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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.

Source: Kernel-based Information Criterion

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/montenegroalessandro/bestarmidsrb

공식 코드

Best Arm Identification for Stochastic Rising Bandits

https://github.com/morningmoni/unipelt

공식 코드

UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning

https://github.com/mosco/unsupervised-preprocessing

공식 코드

On the cross-validation bias due to unsupervised pre-processing

https://github.com/mperezortiz/PBB

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Tighter risk certificates for neural networks

https://github.com/mrc-ide/referenced-TI

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Referenced Thermodynamic Integration for Bayesian Model Selection: Application to COVID-19 Model Selection

https://github.com/mrucker/onoff_experiments

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Infinite Action Contextual Bandits with Reusable Data Exhaust

https://github.com/msabvid/robust_nsde

공식 코드

Robust pricing and hedging via neural SDEs

https://github.com/mushfiqur11/tokenfreetransfer

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To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer

https://github.com/namtrankekl/symmetric-linear-bandit-with-hidden-symmetry

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Symmetric Linear Bandits with Hidden Symmetry

https://github.com/namyongpark/metagl

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MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning

https://github.com/nanshineloong/self-evolving-benchmark

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Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation

https://github.com/national-center-for-ai-saudi-arabia/lm-evaluation-harness

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When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards

https://github.com/navarog/cross-validated-ope

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Cross-Validated Off-Policy Evaluation

https://github.com/neelabhsinha/vlm-selection-tasks-domains-knowledge-type

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Guiding Vision-Language Model Selection for Visual Question-Answering Across Tasks, Domains, and Knowledge Types

https://github.com/networkgeometry/hyperbolic-benchmark-gnn

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Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance

https://github.com/neulab/data-agora

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Evaluating Language Models as Synthetic Data Generators

https://github.com/neuromat/eeg-tree-algorithms

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Context tree selection for functional data

https://github.com/ngoc-vien-dang/fairml-depression

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Fairness and bias correction in machine learning for depression prediction: results from four study populations

https://github.com/nivgold/dfpe

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DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM Performance

https://github.com/nliulab/FedScore

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FedScore: A privacy-preserving framework for federated scoring system development

https://github.com/nliulab/autoscore-ordinal

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AutoScore-Ordinal: An interpretable machine learning framework for generating scoring models for ordinal outcomes

https://github.com/noslenh/SeqROCTM-Matlab-Toolbox

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SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models

https://github.com/now-join-us/cit-llm-routing

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Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing

https://github.com/nrkarthikeyan/topology-decision-boundaries

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Topological Data Analysis of Decision Boundaries with Application to Model Selection

https://github.com/nsfzyzz/generalization_metrics_for_nlp

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Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

https://github.com/nyuad-cai/COVID19Complications

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Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study

https://github.com/of2/cbma_paper_simulations

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clusterBMA: Bayesian model averaging for clustering

https://github.com/of2/clusterbma

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clusterBMA: Bayesian model averaging for clustering

https://github.com/opengvlab/multitask-model-selector

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Foundation Model is Efficient Multimodal Multitask Model Selector

https://github.com/orrzohar/lovm

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LOVM: Language-Only Vision Model Selection

https://github.com/owenzx/InstabilityAnalysis

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The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions

https://github.com/panyidong/insurautoml

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Automated Machine Learning in Insurance

https://github.com/parleyyang/dms-ae-daa

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DMS, AE, DAA: methods and applications of adaptive time series model selection, ensemble, and financial evaluation

https://github.com/pascalinedescloux/lasso-zero

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Model selection with lasso-zero: adding straw to the haystack to better find needles

https://github.com/pascalinedescloux/robust-lasso-zero-NA

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Robust Lasso-Zero for sparse corruption and model selection with missing covariates

https://github.com/pascalrink/mabt-experiments

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Post-Selection Confidence Bounds for Prediction Performance

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