Spain

ECAI 2020

Regret-Based Elicitation for Solving Multi-Objective Knapsack Problems with Rank-Dependent Aggregators

choquet integrals

knapsack problems

incremental elicitation

interactive method

multi-objective combinatorial optimization

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

Learning Kernel-based Embeddings in Graph Neural Networks

Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation

Dynamic Epistemic Logic Games with Epistemic Temporal Goals

New measures of inclusion between fuzzy sets in terms of the φ-index of inclusion

Representing and Reducing Uncertainty for Enumerating the Belief Space to Improve Endgame Play in Skat

Ontology Focusing: Knowledge-enriched Databases on Demand

A Hash Learning Framework for Search-Oriented Knowledge Graph Embedding

Link Prediction by Analyzing Common Neighbors Based Subgraphs using Convolutional Neural Network

Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms

Pruning CNN's with linear filter ensembles

https://d3smihljt9218e.cloudfront.net/transcript/1247/subtitle/a7e72f19adc4d4e46ee50437a2916f8b.vtt

English (automatic)

Regret-Based Elicitation for Solving Multi-Objective Knapsack Problems with Rank-Dependent Aggregators

Downloads

Next from ECAI 2020

Learning Kernel-based Embeddings in Graph Neural Networks

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New computational models for the Choquet Integral

Regret-Based Elicitation for Solving Multi-Objective Knapsack Problems with Rank-Dependent Aggregators

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Next from ECAI 2020

Learning Kernel-based Embeddings in Graph Neural Networks

Similar lecture

New computational models for the Choquet Integral

Downloads