E. Cruz Cortés, K. Josey and F. Yang, D. Ghosh,
An Empirical Process Framework for Covariate Balance in Causal Inference, 2023
(arXiv).
Barbe, Carón, Cruz Cortés, et al.,
Working Through Political Organization. Crisis and Critique, vol 9, Issue 2, 2022 (PDF).
E. Cruz Cortés, S. Rajtmajer, D. Ghosh,
Locality of Technical objects and the Role of Structural Interventions for Systemic Change. FAccT, 2022 (PDF).
E. Cruz Cortés, S. Rajtmajer, D. Ghosh,
Structural Interventions on Automated Decision Making Systems. Workshop on Algorithmic Fairness Through the Lens of Causality and Robustness, NeurIPS 2021 (PDF).
(Note: The extended version of this paper is right above this item, under the new name Locality of Technical Objects....)
E. Cruz Cortés, F. Yang, E. Juárez-Colunga, T. Warsavage, D. Ghosh,
Comment on "Statistical Modeling: the Two Cultures" by Leo Breiman,
Special Issue: Commentaries on Breiman's Two Cultures,
Journal of Observational Studies, Vol. 7, Iss. 1, 2021,
(MUSE).
E. Cruz Cortés and D. Ghosh, An Invitation to System-wide Algorithmic Fairness, Artificial Intelligence, Ethics and Society, 2020 (PDF, ACM).
P. Rudra, E. Cruz Cortés, X. Zhang, D. Ghosh,
Multiple testing approaches for hypotheses in integrative genomics,
WIREs Computational Statistics, 2019,
(Wiley)
D. Ghosh and E. Cruz Cortés,
A Gaussian Process Framework for Overlap and Causal Effect Estiamtion with High-Dimensional Covariates,
Journal of Causal Inference, 2019,
(JCI)
E. Cruz Cortés and C. Scott, Consistent Kernel Density Estimation with Non-Vanishing Bandwidth, undergoing expansion, (arxiv).
E. Cruz Cortés, Aronowitz, Deshmukh, Li, Miles, Navarrete and Solórzano
From Chemistry to History via Kernel Embedding, (in preparation).
C. Croft, E. Cruz Cortés, J. Harge, L. Tawil, A Provocation Towards Moving, QED: A Journal of GLBTQ Worldmaking, 2017 (JSTOR).
E. Cruz Cortés and C. Scott, Sparse
Approximation of a Kernel Mean, arXiv:1503.00323,
IEEE Trans. Signal Processing, vol. 65, pp. 1310-1323,2017. (arxiv, ieee)
E. Cruz Cortés and C. Scott,
Scalable Sparse Approximation of a Sample Mean,
Proc. 2014 IEEE Int. Conf. on Acoustic, Speech
and Signal Processing (ICASSP), pp. 5237-5241, 2014. (pdf)