Can a 2M‑Parameter Model Outperform XGBoost? Inside LimiX‑2M’s Tabular AI Breakthrough

The article examines LimiX‑2M, a lightweight 2‑million‑parameter transformer‑based model for structured tabular data that, through a novel Radial Basis Function embedding layer, achieves classification and regression performance surpassing traditional gradient‑boosting methods like XGBoost and even larger AI models, while remaining easy to fine‑tune and deploy.

LimiXRBF embeddingStructured Data

0 likes · 10 min read

Can a 2M‑Parameter Model Outperform XGBoost? Inside LimiX‑2M’s Tabular AI Breakthrough

Alibaba Cloud Big Data AI Platform

Mar 15, 2024 · Artificial Intelligence

Why Arithmetic Feature Interaction Is Key to Deep Tabular Learning

Researchers from Alibaba Cloud AI and Zhejiang University present AMFormer, a Transformer‑based model that incorporates arithmetic feature interaction, demonstrating superior fine‑grained modeling, sample efficiency, and generalization on synthetic and real‑world tabular datasets, establishing a new state‑of‑the‑art in deep tabular learning.

AMFormerDeep LearningTransformer

0 likes · 12 min read

Why Arithmetic Feature Interaction Is Key to Deep Tabular Learning

Alibaba Cloud Big Data AI Platform

Mar 12, 2024 · Artificial Intelligence

AAAI‑2024 Highlights: Alibaba Cloud’s Deep Tabular Learning & Multi‑Modal Fusion

Alibaba Cloud’s AI platform PAI showcased four cutting‑edge papers at AAAI‑2024—introducing AMFormer for deep tabular learning via arithmetic feature interaction, MuLTI for efficient video‑language understanding, M2SD for few‑shot class‑incremental learning, and M2Doc for multi‑modal document layout analysis—demonstrating the platform’s growing impact on artificial‑intelligence research.

Deep LearningFew‑Shot LearningMultimodal AI

0 likes · 9 min read

AAAI‑2024 Highlights: Alibaba Cloud’s Deep Tabular Learning & Multi‑Modal Fusion

GuanYuan Data Tech Team

Jun 16, 2022 · Artificial Intelligence

How Deepchecks Automates Data and Model Validation for Reliable AI Pipelines

This article introduces the open‑source Deepchecks library, explains its core concepts of checks, conditions, and suites, and provides step‑by‑step tutorials for data validation, train‑test validation, and model evaluation to help AI engineers build robust, data‑centric machine‑learning workflows.

Pythondata validationdeepchecks

0 likes · 15 min read

How Deepchecks Automates Data and Model Validation for Reliable AI Pipelines

Baobao Algorithm Notes

Dec 10, 2021 · Artificial Intelligence

AutoX: One-Click Tabular AutoML from Feature Engineering to Model Fusion

AutoX offers a one‑click solution for tabular AutoML by defining feature operators, constructing a searchable feature space, applying efficient feature selection, tuning hyper‑parameters, and performing model ensembling, enabling users with limited ML expertise to automatically generate high‑performing predictive models, as demonstrated on multiple Kaggle datasets.

AutoMLAutoXMachine Learning Automation

0 likes · 7 min read

AutoX: One-Click Tabular AutoML from Feature Engineering to Model Fusion

DataFunTalk

Sep 11, 2019 · Artificial Intelligence

AutoML for Tabular Data: Research, Techniques, and Applications

This talk presents the research and practical deployment of AutoML for tabular data, covering background, automated feature engineering and selection, hyper‑parameter optimization, the AutoCross feature‑crossing system, case studies, and future directions, demonstrating its advantages over Google Cloud AutoML on multiple Kaggle competitions.

AutoMLfeature engineeringhyperparameter optimization

0 likes · 14 min read

AutoML for Tabular Data: Research, Techniques, and Applications