Spain

ECAI 2020

Pruning CNN&#39;s with linear filter ensembles

filter importance

filter pruning

network compression

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/)

Pruning CNN's with linear filter ensembles

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.

On the Relation between Claim-augmented Argumentation Frameworks and Collective Attacks

Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques

Incentivize Diffusion with Fair Rewards

Dynamic Algorithm Configuration:Foundation of a New Meta-Algorithmic Framework

CDeepEx: Contrastive Deep Explanations

Variational Objectives for Markovian Dynamics with Backward Simulation;

Combination of Active Learning and Self-Paced Learning for Deep Answer Selection with Bayesian Neural Network

Fleet-Wide Policy Iteration using Gaussian Processes

Learning Normative Behaviors through Abstraction

A Formal Model of Affordances for Flexible Robotic Task Execution

https://d3smihljt9218e.cloudfront.net/transcript/1254/subtitle/80eab5ea746f4a0bf4c92c3a1aa7d971.vtt

English (automatic)

Downloads

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On the Relation between Claim-augmented Argumentation Frameworks and Collective Attacks

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Next from ECAI 2020

On the Relation between Claim-augmented Argumentation Frameworks and Collective Attacks

Similar lecture

Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle

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