Eddie Xu
I am a machine learning researcher. My research interest is in manifold learning, kernel learning, and budgeted learning. Google Scholar
I work at a hedge fund in Chicago.
I am a machine learning researcher. My research interest is in manifold learning, kernel learning, and budgeted learning. Google Scholar
I work at a hedge fund in Chicago.
Minmin Chen, Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Fei Sha. Marginalizing Stacked Linear Denoising Autoencoders. Journal of Machine Learning Research (JMLR), 2016 [PDF]
Zhixiang (Eddie) Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng. Gradient Boosted Feature Selection. Proc. 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining ( KDD ), 2014 [PDF]
Zhixiang (Eddie) Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle. Budgeted Learning with Trees and Cascades. Journal of Machine Learning Research ( JMLR ), 15-2014 [PDF]
Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Yixin Chen, Feature- Cost Sensitive Learning with Submodular Trees of Classifiers, Proc. AAAI Conference on Artificial Intelligence ( AAAI ), 2014 [PDF]
Zhixiang (Eddie) Xu, Supervised Machine Learning Under Test-Time Resource Constraints: A Trade-off Between Accuracy and Cost. Ph.D. Dissertation, Washington University, 2014 [PDF]
Gao. Huang, Shiji Song, Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Cheng Wu. Transductive Minimax Probability Machine. Proc. 7th European Conference on Machine Learning ( ECML ), 2014 [PDF]
Jacob Gardner, Matt J. Kusner, Kilian Q. Weinberger, John P. Cunningham, Zhixiang (Eddie) Xu. Bayesian Optimization with Inequality Constraints. Proc. 31st International Conference on Machine Learning ( ICML ), 2014 [PDF]
Zhixiang (Eddie) Xu, Matt J. Kusner, Gao Huang, Kilian Q. Weinberger. Anytime Representation Learning. Proc. 30th International Conference on Machine Learning ( ICML ), 2013 [PDF]
Zhixiang (Eddie) Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen. Cost-Sensitive Tree of Classifiers. Proc. 30th International Conference on Machine Learning ( ICML ), 2013 [PDF]
Zhixiang (Eddie) Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha. An alternative text representation to TF- IDF and Bag-of-Words. Proc. 21st ACM Conference of Information and Knowledge Management ( CIKM ), 2012 [PDF]
Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Olivier Chapelle. Greedy Miser: Learning Under Test-time Budget. Proc. 29th International Conference on Machine Learning ( ICML ), 2012. [PDF]
Minmin Chen, Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Fei Sha. Marginalized Stacked Denoising Autoencoders for Domain Adaptation. Proc. 29th International Conference on Machine Learning ( ICML ), 2012.[PDF]
Minmin Chen, Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem. Classifier Cascade: Tradeoff between Accuracy and Feature Evaluation Cost. Proc. 15th International Conference on Artificial Intelligence and Statistics ( AISTATS ), 2012. [PDF]
Zhixiang (Eddie) Xu, Jake Gardner, Stephen Tyree, Gao Huang, Kilian Q. Weinberger. Compressed Support Vector Machines. arXiv:1501.06478, Technical Report, 2015 [PDF]
Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Olivier Chapelle, Learning Under Test-time Budget, The Learning Workshop, (Snowbird), Snowbird, 2012. (Oral presentation) [PDF]
Dor. Kedem, Zhixiang (Eddie) Xu, Kilian Q. Weinberger. Gradient Boosted Large Margin Nearest Neighbors. NIPS Workshop on Beyond Mahalanobis Distance, 2011. [PDF]
Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Fei Sha. Rapid Feature Learning with Stacked Linear Denoisers. arXiv:1105:0972 [cs.LG]. ICML Workshop on Unsupervised Learning, 2011. [PDF]
Zhixiang (Eddie) Xu, Kilian Q. Weinberger, Olivier Chapelle. Distance Metric Learning for Kernel Machines. arXiv:1208.3422 [stat.ML]. NIPS Workshops on New Directions in Multiple Kernel Learning, 2010. [PDF]