Publications

Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning

Ziyang Song

Qincheng Lu

Mike He Zhu

David Buckeridge

Yue Li

2024-01-01

MLHC (publié)

proceedings.mlr.press

Bio-Mechanical Poet: An Immersive Audiovisual Playground for Brain Signals and Generative AI.

Philipp Thölke

Antoine Bellemare‐Pepin

Yann Harel

François Lespinasse

Karim Jerbi

2024-01-01

ICCC (publié)

dblp.uni-trier.de

Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers.

Xiuying Wei

Skander Moalla

Razvan Pascanu

Caglar Gulcehre

2024-01-01

Neural Information Processing Systems (publié)

dblp.uni-trier.de

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.

Eslam G. Al-Sakkari

Ahmed Ragab

Daria Camilla Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.

Eslam G. Al-Sakkari

Ahmed Ragab

Daria Camilla Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities

Eslam G. Al-Sakkari

Ahmed Ragab

Daria C. Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.

Eslam G. Al-Sakkari

Ahmed Ragab

Daria Camilla Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.

Eslam G. Al-Sakkari

Ahmed Ragab

Daria Camilla Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.

Eslam G. Al-Sakkari

Ahmed Ragab

Daria Camilla Boffito

Mouloud Amazouz

2024-01-01

Science of the Total Environment (publié)

CATRO: Channel Pruning via Class-Aware Trace Ratio Optimization

Wenzheng Hu

Ning Liu

Zhengping Che

Mingyang Li

Jian Tang

Changshui Zhang

Jianqiang Wang

Deep convolutional neural networks are shown to be overkill with high parametric and computational redundancy in many application scenarios,… (voir plus) and an increasing number of works have explored model pruning to obtain lightweight and efficient networks. However, most existing pruning approaches are driven by empirical heuristics and rarely consider the joint impact of channels, leading to unguaranteed and suboptimal performance. In this article, we propose a novel channel pruning method via class-aware trace ratio optimization (CATRO) to reduce the computational burden and accelerate the model inference. Utilizing class information from a few samples, CATRO measures the joint impact of multiple channels by feature space discriminations and consolidates the layerwise impact of preserved channels. By formulating channel pruning as a submodular set function maximization problem, CATRO solves it efficiently via a two-stage greedy iterative optimization procedure. More importantly, we present theoretical justifications on convergence of CATRO and performance of pruned networks. Experimental results demonstrate that CATRO achieves higher accuracy with similar computation cost or lower computation cost with similar accuracy than other state-of-the-art channel pruning algorithms. In addition, because of its class-aware property, CATRO is suitable to prune efficient networks adaptively for various classification subtasks, enhancing handy deployment and usage of deep networks in real-world applications.

2024-01-01

IEEE Trans. Neural Networks Learn. Syst. (publié)

Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces

Ahmad-reza Ehyaei

Kiarash Mohammadi

Amir-Hossein Karimi

S. Samadi

Golnoosh Farnadi

2024-01-01

AAAI (publié)