Spain

ECAI 2020

Feature-level Ensemble Knowledge Distillation for Aggregating Knowledge from Multiple Networks

feature-level distillation

knowledge distillation

model compression

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.

Crowd Counting via Hierarchical Scale Recalibration Network

Learning a Latent Space of Style-Aware Symbolic Music Representations by Adversarial Autoencoders

Adaptive Local Neighbors for Transfer Discriminative Feature Learning

Analysing Irresolute Multiwinner Voting Rules via SAT solving

DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners

Learning Deterministic Automata on Infinite Words

Polynomial Neural Networks and Taylor maps for Dynamical Systems Simulation and Learning

Learning classifier chains using matrix regularization: application to multimorbidity prediction

Abstract Argumentation with Markov Networks

IAD: A Benchmark Dataset and a New Method for Illegal Advertising Classification

https://d3smihljt9218e.cloudfront.net/transcript/991/subtitle/0171018c11d0155d7ca960488f206d5c.vtt

English (automatic)

Feature-level Ensemble Knowledge Distillation for Aggregating Knowledge from Multiple Networks

Downloads

Next from ECAI 2020

Crowd Counting via Hierarchical Scale Recalibration Network

Similar lecture

Bespoke: A Block-Level Neural Network Optimization Framework for Low-Cost Deployment

Feature-level Ensemble Knowledge Distillation for Aggregating Knowledge from Multiple Networks

.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

Crowd Counting via Hierarchical Scale Recalibration Network

Similar lecture

Bespoke: A Block-Level Neural Network Optimization Framework for Low-Cost Deployment

Downloads