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tabular-classification

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Showing 26–48 of 48 papers

TitleStatusHype
Bayesian Concept Bottleneck Models with LLM PriorsCode0
STAND: Data-Efficient and Self-Aware Precondition Induction for Interactive Task Learning—0
Improving GBDT Performance on Imbalanced Datasets: An Empirical Study of Class-Balanced Loss FunctionsCode0
Transformers with Stochastic Competition for Tabular Data ModellingCode0
Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMs—0
MSBoost: Using Model Selection with Multiple Base Estimators for Gradient BoostingCode0
Tokenize features, enhancing tables: the FT-TABPFN model for tabular classification—0
Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications—0
Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks—0
The Disagreement Problem in Faithfulness Metrics—0
Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications—0
Improve Deep Forest with Learnable Layerwise Augmentation Policy ScheduleCode0
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck—0
A Suite of Fairness Datasets for Tabular Classification—0
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization—0
Is margin all you need? An extensive empirical study of active learning on tabular data—0
PTab: Using the Pre-trained Language Model for Modeling Tabular Data—0
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble ModelsCode0
Fieldwise Factorized Networks for Tabular Data Classification—0
CARE: Coherent Actionable Recourse based on Sound Counterfactual ExplanationsCode0
SCARF: Self-Supervised Contrastive Learning using Random Feature CorruptionCode0
Metalearning Using Structure-rich Pipeline Representations for Better AutoML—0
Ensemble Squared: A Meta AutoML System—0
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