12 citations · 14 across the 4 of their papers we have counts for
4 papers
Gradient Regularized Budgeted Boosting
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger +1
As machine learning transitions increasingly towards real world applications controlling the test-time cost of algorithms becomes more and more crucial. Recent work, such as the Gr…
Gradient Boosted Feature Selection
Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger +1
A feature selection algorithm should ideally satisfy four conditions: reliably extract relevant features; be able to identify non-linear feature interactions; scale linearly with t…
Efficient Test Selection in Active Diagnosis via Entropy Approximation
Alice X. Zheng, Irina Rish, Alina Beygelzimer
We consider the problem of diagnosing faults in a system represented by a Bayesian network, where diagnosis corresponds to recovering the most likely state of unobserved nodes give…
A survey of statistical network models
Anna Goldenberg, Alice X Zheng, Stephen E Fienberg +1
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major…