Generative Adversarial Networks

Alimama Tech

Sep 11, 2024 · Artificial Intelligence

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective

The paper introduces a coupled generative adversarial framework that merges biased observational with unbiased experimental data to create a bias‑free dataset for causal inference, enabling robust treatment‑effect estimation under collider bias from an out‑of‑distribution perspective, and demonstrates superior bias reduction on three public advertising datasets.

Generative Adversarial Networksadvertisingcausal inference

0 likes · 10 min read

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective

DataFunSummit

Dec 3, 2020 · Artificial Intelligence

GAN Fundamentals, Variants, and Practical Applications in Image Style Transfer and Handwriting Font Generation

This article provides a comprehensive overview of Generative Adversarial Networks, covering their original formulation, training dynamics, loss functions, major variants such as DCGAN and WGAN, and practical implementations for image‑to‑image translation, style transfer, and handwriting font synthesis at Laiye Technology.

GANGenerative Adversarial NetworksImage Translation

0 likes · 28 min read

GAN Fundamentals, Variants, and Practical Applications in Image Style Transfer and Handwriting Font Generation

Tencent Advertising Technology

Nov 26, 2020 · Artificial Intelligence

Representative Negative Instance Generation for Online Ad Targeting (RNIG)

Researchers from Tencent Ads and Tsinghua University introduced a novel Generative Adversarial framework, the Representative Negative Instance Generator (RNIG), which creates high‑quality representative negative samples from exposure data to mitigate data imbalance and selection bias, achieving superior performance on CIKM‑2020 ad targeting benchmarks.

Generative Adversarial NetworksRecommendation systemsad targeting

0 likes · 8 min read

Representative Negative Instance Generation for Online Ad Targeting (RNIG)

Laiye Technology Team

Nov 25, 2020 · Artificial Intelligence

Comprehensive Overview of GANs: History, Improvements, Applications, and Handwriting Style Transfer

This article provides an in‑depth overview of Generative Adversarial Networks (GANs), covering their original formulation, major variants such as DCGAN and WGAN, challenges like mode collapse, image‑to‑image translation techniques (cGAN, pix2pix, CycleGAN), and practical handwriting style‑transfer implementations using BicycleGAN and Zi2Zi.

GANGenerative Adversarial NetworksImage-to-Image Translation

0 likes · 27 min read

Comprehensive Overview of GANs: History, Improvements, Applications, and Handwriting Style Transfer

AntTech

Jun 10, 2019 · Artificial Intelligence

Generative Adversarial User Model for Reinforcement Learning‑Based Recommendation Systems

This article presents a model‑based reinforcement learning framework for recommendation systems that uses a generative adversarial user model to simultaneously learn user behavior dynamics and reward functions, enabling efficient Cascading‑DQN policy learning and achieving superior long‑term user rewards and click‑through rates in experiments.

Artificial IntelligenceCascading DQNGenerative Adversarial Networks

0 likes · 9 min read

Generative Adversarial User Model for Reinforcement Learning‑Based Recommendation Systems

JD Retail Technology

Nov 22, 2018 · Artificial Intelligence

Challenges and Innovations in Category Classification Systems

This article discusses the limitations of algorithm-based classification models, including the need for large labeled datasets, limited sample coverage, frequent category changes requiring retraining, and complex optimization issues, while exploring knowledge graph-based approaches and generative adversarial networks for more flexible and accurate classification.

Generative Adversarial NetworksKnowledge Graphsbad case optimization

0 likes · 6 min read

Challenges and Innovations in Category Classification Systems