dr. C.A. Guzmán Paredes (Cristóbal)

Mathematics

# Congestion Control
# Convex Optimization
# Lower Bound
# Multipath Routing
# Seriation
# Stackelberg Game
# Stochastic Optimization

Engineering & Materials Science

# Convex Optimization

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Operations Research (MOR)

Correa, J. , Guzmán, C., Lianeas, T., Nikolova, E., & Schröder, M. (2022). Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. Operations research, 70(1), 472-489. https://doi.org/10.1287/opre.2020.2067

Zhang, S., Yang, J. , Guzmán, C., Kiyavash, N., & He, N. (2021). The complexity of nonconvex-strongly-concave minimax optimization. In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (UAI 2021): UAI (Proceedings of Machine Learning Research; Vol. 161). MLResearchPress. https://proceedings.mlr.press/v161/zhang21c.html

Bassily, R. , Guzmán, C., & Nandi, A. (2021). Non-Euclidean Differentially Private Stochastic Convex Optimization. In 34th Annual Conference on Learning Theory 2021 (pp. 474-499). (Proceedings of Machine Learning Research; Vol. 134). MLResearchPress. http://proceedings.mlr.press/v134/bassily21a.html

Bassily, R. , Guzmán, C., & Menart, M. (2021). Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. In 35th Conference on Neural Information Processing Systems (NeurIPS 2021): NeurIPS (pp. 9317--9329). (Advances in Neural Information Processing Systems; Vol. 34). Curran Associates Inc.. https://proceedings.neurips.cc/paper/2021/hash/4ddb5b8d603f88e9de689f3230234b47-Abstract.html

Guzmán, C., Mehta, N., & Mortazavi, A. (2021). Best-case lower bounds in online learning. In 35th Conference on Neural Information Processing Systems, NeurIPS 2021: NeurIPS (pp. 21923--21934). Curran Associates Inc.. https://proceedings.neurips.cc/paper/2021/hash/b7da6669894867f04b8727876a69ffc0-Abstract.html

Guzmán, C., Riffo, J., Telha, C., & van Vyve, M. (2021). A sequential Stackelberg game for dynamic inspection problems. European journal of operational research, [17623]. https://doi.org/10.1016/j.ejor.2021.12.015

Guzmán, C., Armstrong, S., & Sing-Long, C. (2021). An Optimal Algorithm for Strict Circular Seriation. SIAM Journal on Mathematics of Data Science, 3(4), 1223-1250. https://doi.org/10.1137/21M139356X

Feldman, V. , Guzmán Paredes, C. A., & Vempala, S. (2021). Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Mathematics of operations research, 46(3), 912-945. https://doi.org/10.1287/moor.2020.1111

Bassily, R., Feldman, V. , Guzmán Paredes, C. A., & Talwar, K. (2020). Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. In Advances in Neural Information Processing Systems (NeurIPS) https://papers.nips.cc/paper/2020/file/2e2c4bf7ceaa4712a72dd5ee136dc9a8-Paper.pdf

Diakonikolas, J. , & Guzmán Paredes, C. A. (2019). Lower Bounds for Parallel and Randomized Convex Optimization. In Proceedings of the Thirty-Second Conference on Learning Theory (Proceedings of Machine Learning Research; Vol. 99). http://proceedings.mlr.press/v99/diakonikolas19c.html

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