165 citations · 612 across the 67 of their papers we have counts for
71 papers
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm
Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez +1
High-quality machine learning models are dependent on access to high-quality training data. When the data are not already available, it is tedious and costly to obtain them. Data m…
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
Ilgee Hong, Sen Na, Michael W. Mahoney +1
We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety of applications in machine learning and engi…
Confidence Sets for Causal Orderings
Y. Samuel Wang, Mladen Kolar, Mathias Drton
Causal discovery procedures aim to deduce causal relationships among variables in a multivariate dataset. While various methods have been proposed for estimating a single causal mo…
Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
Yuchen Fang, Sen Na, Michael W. Mahoney +1
We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems with stochastic objectives and deterministic eq…
Latent Multimodal Functional Graphical Model Estimation
Katherine Tsai, Boxin Zhao, Sanmi Koyejo +1
Joint multimodal functional data acquisition, where functional data from multiple modes are measured simultaneously from the same subject, has emerged as an exciting modern approac…
On the Lasso for Graphical Continuous Lyapunov Models
Philipp Dettling, Mathias Drton, Mladen Kolar
Graphical continuous Lyapunov models offer a new perspective on modeling causally interpretable dependence structure in multivariate data by treating each independent observation a…