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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 51–100 of 2050 papers

TitleStatusHype
Thompson Sampling-like Algorithms for Stochastic Rising Bandits—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model SelectionCode0
A Systematic Analysis of Base Model Choice for Reward Modeling—0
Supervised Models Can Generalize Also When Trained on Random LabelCode0
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework—0
Tuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization—0
Reassessing Large Language Model Boolean Query Generation for Systematic Reviews—0
Uncertainty Profiles for LLMs: Uncertainty Source Decomposition and Adaptive Model-Metric Selection—0
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model—0
High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality—0
Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal—0
Machine Learning: a Lecture Note—0
Multimodal Benchmarking and Recommendation of Text-to-Image Generation ModelsCode0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
Solar Flare Forecast: A Comparative Analysis of Machine Learning Algorithms for Solar Flare Class PredictionCode0
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling—0
Mallows-type model averaging: Non-asymptotic analysis and all-subset combination—0
Logits-Constrained Framework with RoBERTa for Ancient Chinese NER—0
ReeM: Ensemble Building Thermodynamics Model for Efficient HVAC Control via Hierarchical Reinforcement Learning—0
A Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications—0
A-DARTS: Stable Model Selection for Data Repair in Time SeriesCode0
LENSLLM: Unveiling Fine-Tuning Dynamics for LLM SelectionCode1
Generative diffusion model surrogates for mechanistic agent-based biological models—0
Towards Robust and Generalizable Gerchberg Saxton based Physics Inspired Neural Networks for Computer Generated Holography: A Sensitivity Analysis Framework—0
Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare—0
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
OpenTCM: A GraphRAG-Empowered LLM-based System for Traditional Chinese Medicine Knowledge Retrieval and Diagnosis—0
Optimizing Hard Thresholding for Sparse Model Discovery—0
Evaluating Meta-Regression Techniques: A Simulation Study on Heterogeneity in Location and Time—0
Topological model selection: a case-study in tumour-induced angiogenesis—0
Transfer Learning via Auxiliary Labels with Application to Cold-Hardiness Prediction—0
Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?—0
Physics-Aware Initialization Refinement in Code-Aided EM for Blind Channel Estimation—0
Meta-Evaluating Local LLMs: Rethinking Performance Metrics for Serious Games—0
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes—0
Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability—0
What the HellaSwag? On the Validity of Common-Sense Reasoning BenchmarksCode0
Robust Social Planning—0
M-Prometheus: A Suite of Open Multilingual LLM JudgesCode5
Model Selection via MCRB Optimization—0
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical SystemsCode0
Instruction-Guided Autoregressive Neural Network Parameter Generation—0
Efficient Model Selection for Time Series Forecasting via LLMs—0
Optimizing Humor Generation in Large Language Models: Temperature Configurations and Architectural Trade-offs—0
Why risk matters for protein binder design—0
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting—0
Neural Bayes inference for complex bivariate extremal dependence modelsCode0
Reinforcement Learning for Machine Learning Model Deployment: Evaluating Multi-Armed Bandits in ML Ops Environments—0
Collab: Controlled Decoding using Mixture of Agents for LLM Alignment—0
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