Contents

Highlights

Tutorial Sessions

We delivered tutorials around constrained deep learning and NCVX in SIAM International Conference on Data Mining (SDM 23) to the machine learning and data science communities, as well as other domains including computer vision, machine learning, optimization, and health informatics.

See our tutorial proposals and tutorial slides for more details: SDM23 proposal and SDM23 tutorial slides.

Preprints

Our software announcement paper is available at https://arxiv.org/abs/2210.00973. This paper is accepted by the NeurIPS Workshop on Optimization for Machine Learning (OPT 2022).

Our universal Deep Learning robustness evaluation paper is available at https://arxiv.org/pdf/2303.13401. This paper is under review at International Journal of Computer Vision (IJCV).

The preview version of universal Deep Learning robustness evaluation paper is available at https://arxiv.org/abs/2210.00621. This paper is accepted by the NeurIPS Workshop on Optimization for Machine Learning (OPT 2022).

The preview version of solution pattern analysis paper is available at https://robustart.github.io/long_paper/39.pdf. This paper is accepted by the CVPR Workshop of Adversarial Machine Learning on Computer Vision: Art of Robustness.

Application of PyGRANSO in Different Areas

Adversarial Robustness: MMLS 2023 poster (Trustworthy AI)

Imbalanced Learning: MMLS 2023 poster (Imbalanced Learning)

Neural Topology Optimization: TBA

Optimization and Control: https://arxiv.org/abs/2301.05393

NCVX Methods

See Prof.Ju Sun’s blog for more details: https://sunju.org/research/nonconvex