Publisher
Springer International Publishing
Reference24 articles.
1. Bach, F.: Learning with submodular functions: a convex optimization perspective. Found. Trends Mach. Learn. 6(2–3), 145–373 (2013)
2. Chakrabarty, D., Jain, P., Kothari, P.: Provable submodular minimization using Wolfe’s algorithm. In: Advances in Neural Information Processing Systems, vol. 27 (2014)
3. Dadush, D., Huiberts, S., Natura, B., Végh, L.A.: A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. In: Proceedings of the 52nd Annual ACM Symposium on Theory of Computing (STOC), pp. 761–774 (2020)
4. Dadush, D., Natura, B., Végh, L.A.: Revisiting Tardos’s framework for linear programming: faster exact solutions using approximate solvers. In: Proceedings of the 61st Annual IEEE Symposium on Foundations of Computer Science (FOCS), pp. 931–942 (2020)
5. De Loera, J.A., Haddock, J., Rademacher, L.: The minimum Euclidean-norm point in a convex polytope: Wolfe’s combinatorial algorithm is exponential. SIAM J. Comput. 49(1), 138–169 (2020)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献