no code implementations • ECNLP (ACL) 2022 • Bo Dong, Yiyi Wang, Hanbo Sun, Yunji Wang, Alireza Hashemi, Zheng Du
In this paper, we propose a contrastive meta-learning framework (CML) to address the challenges introduced by noisy annotated data, specifically in the context of natural language processing.
no code implementations • 8 Oct 2023 • Heinrich Peters, Alireza Hashemi, James Rae
This paper presents a predictive error model trained to detect potential errors in search relevance annotation tasks for three industry-scale ML applications (music streaming, video streaming, and mobile apps) and assesses its potential to enhance the quality and efficiency of the data annotation process.
no code implementations • 26 Jan 2023 • Alireza Hashemi, Hernan Makse
We extend the graph convolutional network method for deep learning on graph data to higher order in terms of neighboring nodes.
1 code implementation • 24 Oct 2020 • Sina Sajjadi, Alireza Hashemi, Fakhteh Ghanbarnejad
For the mobility dynamics, we design an agent based model consisting of pedestrian dynamics with a novel type of force to resemble social distancing in crowded sites.
Physics and Society Populations and Evolution
1 code implementation • 28 Aug 2020 • Majid Ashouri, Alireza Hashemi
We adopted two approaches to this problem: Firstly, we made use of a multi-grid dataset in order to train our artificial neural network in a cost-effective manner.