Timezone: »
Poster
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic · Slobodan Mitrovic · Jonathan Scarlett · Volkan Cevher
We study the problem of maximizing a monotone submodular function subject to a cardinality constraint $k$, with the added twist that a number of items $\tau$ from the returned set may be removed. We focus on the worst-case setting considered in \cite{orlin2016robust}, in which a constant-factor approximation guarantee was given for $\tau = o(\sqrt{k})$. In this paper, we solve a key open problem raised therein, presenting a new Partitioned Robust (PRo) submodular maximization algorithm that achieves the same guarantee for more general $\tau = o(k)$. Our algorithm constructs partitions consisting of buckets with exponentially increasing sizes, and applies standard submodular optimization subroutines on the buckets in order to construct the robust solution. We numerically demonstrate the performance of PRo in data summarization and influence maximization, demonstrating gains over both the greedy algorithm and the algorithm of \cite{orlin2016robust}.
[
PDF]
[
Summary/Notes]
Summary/Notes]
Author Information
Ilija Bogunovic (EPFL)
Slobodan Mitrovic (EPFL)
Jonathan Scarlett (EPFL)
Volkan Cevher (EPFL)
Related Events (a corresponding poster, oral, or spotlight)
-
2017 Talk: Robust Submodular Maximization: A Non-Uniform Partitioning Approach »
Wed. Aug 9th 04:06 -- 04:24 AM Room Parkside 2
More from the Same Authors
-
2022 : Robustness in deep learning: The width (good), the depth (bad), and the initialization (ugly) »
Zhenyu Zhu · Fanghui Liu · Grigorios Chrysos · Volkan Cevher -
2022 : Sound and Complete Verification of Polynomial Networks »
Elias Abad Rocamora · Mehmet Fatih Sahin · Fanghui Liu · Grigorios Chrysos · Volkan Cevher -
2022 Poster: Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models »
Paul Rolland · Volkan Cevher · Matthäus Kleindessner · Chris Russell · Dominik Janzing · Bernhard Schölkopf · Francesco Locatello -
2022 Poster: UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees »
Kimon Antonakopoulos · Dong Quan Vu · Volkan Cevher · Kfir Levy · Panayotis Mertikopoulos -
2022 Oral: UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees »
Kimon Antonakopoulos · Dong Quan Vu · Volkan Cevher · Kfir Levy · Panayotis Mertikopoulos -
2022 Oral: Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models »
Paul Rolland · Volkan Cevher · Matthäus Kleindessner · Chris Russell · Dominik Janzing · Bernhard Schölkopf · Francesco Locatello -
2022 Poster: A Natural Actor-Critic Framework for Zero-Sum Markov Games »
Ahmet Alacaoglu · Luca Viano · Niao He · Volkan Cevher -
2022 Spotlight: A Natural Actor-Critic Framework for Zero-Sum Markov Games »
Ahmet Alacaoglu · Luca Viano · Niao He · Volkan Cevher -
2021 Poster: The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets »
Ya-Ping Hsieh · Panayotis Mertikopoulos · Volkan Cevher -
2021 Poster: Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach »
Nadav Hallak · Panayotis Mertikopoulos · Volkan Cevher -
2021 Spotlight: Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach »
Nadav Hallak · Panayotis Mertikopoulos · Volkan Cevher -
2021 Oral: The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets »
Ya-Ping Hsieh · Panayotis Mertikopoulos · Volkan Cevher -
2020 Poster: Efficient Proximal Mapping of the 1-path-norm of Shallow Networks »
Fabian Latorre · Paul Rolland · Shaul Nadav Hallak · Volkan Cevher -
2020 Poster: Conditional gradient methods for stochastically constrained convex minimization »
Maria-Luiza Vladarean · Ahmet Alacaoglu · Ya-Ping Hsieh · Volkan Cevher -
2020 Poster: Random extrapolation for primal-dual coordinate descent »
Ahmet Alacaoglu · Olivier Fercoq · Volkan Cevher -
2020 Poster: Double-Loop Unadjusted Langevin Algorithm »
Paul Rolland · Armin Eftekhari · Ali Kavis · Volkan Cevher -
2020 Poster: A new regret analysis for Adam-type algorithms »
Ahmet Alacaoglu · Yura Malitsky · Panayotis Mertikopoulos · Volkan Cevher -
2019 Poster: Almost surely constrained convex optimization »
Olivier Fercoq · Ahmet Alacaoglu · Ion Necoara · Volkan Cevher -
2019 Poster: Finding Mixed Nash Equilibria of Generative Adversarial Networks »
Ya-Ping Hsieh · Chen Liu · Volkan Cevher -
2019 Poster: Efficient learning of smooth probability functions from Bernoulli tests with guarantees »
Paul Rolland · Ali Kavis · Alexander Niklaus Immer · Adish Singla · Volkan Cevher -
2019 Oral: Finding Mixed Nash Equilibria of Generative Adversarial Networks »
Ya-Ping Hsieh · Chen Liu · Volkan Cevher -
2019 Oral: Efficient learning of smooth probability functions from Bernoulli tests with guarantees »
Paul Rolland · Ali Kavis · Alexander Niklaus Immer · Adish Singla · Volkan Cevher -
2019 Oral: Almost surely constrained convex optimization »
Olivier Fercoq · Ahmet Alacaoglu · Ion Necoara · Volkan Cevher -
2019 Poster: On Certifying Non-Uniform Bounds against Adversarial Attacks »
Chen Liu · Ryota Tomioka · Volkan Cevher -
2019 Poster: Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator »
Alp Yurtsever · Suvrit Sra · Volkan Cevher -
2019 Poster: A Conditional-Gradient-Based Augmented Lagrangian Framework »
Alp Yurtsever · Olivier Fercoq · Volkan Cevher -
2019 Oral: Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator »
Alp Yurtsever · Suvrit Sra · Volkan Cevher -
2019 Oral: A Conditional-Gradient-Based Augmented Lagrangian Framework »
Alp Yurtsever · Olivier Fercoq · Volkan Cevher -
2019 Oral: On Certifying Non-Uniform Bounds against Adversarial Attacks »
Chen Liu · Ryota Tomioka · Volkan Cevher -
2018 Poster: A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming »
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher -
2018 Oral: A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming »
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher -
2018 Poster: Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games »
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher -
2018 Poster: Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods »
Junhong Lin · Volkan Cevher -
2018 Oral: Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games »
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher -
2018 Oral: Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods »
Junhong Lin · Volkan Cevher -
2018 Poster: Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams »
Ashkan Norouzi-Fard · Jakub Tarnawski · Slobodan Mitrovic · Amir Zandieh · Aidasadat Mousavifar · Ola Svensson -
2018 Poster: Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces »
Junhong Lin · Volkan Cevher -
2018 Oral: Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams »
Ashkan Norouzi-Fard · Jakub Tarnawski · Slobodan Mitrovic · Amir Zandieh · Aidasadat Mousavifar · Ola Svensson -
2018 Oral: Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces »
Junhong Lin · Volkan Cevher