I am a third year Ph.D. student at the Machine Learning Lab of Columbia University (under the supervision of Prof. Tony Jebara). Previously, I was an undergraduate student at Institute for Interdisciplinary Information Sciences, Tsinghua University (under the supervision of Prof. Jun Zhu). I am interested in Machine Learning and Artificial Intelligence as well as their applications to related fields, like Computer Vision and Natual Language Processing.
|Time (or Expected Time)||Degree Level||Major||Second Major||School|
|2015-2020||Doctoral Degree||Computer Science||Columbia University|
|2011-2015||Bachelor's Degree||Computer Science||Pure and Applied Math||Tsinghua University|
3. Research Intern, instructed by Prof. Tong Zhang, Big Data Lab, Baidu Research, Beijing, China.
For more information about my research experience, please look at my CURRICULUM VITAE.
1. Da Tang and Rajesh Ranganath, Natural Gradients via the Variational Predictive Distribution, Advances in Approximate Bayesian Inference (AABI) Workshop, Advances in Neural Information Processing Systems (NIPS), 2017 (Spotlight) [PDF]
2. Da Tang and Tony Jebara, Initialization and Coordinate Optimization for Multi-way Matching, Artificial Intelligence and Statistics (AISTATS), 2017 [PDF]
3. Da Tang and Tong Zhang, On the Duality Gap Convergence of ADMM Methods, arXiv preprint arXiv:1508.03702, 2015 [PDF]
4. Tianlin Shi, Da Tang, Liwen Xu and Thomas Moscibroda, Correlated Compressive Sensing for Networked Data, Uncertainty in Artificial Intelligence (UAI), 2014 [PDF]