H. Eskandari and J. Lamperski. Computing the transition probabilities of a discrete-time Markov chain from its marginal absorption probabilities. 2022.

J. Lamperski, O.A. Prokopyev, and L. Wrabetz. Min-max-min optimization with smooth and strongly convex objectives. 2022.

H. Eskandari and J. Lamperski. Approximate FedSplit for smooth and strongly convex federated optimization. 2021.

C. Worrell, J. Lamperski, and L.M. Maillart. Minimizing makespan across preloaded machines. 2021.

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

J. Lamperski. Unique sink orientations for homogeneous linear inequalities and their alternative systems. 2019.

J. Lamperski. Removing an edge from a moderately balanced graph. 2019.


J. Lamperski, R.M. Freund, and M.J. Todd. An oblivious ellipsoid algorithm for solving a system of (in)feasible linear inequalities. Accepted to Mathematics of Operations Research, 2020.

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.