Spain

ECAI 2020

Enhanced foraging in robot swarms using collective Lévy walks

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robot swarms

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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

General Supervision via Probabilistic Transformations

Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms

Heuristics for Link Prediction in Multiplex Networks

SSHFD: Single Shot Human Fall Detection with Occluded Joints Resilience

Ensemble Knowledge Distillation for Learning Improved and Efficient Networks

EPNE: Evolutionary Pattern Preserving Network Embedding

Lifting Majority to Unanimity in Opinion Diffusion

Dynamic thresholding for learning sparse neural networks

A Region Selection Model to Identify Unknown Unknowns in Image Datasets

End-To-End Speech Emotion Recognition Based on Time and Frequency Information Using Deep Neural Networks

https://d3smihljt9218e.cloudfront.net/transcript/1001/subtitle/83cba11fe3e680ce35b73a32c130fd3a.vtt

English (automatic)

Enhanced foraging in robot swarms using collective Lévy walks

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General Supervision via Probabilistic Transformations

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On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data

Enhanced foraging in robot swarms using collective Lévy walks

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Next from ECAI 2020

General Supervision via Probabilistic Transformations

Similar lecture

On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data

Downloads