SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1100 of 2050 papers

TitleStatusHype
Progressive Sampling-Based Bayesian Optimization for Efficient and Automatic Machine Learning Model Selection—0
Prompt Design Matters for Computational Social Science Tasks but in Unpredictable Ways—0
PromptWise: Online Learning for Cost-Aware Prompt Assignment in Generative Models—0
Propagation Regularizer for Semi-Supervised Learning With Extremely Scarce Labeled Samples—0
Proximity Operator of the Matrix Perspective Function and its Applications—0
Pseudo Label Selection is a Decision Problem—0
PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems—0
Pushing the limits of fairness impossibility: Who's the fairest of them all?—0
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs—0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection—0
Qualitative inequalities for squared partial correlations of a Gaussian random vector—0
Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice—0
Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces—0
Quantifying the Capability Boundary of DeepSeek Models: An Application-Driven Performance Analysis—0
Quantifying Uncertainty and Variability in Machine Learning: Confidence Intervals for Quantiles in Performance Metric Distributions—0
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles—0
Quantile Factor Models—0
Quantile universal threshold: model selection at the detection edge for high-dimensional linear regression—0
Quantized Neural Networks: Characterization and Holistic Optimization—0
Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities—0
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models—0
Radar Cross Section Based Statistical Recognition of UAVs at Microwave Frequencies—0
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption—0
Random Models for Fuzzy Clustering Similarity Measures—0
Ranking pre-trained segmentation models for zero-shot transferability—0
Ranking & Reweighting Improves Group Distributional Robustness—0
Rate-adaptive model selection over a collection of black-box contextual bandit algorithms—0
Rational kernel-based interpolation for complex-valued frequency response functions—0
Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme—0
Realistic Evaluation of Deep Partial-Label Learning Algorithms—0
Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection—0
Real-time Monocular Depth Estimation with Sparse Supervision on Mobile—0
Reassessing Large Language Model Boolean Query Generation for Systematic Reviews—0
Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood—0
Recommending Pre-Trained Models for IoT Devices—0
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence—0
Reduced-order modeling using Dynamic Mode Decomposition and Least Angle Regression—0
ReeM: Ensemble Building Thermodynamics Model for Efficient HVAC Control via Hierarchical Reinforcement Learning—0
Reframing Neural Networks: Deep Structure in Overcomplete Representations—0
Region Detection in Markov Random Fields: Gaussian Case—0
Regret Balancing for Bandit and RL Model Selection—0
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL—0
Regularity Normalization: Constraining Implicit Space with Minimum Description Length—0
Regularization for Cox's proportional hazards model with NP-dimensionality—0
Regularized Bilinear Discriminant Analysis for Multivariate Time Series Data—0
Regularized DeepIV with Model Selection—0
Regularized Modal Regression with Applications in Cognitive Impairment Prediction—0
Reinforcement Learning based Dynamic Model Selection for Short-Term Load Forecasting—0
Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting—0
Reinforcement Learning for Machine Learning Model Deployment: Evaluating Multi-Armed Bandits in ML Ops Environments—0
Show:102550
← PrevPage 22 of 41Next →

No leaderboard results yet.