Spain

ECAI 2020

Strong Refinements for Hard Problems in Argumentation Dynamics

counterexample-guided abstraction refinement

af synthesis

status enforcement

extension enforcement

argumentation dynamics

abstract argumentation

implementation

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

Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

Polynomial-time Implicit Learnability in SMT

Generating Natural Language Adversarial Examples on a Large Scale with Generative Models

Joint Modeling of Local and Global Behavior Dynamics for Session-based Recommendation

Learning Chordal Markov Networks via Stochastic Local Search

Learning Variable Ordering Heuristics with Multi-Armed Bandits and Restarts

Learning Joint Job Embeddings using a Job-Oriented Asymmetrical Pairing System

Prioritized Simple Contrapositive Assumption-Based Frameworks

ET-GAN: Cross-Language Emotion Transfer Based on Cycle-Consistent Generative Adversarial Networks

Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy

https://d3smihljt9218e.cloudfront.net/transcript/1223/subtitle/d0bad0811e4935fc31c0390b0e3b74cc.vtt

English (automatic)

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Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

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Abstract Argumentation with Markov Networks

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Next from ECAI 2020

Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

Similar lecture

Abstract Argumentation with Markov Networks

Downloads