137 citations · 650 across the 48 of their papers we have counts for
16 papers · 1 filter
Online and Bandit Algorithms Beyond Norms
Thomas Kesselheim, Marco Molinaro, Sahil Singla
Vector norms play a fundamental role in computer science and optimization, so there is an ongoing effort to generalize existing algorithms to settings beyond and $\el…
Online Demand Scheduling with Failovers
Konstantina Mellou, Marco Molinaro, Rudy Zhou
Motivated by cloud computing applications, we study the problem of how to optimally deploy new hardware subject to both power and robustness constraints. To model the situation obs…
Robust Secretary and Prophet Algorithms for Packing Integer Programs
C. J. Argue, Anupam Gupta, Marco Molinaro +1
We study the problem of solving Packing Integer Programs (PIPs) in the online setting, where columns in of the constraint matrix are revealed sequentially, and the goal i…
Lipschitz Selectors may not Yield Competitive Algorithms for Convex Body Chasing
C. J. Argue, Anupam Gupta, Marco Molinaro
The current best algorithms for convex body chasing problem in online algorithms use the notion of the Steiner point of a convex set. In particular, the algorithm which always move…
Robust Algorithms for Online Convex Problems via Primal-Dual
Marco Molinaro
Primal-dual methods in online optimization give several of the state-of-the art results in both of the most common models: adversarial and stochastic/random order. Here we try to p…
Knapsack Secretary with Bursty Adversary
Thomas Kesselheim, Marco Molinaro
The random-order or secretary model is one of the most popular beyond-worst case model for online algorithms. While it avoids the pessimism of the traditional adversarial model, in…