activity
20202022
most citedARCADe: A Rapid Continual Anomaly Detector

8 citations · 11 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2022★ 2 cited

CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering

Yao Zhang, Haokun Chen, Ahmed Frikha +5

Visual Question Answering (VQA) is a multi-discipline research task. To produce the right answer, it requires an understanding of the visual content of images, the natural language…

cs.LG2022★ 1 cited

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation

Haokun Chen, Ahmed Frikha, Denis Krompass +2

Federated Learning (FL) is a decentralized learning paradigm, in which multiple clients collaboratively train deep learning models without centralizing their local data, and hence…

cs.LG2021

Towards Data-Free Domain Generalization

Ahmed Frikha, Haokun Chen, Denis Krompaß +2

In this work, we investigate the unexplored intersection of domain generalization (DG) and data-free learning. In particular, we address the question: How can knowledge contained i…

cs.LG2021

Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption

Ahmed Frikha, Denis Krompaß, Volker Tresp

Machine learning models that can generalize to unseen domains are essential when applied in real-world scenarios involving strong domain shifts. We address the challenging domain g…

cs.LG2020★ 8 cited

ARCADe: A Rapid Continual Anomaly Detector

Ahmed Frikha, Denis Krompaß, Volker Tresp

Although continual learning and anomaly detection have separately been well-studied in previous works, their intersection remains rather unexplored. The present work addresses a le…

cs.LG2020

Few-Shot One-Class Classification via Meta-Learning

Ahmed Frikha, Denis Krompaß, Hans-Georg Köpken +1

Although few-shot learning and one-class classification (OCC), i.e., learning a binary classifier with data from only one class, have been separately well studied, their intersecti…