1. Balakrishnan, S., Kolar, M., Rinaldo, A., Singh, A., Wasserman, L. (2011). Statistical and computational tradeoffs in biclustering. In: NIPS 2011 workshop on computational trade-offs in statistical learning.
2. Ben-Dor, A., Chor, B., Karp, R., Yakhini, Z. (2002). Discovering local structure in gene expression data: The order-preserving submatrix problem. In: Proceedings of the Sixth Annual International Conference on Computational Biology (pp 49–57).
3. Bickel, P. J., Sarkar, P. (2016). Hypothesis testing for automated community detection in networks. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 78(1), 253–273.
4. Bloemendal, A., Knowles, A., Yau, H. T., Yin, J. (2016). On the principal components of sample covariance matrices. Probability Theory and Related Fields, 164, 459–552.
5. Brennan, M., Bresler, G., Huleihel, W. (2018). Reducibility and computational lower bounds for problems with planted sparse structure. In: Proceedings of the 31st Conference On Learning Theory (vol 75, pp. 48–166). Proceedings of Machine Learning Research.