2019 Publications

  • P. L. Combettes, A. M. McDonald, C. A. Micchelli, and M. Pontil, “Learning with optimal interpolation norms,” Numerical Algorithms, vol. 81, no. 2, pp. 695-717, June 2019.
  • P. L. Combettes and L. E. Glaudin, “Proximal activation of smooth functions in splitting algorithms for convex image recovery,” SIAM Journal on Imaging Sciences, vol. 12, no. 4, pp. 1905-1935, November 2019.
  • P. L. Combettes and J.-C. Pesquet, “Stochastic quasi-Fejér block-coordinate fixed point iterations with random sweeping II: Mean-square and linear convergence,” Mathematical Programming, vol. B174, no. 1, pp. 433-451, April 2019.
  • P. L. Combettes and L. E. Glaudin, “Fully proximal splitting algorithms in image recovery,” Proceedings of the European Signal Processing Conference, pp. 525-529. A Coruña, Spain, September 2-6, 2019.
  • Marco Mazzola and Khai T. Nguyen, Lyapunov’s theorem via Baire category, Trends in control theory and partial differential equations, 181–194, Springer INdAM Series, 32, Springer, Cham, 2019.
  • Fabio Ancona, Olivier Glass, and Khai T. Nguyen, On Kolmogorov entropy compactness estimates for scalar conservation laws without uniform convexity, SIAM Journal on Mathematical Analysis , 51 (2019), no. 4, 3020–3051.
  • Alberto Bressan, Marco Mazzola, and Khai T. Nguyen, Approximation of sweeping processes and controllability for a set valued evolution , SIAM J. Control Optim 57 (2019), no. 4, 2487–2514.
  • Leoni, Giovanni and Murray, Ryan Local minimizers and slow motion for the mass preserving Allen–Cahn equation in higher dimensions. Proc. Amer. Math. Soc.147 (2019), no. 12, 5167–5182.
  • Schaeffer, D. G.; Barker, T.; Tsuji, D.; Gremaud, P.; Shearer, M.; Gray, J. M. N. T. Constitutive relations for compressible granular flow in the inertial regime. J. Fluid Mech. 874 (2019), 926–951.
  • Congy, T.; El, G. A.; Hoefer, M. A.; Shearer, M. Nonlinear Schrödinger equations and the universal description of dispersive shock wave structure. Stud. Appl. Math.142 (2019), no. 3, 241–268.     
  • Bociu, L., Guidoboni, G., Sacco, R., & Verri, M. (2019). On the role of compressibility in poroviscoelastic models. Mathematical Biosciences and Engineering, 16(5).
  • Banks, H. T., Bekele-Maxwell, K., Bociu, L., Noorman, M., & Guidoboni, G. (2019). Local sensitivity via the complex-step derivative approximation for 1-D poro-elastic and poro-visco-elastic models. Mathematical Control & Related Fields, 9(4), 623.
  • Bociu, L., & Noorman, M. (2019). Poro-Visco-Elastic Models in Biomechanics: Sensitivity Analysis. Communications in Applied Analysis, 23(1), 61-77.
  • Lee, C. H., Kang, M., & Eun, D. Y. (2019). Non-Markovian Monte Carlo on Directed Graphs. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 3(1), 1-31.
  • Heikkola, E., Ito, K., & Toivanen, J. (2019). A parallel domain decomposition method for the Helmholtz equation in layered media. SIAM Journal on Scientific Computing, 41(5), C505-C521.
  • Chen, S. Y., Bardall, A., Shearer, M., & Daniels, K. E. (2019). Distinguishing deformation mechanisms in elastocapillary experiments. Soft matter, 15(46), 9426-9436.