causal learning

DataFunTalk

Feb 24, 2024 · Artificial Intelligence

Causal Learning Paradigms: From Prior Causal Structure to Causal Discovery

This article introduces causal learning, explains its distinction from traditional correlation‑based machine learning, outlines its three main parts, discusses the two primary paradigms—learning with known causal graphs and learning via causal discovery—and highlights their advantages, challenges, and recent research directions.

causal discoverycausal inferencecausal learning

0 likes · 11 min read

Causal Learning Paradigms: From Prior Causal Structure to Causal Discovery

AntTech

Dec 11, 2023 · Artificial Intelligence

Ant Group Open-Sources OpenASCE: A Distributed Full-Stack Causal Learning System Presented at NeurIPS

At NeurIPS 2023, Ant Group unveiled OpenASCE, the industry's first open‑source distributed full‑link causal learning system, detailing its architecture, large‑scale capabilities, and real‑world applications in credit risk, marketing, and recommendation while emphasizing its role in advancing causal AI research.

AIAnt GroupDistributed Systems

0 likes · 5 min read

Ant Group Open-Sources OpenASCE: A Distributed Full-Stack Causal Learning System Presented at NeurIPS

DataFunSummit

Dec 9, 2023 · Artificial Intelligence

Causal Learning Paradigms: From Prior Causal Structure to Causal Discovery

This article reviews the growing interest in causal learning within machine learning, explaining what causal learning is, its advantages over purely correlational methods, and detailing two main paradigms—learning with known causal structures and learning via causal discovery—along with examples, challenges, and future directions.

causal discoverycausal inferencecausal learning

0 likes · 12 min read

DataFunSummit

Nov 7, 2023 · Artificial Intelligence

Instrumental Variable Based Causal Inference and Generalizable Causal Learning

This article presents a comprehensive overview of using instrumental variables for causal inference and causal generalization in machine learning, discussing deep learning limitations, Pearl's causal hierarchy, two‑stage regression, challenges with unobserved confounders, automatic IV generation, and applications in economics and social networks.

Generalizationartificial intelligencecausal inference

0 likes · 16 min read

Instrumental Variable Based Causal Inference and Generalizable Causal Learning

DataFunTalk

Dec 22, 2022 · Artificial Intelligence

Causal Inference: Core Concepts, Differences from Traditional Machine Learning, and Real‑World Applications in Finance

This article introduces the fundamental ideas of causal inference, explains how it differs from correlation‑based machine learning, discusses the role of confounders, and showcases practical implementations in financial services such as offer optimization, uplift modeling, and decision‑making pipelines.

Financial AIcausal inferencecausal learning

0 likes · 17 min read

Causal Inference: Core Concepts, Differences from Traditional Machine Learning, and Real‑World Applications in Finance

DaTaobao Tech

Oct 17, 2022 · Artificial Intelligence

AI Live Stream: Causal Representation Learning and Real-time Color Enhancement

In this AI Live Stream, two Taobao Technology engineers present how causal representation learning enables unbiased data augmentation and factor‑controllable generation to boost fine‑grained image classification, while also unveiling a real‑time color‑enhancement technique that merges cascaded lookup tables with dynamic neural networks, illustrating modern AI trends and practical deployment strategies.

AI algorithmsModel GeneralizationReal-time Processing

0 likes · 4 min read

AI Live Stream: Causal Representation Learning and Real-time Color Enhancement

Kuaishou Tech

Feb 14, 2022 · Artificial Intelligence

Machine Heart Column

Researchers propose a causal learning framework IV4Rec to separate causal and non-causal factors in recommendations using search data.

AIcausal learninginstrumental variables

0 likes · 17 min read

JD Cloud Developers

Feb 10, 2021 · Artificial Intelligence

How JD Tech’s Breakthrough AI Papers Dominated AAAI 2021

JD Tech showcased a remarkable 21-paper presence at AAAI 2021, covering federated learning, spatio‑temporal AI, recommendation systems, computer vision, and causal learning, highlighting the company’s transition from research to real‑world AI applications across smart cities, retail, and risk management.

AAAI 2021Federated Learningcausal learning

0 likes · 12 min read

How JD Tech’s Breakthrough AI Papers Dominated AAAI 2021