Spain

ECAI 2020

Complexity of Problems of Possible and Necessary Existence in Abstract Argumentation

nonemptiness problem

necessary existence problem

possible existence problem

incomplete argumentation framework

computational complexity

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

MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records

Robust Deep Subspace Discovery by a Multilayer Collaborative Low-Rank Coding Network

Hope Speech Detection: A Computational Analysis of the Voice of Peace

Classification Rules in Relaxed Logical Form

Learning Fairness-aware   Relational Structures

Abstract Interpretation based Robustness Certification for Graph Convolutional Networks

Object Allocation and Positive Graph Externalities

Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection

Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors

Dedge AGMNet

https://d3smihljt9218e.cloudfront.net/transcript/1208/subtitle/8fc96916326bb2dd78416674052b2db7.vtt

English (automatic)

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Next from ECAI 2020

MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records

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Abstract Argumentation with Markov Networks

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Next from ECAI 2020

MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records

Similar lecture

Abstract Argumentation with Markov Networks

Downloads