Spain

ECAI 2020

Analysis of reduced costs filtering for alldifferent and minimum weight alldifferent global constraints

minimum weight alldifferent

global constraints

reduced-costs based filtering

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities. This includes talks to attend in person, talks to attend remotely, breaks with colleagues and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).

In order to access this site, you need to register. If you haven't already, please register [here](https://aaai.org/Conferences/AAAI-23/registration/).


AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

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.

Automatic Generation of Typicality Measures for Spatial Language in Grounded Settings

Speeding Up CDCL Inference With Duplicate Learnt Clauses

PushNet: Efficient and Adaptive Neural Message Passing

Point Cloud Segmentation with Deep Reinforcement Learning

Algebraic Circuits for Decision Theoretic Inference and Learning

AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues

Neighborhood-based Pooling for Population-level Label Distribution Learning

Decoding the Imitation Security Game: Handling Attacker Imitative Behavior Deception

Tackling Imitative Attacker Deception in Repeated Bayesian Stackelberg Security Games

STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment

https://d3smihljt9218e.cloudfront.net/transcript/1124/subtitle/6e4d6f7d4135baf9e62eccb8b427eb23.vtt

English (automatic)

Analysis of reduced costs filtering for alldifferent and minimum weight alldifferent global constraints

Downloads

Next from ECAI 2020

Automatic Generation of Typicality Measures for Spatial Language in Grounded Settings

Similar lecture

DeepGemini: Verifying Dependency Fairness for Deep Neural Network

Analysis of reduced costs filtering for alldifferent and minimum weight alldifferent global constraints

.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

Automatic Generation of Typicality Measures for Spatial Language in Grounded Settings

Similar lecture

DeepGemini: Verifying Dependency Fairness for Deep Neural Network

Downloads