no code implementations • Findings (EMNLP) 2021 • Dingcheng Li, Hongliang Fei, Shaogang Ren, Ping Li
Recently, disentanglement based on a generative adversarial network or a variational autoencoder has significantly advanced the performance of diverse applications in CV and NLP domains.
no code implementations • 4 Feb 2024 • Shaogang Ren, Xiaoning Qian
Best subset selection is considered the `gold standard' for many sparse learning problems.
no code implementations • 3 Feb 2024 • Shaogang Ren, Xiaoning Qian
A new CBO method is developed by leveraging the learned exogenous distribution.
no code implementations • 21 Sep 2023 • Shaogang Ren, Dingcheng Li, Ping Li
To improve word representation learning, we propose a probabilistic prior which can be seamlessly integrated with word embedding models.
1 code implementation • Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM) 2022 • Shaogang Ren, Ping Li
A new causal discovery method is introduced to solve the bivariate causal discovery problem.
no code implementations • 6 Jul 2022 • Shaogang Ren, Belhal Karimi, Dingcheng Li, Ping Li
VFGs learn the representation of high dimensional data via a message-passing scheme by integrating flow-based functions through variational inference.
no code implementations • 5 Jul 2022 • Shaogang Ren, Guanhua Fang, Ping Li
Best subset selection is considered the `gold standard' for many sparse learning problems.
1 code implementation • ICDM 21 2021 • Shaogang Ren, Haiyan Yin, Mingming Sun, Ping Li
Then we formulate a novel evaluation metric to infer the scores for each potential causal direction based on the variance of the conditional density estimation.
1 code implementation • NeurIPS 2020 • Shaogang Ren, Weijie Zhao, Ping Li
L1 regularization has been broadly employed to pursue model sparsity.
1 code implementation • 20 Apr 2020 • Shaogang Ren, Dingcheng Li, Zhixin Zhou, Ping Li
The thriving of deep models and generative models provides approaches to model high dimensional distributions.
no code implementations • 15 Jun 2018 • Shaogang Ren, Jianhua Z. Huang, Shuai Huang, Xiaoning Qian
More critically, SAIF has the safe guarantee as it has the convergence guarantee to the optimal solution to the original full LASSO problem.