Seminar Series
March 16, 2021: Fairness in Graph Neural Networks. Presenter: Pelin Arancy.
March 9, 2021: Batch Normalization in Federated Learning. Presenter: Khang Dang.
Feb 23, 2021: Poisoning Attacks and Defenses in Federated Learning. Presenter: Han Hu.
Feb 16, 2021: InstaHide: Instance-hiding Schemes for Private Distributed Learning. Presenter: Khang Dang.
Feb 09, 2021: Extracting Training Data from Large Language Models. Presenter: Phung Lai.
Feb 02, 2021: Federated Graph Neural Networks. Presenter: Khang Tran.
Jan 26, 2021: Federated Learning System in the Wild. Presenter: Han Hu.
Dec 7, 2020: A Novel Audio-Based Machine Learning Model for Automated Detection of Collision Hazards at Construction Sites. Presenter: Khang Dang.
Nov 23, 2020: Thanks Giving Week.
Nov 16, 2020: Presenter: Andrew Denis.
Oct 26, 2020: Prototypical Networks for Few-shot Learning. Jake Snell et al., NeurIPS 2017. Presenter: Khang Tran. [slides]
Oct 19, 2020: Bayesian Differential Privacy for Machine Learning. Triastcyn et al., ICML 2020. Presenter: Phung Lai. [slides]
Oct 12, 2020: Hierarchical Attention Prototypical Networks for Few-Shot Text Classification. Shengli Sun et al., EMNLP 2019. Presenter: Andrew Denis. [slides]
Oct 5, 2020: GNNExplainer: Generating Explanations for Graph Neural Networks. Rex Ying et al., NeuRIPS 2019. Presenter: Pelin Ayranci. [slides]
Sept 28, 2020: Once-for-All: Train One Network and Specialize it for Efficient Deployment. Han Cai et al., ICLR 2020. Presenter: Han Hu. [slides]
Sept 21, 2020: ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. Han Cai et al., ICLR 2019. Presenter: Pradnya Desai. [slides]
Sept 14, 2020: Context-Aware Local Differential Privacy. Jayadev Acharya et al., ICML 2020. Presenter: Khang Tran. [slides]
Sept 07, 2020: Generative Models for Effective ML on Private, Decentralized Datasets. Sean Augenstein et al., ICLR 2020. Presenter: Phung Lai. [slides]