Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond
Probing the Decision Boundaries of In-context Learning in Large Language Models
The harms of class imbalance corrections for machine learning based prediction models: a simulation study
From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers
Attention versus Contrastive Learning of Tabular Data—A Data-centric Benchmarking
Unambiguous discrimination of all 20 proteinogenic amino acids and their modifications by nanopore
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT
RGD: Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
Deep Learning based Forecasting: a case study from the online fashion industry
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes
TSMixer: An All-MLP Architecture for Time Series Forecasting
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
Fast semi-supervised self-training algorithm based on data editing
Why do tree-based models still outperform deep learning on tabular data?
Revisiting Pretraining Objectives for Tabular Deep Learning
TabPFN: Meta-Learning a Real-Time Tabular AutoML Method For Small Data
Predicting romantic interest during early relationship development: A preregistered investigation using machine learning
On Embeddings for Numerical Features in Tabular Deep Learning
M5 accuracy competition: Results, findings, and conclusions
The GatedTabTransformer: An enhanced deep learning architecture for tabular modeling
DANets: Deep Abstract Networks for Tabular Data Classification and Regression
An Unsupervised Model for Identifying and Characterizing Dark Web Forums
TAPEX: Table Pre-training via Learning a Neural SQL Executor
ARM-Net: Adaptive Relation Modeling Network for Structured Data
Decision tree heuristics can fail, even in the smoothed setting
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption
The Epic Sepsis Model Falls Short—The Importance of External Validation
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
Intelligence and General Psychopathology in the Vietnam Experience Study: A Closer Look
Converting tabular data into images for deep learning with convolutional neural networks
External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Kaggle forecasting competitions: An overlooked learning opportunity
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
Neural Additive Models: Interpretable Machine Learning with Neural Nets
A Market in Dream: the Rapid Development of Anonymous Cybercrime
VIME: Extending the Success of Self-supervised and Semi-supervised Learning to Tabular Domain
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
3D human pose estimation via human structure-aware fully connected network
Behavioral Patterns in Smartphone Usage Predict Big Five Personality Traits
Asymptotic learning curves of kernel methods: empirical data versus Teacher-Student paradigm
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data
Tweedie Gradient Boosting for Extremely Unbalanced Zero-inflated Data
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL
Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario
Resource-Efficient Machine Learning in 2 KB RAM for the Internet of Things
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Leakage in Data Mining: Formulation, Detection, and Avoidance
Tree Induction vs. Logistic Regression: A Learning-Curve Analysis
On the Boosting Ability of Top-Down Decision Tree Learning Algorithms
On The Effect of Data Set Size on Bias And Variance in Classification Learning
The Effects of Training Set Size on Decision Tree Complexity
Scaling up the accuracy of Naive-Bayes classifiers: a decision-tree hybrid
The MONK’s Problems-A Performance Comparison of Different Learning Algorithms
Symbolic and neural learning algorithms: An experimental comparison
2022-grinsztajn-figure9-treesvsneuralnetson4classificationtasksusingnumericalfeaturesonmediumvslargedatasets.png
https://spectrum.ieee.org/its-too-easy-to-hide-bias-in-deeplearning-systems
https://www.maskaravivek.com/post/gan-synthetic-data-generation/
https://www.oneusefulthing.org/p/it-is-starting-to-get-strange
https://www.reddit.com/r/Anki/comments/1c29775/fsrs_is_one_of_the_most_accurate_spaced/
https://www.thelancet.com/journals/lanhl/article/PIIS2666-7568(23)00189-7/fulltext
Probing the Decision Boundaries of In-context Learning in Large Language Models
From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
RGD: Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
https%253A%252F%252Farxiv.org%252Fabs%252F2306.09222%2523google.html
TSMixer: An All-MLP Architecture for Time Series Forecasting
https%253A%252F%252Farxiv.org%252Fabs%252F2303.06053%2523google.html
https%253A%252F%252Fwww.sciencedirect.com%252Fscience%252Farticle%252Fpii%252FS0169207021001679.html
TabPFN: Meta-Learning a Real-Time Tabular AutoML Method For Small Data
Predicting romantic interest during early relationship development: A preregistered investigation using machine learning
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M5 accuracy competition: Results, findings, and conclusions
https%253A%252F%252Fwww.sciencedirect.com%252Fscience%252Farticle%252Fpii%252FS0169207021001874.html
Asymptotic learning curves of kernel methods: empirical data versus Teacher-Student paradigm
Tree Induction vs. Logistic Regression: A Learning-Curve Analysis
On the Boosting Ability of Top-Down Decision Tree Learning Algorithms
https%253A%252F%252Fwww.sciencedirect.com%252Fscience%252Farticle%252Fpii%252FS0022000097915439.html
