Papers

Preprints

J. Lamperski, L. Wrabetz, and O. Prokopyev. Online facility location with recurring maximum demand. 2024.

J. Lamperski, H. Yang, and O. Prokopyev. Simple randomized rounding for max-min eigenvalue augmentation. 2024.

C. Worrell,  J. Lamperski, and L. Maillart. Designing meet-in-the-middle service systems. 2024.

C. Worrell, J. Lamperski, and L. Maillart. Minimum makespan scheduling with relocation times. 2024.

J. Lamperski and H. Eskandari. Learning acyclic self-transitioning discrete-time Markov chains from aggregate absorption data. 2023.

C. Worrell and J. Lamperski. Recovering locally distinguishable communities with applications to clustering training data. 2023.

H. Eskandari, J. Lamperski, M. Roberts, M. Krauland, P. Kumar, N. Nataraj, and M. Rikard. Calibrating covariate-dependent discrete-time Markov chain models of disease progression to prevalence target data. 2023.   

Y. Gao, B. Gärtner, and J. Lamperski. A new combinatorial property of geometric unique sink orientations. 2020.

J. Lamperski. Removing an edge from a moderately balanced graph. 2020.

Publications

J. Lamperski, O.A. Prokopyev, and L. Wrabetz. Min-max-min optimization with smooth and strongly convex objectives. SIAM Journal on Optimization, Vol. 33, No. 3: 2435-2456, 2023. 

J. Lamperski, R.M. Freund, and M.J. Todd. An oblivious ellipsoid algorithm for solving a system of (in)feasible linear inequalities. Mathematics of Operations Research, Articles in Advance, 2023.

D. Bertsimas, J. Lamperski, and J. Pauphilet. Certifiably optimal sparse inverse covariance estimation. Mathematical Programming A, Vol. 184: 491-530, 2020.

J. Lamperski and A.J. Schaefer. A polyhedral characterization of the inverse feasible region of a mixed-integer program. Operations Research Letters, Vol. 43, No. 6: 575-578, 2015.