 papers

TitleStatusHype
SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese—0
Searching parsimonious solutions with GA-PARSIMONY and XGboost in high-dimensional databases—0
Second-Order Convergence in Private Stochastic Non-Convex Optimization—0
SEERL: Sample Efficient Ensemble Reinforcement Learning—0
Segmentation et Interprétation de Nuages de Points pour la Modélisation d'Environnements Urbains—0
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning—0
Selecting for Less Discriminatory Algorithms: A Relational Search Framework for Navigating Fairness-Accuracy Trade-offs in Practice—0
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge—0
Cost-based feature selection for network model choice—0
Selective Factor Extraction in High Dimensions—0
Selective Inference and Learning Mixed Graphical Models—0
Selective Inference for Latent Block Models—0
Selective linear segmentation for detecting relevant parameter changes—0
Selective Sequential Model Selection—0
Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series—0
Self-directed Machine Learning—0
Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models—0
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities—0
Quantifying Topology In Pancreatic Tubular Networks From Live Imaging 3D Microscopy—0
SeNMFk-SPLIT: Large Corpora Topic Modeling by Semantic Non-negative Matrix Factorization with Automatic Model Selection—0
Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases—0
Sequential Experimental Design for Spectral Measurement: Active Learning Using a Parametric Model—0
Sequential Model-Based Ensemble Optimization—0
Sequential prediction under log-loss and misspecification—0
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures—0
Gibbs-Based Information Criteria and the Over-Parameterized Regime—0
Sharp Convergence Rates for Forward Regression in High-Dimensional Sparse Linear Models—0
Fast Partition-Based Cross-Validation With Centering and Scaling for X^TX and X^TY—0
Short-term prediction of photovoltaic power generation using Gaussian process regression—0
Short-time asymptotics for the implied volatility skew under a stochastic volatility model with L\'evy jumps—0
Sig-SDEs model for quantitative finance—0
Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study—0
Simultaneous Clustering and Model Selection for Tensor Affinities—0
Simultaneous Identification of Sparse Structures and Communities in Heterogeneous Graphical Models—0
Simultaneous Localization and Layout Model Selection in Manhattan Worlds—0
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning—0
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC—0
Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship—0
Sliding Window Neural Generated Tracking Based on Measurement Model—0
Small Data, Big Decisions: Model Selection in the Small-Data Regime—0
Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare—0
Smart Multi-Modal Search: Contextual Sparse and Dense Embedding Integration in Adobe Express—0
Smooth Bandit Optimization: Generalization to Hölder Space—0
Solar Power Prediction Using Machine Learning—0
SortedNet: A Scalable and Generalized Framework for Training Modular Deep Neural Networks—0
SPAgent: Adaptive Task Decomposition and Model Selection for General Video Generation and Editing—0
Sparse Estimation with Structured Dictionaries—0
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient—0
Sparse Gaussian Process Hyperparameters: Optimize or Integrate?—0
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection—0
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