Spain

ECAI 2020

SETNet : A Novel Semi-Supervised Approach for Semantic Parsing

semantic parsing

semi-supervised learning

multi-task learning

## Welcome to NAACL 2022!
The Annual Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL) is taking place July 10-15, 2022 as a hybrid event, in Seattle, WA and online. We are happy to welcome all of you to conference! 
 
The main conference program features oral presentations, in-person and virtual posters and demo sessions, a plenary session for our best paper presentations and awards, keynote presentations, a plenary panel on the place of linguistics and symbolic structures in NLP, and an Industrial Track panel on Careers in NLP.
 
Posters (including Findings of NAACL 2022) and demos are grouped by areas for both the in-person and the virtual sessions. For the virtual component, the talks will be on Zoom and the posters and the demos will be in GatherTown. The Student Research Workshop and will have an oral session and a poster session.
 
The program also features 6 Tutorials and 26 Workshops.
 
 We wish you a wonderful conference!
 
[The NAACL 2022 Organizing Committee](https://2022.naacl.org/committees/organization/)

NAACL 2022

2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics

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.

A Knowledge-driven Approach to Explaining Black-box Models

Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map

Learning Conjunctive Information   of Signals in Multi-sensor Systems

Tree search for the Sequential Ordering Problem

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

Multi-Stage Transfer Learning with an Application to Selection Process

Improving Supervised Superpixel-Based Codebook Representations by Local Convolutional Features

Incorporating Semantic Dependencies Extracted from Knowledge Graphs into Joint Inference template-based Information Extraction

On Measuring Inconsistency in Relational Databases with Denial Constraints

Classifying the classifier: dissecting the weight space of neural networks

https://d3smihljt9218e.cloudfront.net/transcript/1181/subtitle/9779b51d087ec31bbe0184dcdc368e44.vtt

English (automatic)

Downloads

Next from ECAI 2020

A Knowledge-driven Approach to Explaining Black-box Models

Similar lecture

Progressive Class Semantic Matching for Semi-supervised Text Classification

.css-70qvj9{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}Downloads

Next from ECAI 2020

A Knowledge-driven Approach to Explaining Black-box Models

Similar lecture

Progressive Class Semantic Matching for Semi-supervised Text Classification

Downloads