Spain

ECAI 2020

Generative Adversarial Networks for Mitigating Biases in Machine Learning Systems

mitigating biases

machine learning

generative adversarial networks

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

technical paper

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

Online Probabilistic Interval-based Event Calculus

Saliency Detection with Deformable Convolution and Feature Attention

Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings

Extended Markov Games to Learn Complex Specifications in Multi-Agent Reinforcement Learning

Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search

Conference Presentation Recording for ECAI2020 paper 'Adaptive Graph Reasoning Network for Fashion Landmark Detection'

Feature-level Ensemble Knowledge Distillation for Aggregating Knowledge from Multiple Networks

Crowd Counting via Hierarchical Scale Recalibration Network

Learning a Latent Space of Style-Aware Symbolic Music Representations by Adversarial Autoencoders

https://d3smihljt9218e.cloudfront.net/transcript/980/subtitle/e3705972a55582c1b65eda504b246bdb.vtt

English (automatic)

Downloads

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A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

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Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

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Next from ECAI 2020

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

Similar lecture

Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

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