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Model Selection
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits
Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One
Second-Order Convergence in Private Stochastic Non-Convex Optimization
LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought
An Asymptotic Equation Linking WAIC and WBIC in Singular Models
Truth or Twist? Optimal Model Selection for Reliable Label Flipping Evaluation in LLM-based Counterfactuals
Choosing a Model, Shaping a Future: Comparing LLM Perspectives on Sustainability and its Relationship with AI
DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management
AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection
PEER pressure: Model-to-Model Regularization for Single Source Domain Generalization
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
High-Dimensional Dynamic Covariance Models with Random Forests
Exploring the Potential of SSL Models for Sound Event Detection
Thompson Sampling-like Algorithms for Stochastic Rising Bandits
Zero-Shot Forecasting Mortality Rates: A Global Study
A Systematic Analysis of Base Model Choice for Reward Modeling
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model Selection
Supervised Models Can Generalize Also When Trained on Random Label
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
Reassessing Large Language Model Boolean Query Generation for Systematic Reviews
Uncertainty Profiles for LLMs: Uncertainty Source Decomposition and Adaptive Model-Metric Selection
Tuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model
High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality
Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example
Solar Flare Forecast: A Comparative Analysis of Machine Learning Algorithms for Solar Flare Class Prediction
Machine Learning: a Lecture Note
Multimodal Benchmarking and Recommendation of Text-to-Image Generation Models
ReeM: Ensemble Building Thermodynamics Model for Efficient HVAC Control via Hierarchical Reinforcement Learning
Mallows-type model averaging: Non-asymptotic analysis and all-subset combination
Logits-Constrained Framework with RoBERTa for Ancient Chinese NER
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling
A Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications
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