Spain

ECAI 2020

Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives

dynamic optimization

pareto

uncertainty

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!

Basic Utility Theory for Belief Functions

Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation

Mid-weight Image Super-Resolution with Bypass Connection Attention Network

Learning to Reuse Translations: Guiding Neural Machine Translation with Examples

Metric Learning for Ordered Labeled Trees with pq-grams

An Efficient Agreement Mechanism in CapsNets By Pairwise Product

Towards Efficient Discrete Integration via Adaptive Quantile Queries

Self-Attention-based Fully-Inception Networks for Continuous Sign Language Recognition

A Weighted GCN with Logical Adjacency Matrix for Relation Extraction

Negative-Aware Training: Be Aware of Negative Samples

https://d3smihljt9218e.cloudfront.net/transcript/1053/subtitle/a3a25f0656ad38721b7204059c3e6c83.vtt

English (automatic)

Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives

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Basic Utility Theory for Belief Functions

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Sample-dependent Adaptive Temperature Scaling for Improved Calibration

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Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives

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Next from ECAI 2020

Basic Utility Theory for Belief Functions

Similar lecture

Sample-dependent Adaptive Temperature Scaling for Improved Calibration

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES

Downloads