Spain

ECAI 2020

Refinement of Unsupervised Cross-Lingual Word Embeddings

representation learning

embeddings

natural language processing

unsupervised

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

NAML 2021

technical paper

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.

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

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

https://d3smihljt9218e.cloudfront.net/transcript/1244/subtitle/5ae8aba39816e9e8e430467e5ec01d74.vtt

English (automatic)

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

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Next from ECAI 2020

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

Similar lecture

Next Generation NLP and AI Methods in the Navy Contact Center

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