1 code implementation • 16 Apr 2024 • Jibril Frej, Anna Dai, Syrielle Montariol, Antoine Bosselut, Tanja Käser
In light of the job market's rapid changes and the current state of research in course recommender systems, we outline essential properties for course recommender systems to address these demands effectively, including explainable, sequential, unsupervised, and aligned with the job market and user's goals.
1 code implementation • 5 Feb 2024 • Antoine Magron, Anna Dai, Mike Zhang, Syrielle Montariol, Antoine Bosselut
Recent approaches in skill matching, employing synthetic training data for classification or similarity model training, have shown promising results, reducing the need for time-consuming and expensive annotations.
no code implementations • 28 Mar 2023 • Jingwei Sun, Zhixu Du, Anna Dai, Saleh Baghersalimi, Alireza Amirshahi, David Atienza, Yiran Chen
In this paper, we propose \textbf{Party-wise Dropout} to improve the VFL model's robustness against the unexpected exit of passive parties and a defense method called \textbf{DIMIP} to protect the active party's IP in the deployment phase.
no code implementations • 1 Mar 2019 • Anna Dai, Zhifeng Zhao, Honggang Zhang, Rongpeng Li, Yugeng Zhou
Collective intelligence is manifested when multiple agents coherently work in observation, interaction, decision-making and action.