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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 1901–1950 of 2050 papers

TitleStatusHype
Towards Portfolios of Streamlined Constraint Models: A Case Study with the Balanced Academic Curriculum ProblemCode0
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough PatentsCode0
Defining Expertise: Applications to Treatment Effect EstimationCode0
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge DistillationCode0
The information bottleneck and geometric clusteringCode0
Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric PerspectiveCode0
Investigating the Impact of Independent Rule Fitnesses in a Learning Classifier SystemCode0
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A SurveyCode0
Model selection for contextual banditsCode0
SMLSOM: The shrinking maximum likelihood self-organizing mapCode0
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model SelectionCode0
NYTRO: When Subsampling Meets Early StoppingCode0
DeepNNK: Explaining deep models and their generalization using polytope interpolationCode0
Iterative Hard Thresholding for Model Selection in Genome-Wide Association StudiesCode0
Finding Materialized Models for Model ReuseCode0
Combining Model and Parameter Uncertainty in Bayesian Neural NetworksCode0
Joint Inference for Neural Network Depth and Dropout RegularizationCode0
Odd-One-Out Representation LearningCode0
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT RankersCode0
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly DetectionCode0
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical SystemsCode0
Offline detection of change-points in the mean for stationary graph signalsCode0
Ranking vs. Classifying: Measuring Knowledge Base Completion QualityCode0
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and FairnessCode0
Know2Vec: A Black-Box Proxy for Neural Network RetrievalCode0
Solar Flare Forecast: A Comparative Analysis of Machine Learning Algorithms for Solar Flare Class PredictionCode0
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source LayoutCode0
LaF: Labeling-Free Model Selection for Automated Deep Neural Network ReusingCode0
Solution Path Algorithm for Twin Multi-class Support Vector MachineCode0
Best Arm Identification for Stochastic Rising BanditsCode0
Changing the Kernel During Training Leads to Double Descent in Kernel RegressionCode0
One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual TransferCode0
LaPLACE: Probabilistic Local Model-Agnostic Causal ExplanationsCode0
Deep Generalized Method of Moments for Instrumental Variable AnalysisCode0
Cold Case: The Lost MNIST DigitsCode0
The Merging Path Plot: adaptive fusing of k-groups with likelihood-based model selectionCode0
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A SurveyCode0
Clustering Indices based Automatic Classification Model SelectionCode0
A Realistic Protocol for Evaluation of Weakly Supervised Object LocalizationCode0
Large Scale Correlation Clustering OptimizationCode0
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature ExtractorsCode0
LASSO-ODE: A framework for mechanistic model identifiability and selection in disease transmission modelingCode0
A principled approach to model validation in domain generalizationCode0
Last Layer Marginal Likelihood for Invariance LearningCode0
Warlock: an automated computational workflow for simulating spatially structured tumour evolutionCode0
Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre studyCode0
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal InferenceCode0
LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously ThoughtCode0
Deeper Insights into Graph Convolutional Networks for Semi-Supervised LearningCode0
Adaptive Concentration of Regression Trees, with Application to Random ForestsCode0
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