Spain

ECAI 2020

Unsupervised Learning of Interpretable Dialog Models

bayesian

latent variable

dialog

The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. It is supported by the [Association for Uncertainty in Artificial Intelligence (AUAI).](https://www.auai.org/)

The 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) is held fully online. We have an exciting program consisting of keynote talks by [Susan Murphy](https://www.auai.org/uai2021/program?block=A), [Eric Horvitz](https://www.auai.org/uai2021/program?block=B), [Lenka Zdeborová](https://www.auai.org/uai2021/program?block=C), [Judea Pearl](https://www.auai.org/uai2021/program?block=D) and [Ankur Moitra](https://www.auai.org/uai2021/program?block=E), a town hall meeting, peer-reviewed papers, and three workshops. The main conference is single-track and each paper is show-cased with a live component (either a live discussion and Q&A, or a live lightning talk). All papers are also featured in video presentations and in poster sessions in gather.town. The three parallel workshops on Friday allow for smaller meetings on current topics.

The walkthrough video below shows how you can navigate this site and use the different possibilities for interaction: UAIsland2021 on gather.town for posters and social interactions, the mementor platform for virtual mentoring sessions, and the chat and Q&A systems for discussions about talks and posters.

Have a great UAI 2021! 
<br>
<br>Cassio de Campos and Marloes Maathuis
<br>UAI 2021 Program Chairs
<br>uai2021programchairs@gmail.com

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A ticket is required to access this conference. Please use the provided link to register for the event.

https://auai.org/uai2021/registration

UAI 2021

The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. It is supported by the [Association for Uncertainty in Artificial Intelligence (AUAI).](https://www.auai.org/)

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.

NASS: Optimizing Secure Inference via Neural Architecture Search

A Multi-Task Learning Neural Network for Emotion-Cause Pair Extraction

Building a Multi-domain Neural Machine Translation Model using Knowledge Distillation

QuantumWeighted Model Counting

A Variant of Recurrent Entity Networks for Targeted Aspect-Based Sentiment Analysis

Leveraging Human Prior Knowledge to Learn Sense Representations

Secure Social Recommendation based on Secret Sharing

Understanding and Training Deep Diagonal Circulant Neural Networks

Harmonic Recurrent Process for Time Series Forecasting

IntuiGeo: Interactive tutor for online geometry problems resolution on pen-based tablets

https://d3smihljt9218e.cloudfront.net/transcript/1011/subtitle/f80a3afbba0a5fa60e99d03aab2a0695.vtt

English (automatic)

Unsupervised Learning of Interpretable Dialog Models

Downloads

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NASS: Optimizing Secure Inference via Neural Architecture Search

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A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery

Unsupervised Learning of Interpretable Dialog Models

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Next from ECAI 2020

NASS: Optimizing Secure Inference via Neural Architecture Search

Similar lecture

A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery

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