Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy J Yang, Q Liu, V Rao, J Neville International Conference on Machine Learning (ICML), 5557-5566, 2018 | 69 | 2018 |
An Iterative, Sketching-based Framework for Ridge Regression A Chowdhury, J Yang, P Drineas International Conference on Machine Learning (ICML), 988-997, 2018 | 53 | 2018 |
Decoupling Homophily and Reciprocity with Latent Space Network Models J Yang, V Rao, J Neville Conference on Uncertainty in Artificial Intelligence (UAI), 2017 | 26 | 2017 |
Hats: A hierarchical sequence-attention framework for inductive set-of-sets embeddings C Meng, J Yang, B Ribeiro, J Neville Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 22 | 2019 |
A Stein–Papangelou goodness-of-fit test for point processes J Yang, V Rao, J Neville The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 22 | 2019 |
Randomized iterative algorithms for fisher discriminant analysis A Chowdhury, J Yang, P Drineas arXiv preprint arXiv:1809.03045, 2018 | 10 | 2018 |
Should We Be Confident in Peer Effects Estimated From Partial Crawls of Social Networks J Yang, B Ribeiro, J Neville International AAAI Conference on Web and Social Media (ICWSM), 708-711, 2017 | 10* | 2017 |
Structural conditions for projection-cost preservation via randomized matrix multiplication A Chowdhury, J Yang, P Drineas Linear Algebra and its Applications 573, 144-165, 2019 | 7 | 2019 |
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls J Yang, B Ribeiro, J Neville International Workshop on Statistical Relational AI (StarAI), 2017 | 5 | 2017 |
Partial conditioning for inference of many-normal-means with Hölder constraints J Yang, X Wang, C Liu International Journal of Approximate Reasoning 159, 108946, 2023 | | 2023 |
Statistical Learning and Model Criticism for Networks and Point Processes J Yang Purdue University, 2019 | | 2019 |