Papers

Publications

J. Lamperski, H. Yang, and O. Prokopyev. Simple randomized rounding for max-min eigenvalue augmentation. ICML 2025.

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.

Under revision

J. Lamperski, L. Wrabetz, and O. Prokopyev. Online facility location with recurring maximum demand. Under revision at Operation Research.

J. Lamperski and H. Eskandari. Learning acyclic self-transitioning discrete-time Markov chains from aggregate absorption data. Under revision at Mathematics of Operations Research.

C. Worrell, J. Lamperski, and L. Maillart. Minimum makespan scheduling with relocation times. Under Revision at IISE Transactions.

Submitted/working

M. Hamilton, J. Lamperski, and K. G. Tari. Unit-Demand Pricing for Min-Buying Customers.

L. Wrabetz, J. Lamperski, and O. Prokopyev. The k-Adaptive l-Most-Vital-Arcs Problem.

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

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

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

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

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.