Timezone: »
Poster
Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator
Alp Yurtsever · Suvrit Sra · Volkan Cevher
We propose a class of variance-reduced stochastic conditional gradient methods. By adopting the recent stochastic path-integrated differential estimator technique (SPIDER) of Fang et. al. (2018) for the classical Frank-Wolfe (FW) method, we introduce SPIDER-FW for finite-sum minimization as well as the more general expectation minimization problems. SPIDER-FW enjoys superior complexity guarantees in the non-convex setting, while matching the best known FW variants in the convex case. We also extend our framework a la conditional gradient sliding (CGS) of Lan & Zhou. (2016), and propose SPIDER-CGS.
Author Information
Alp Yurtsever (EPFL)
Suvrit Sra (MIT)
Volkan Cevher (EPFL)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Oral: Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator »
Tue. Jun 11th 11:35 -- 11:40 PM Room Grand Ballroom
More from the Same Authors
-
2022 Poster: Rethinking Convergence in Deep Learning: Beyond Stationary Points »
Jingzhao Zhang · Haochuan Li · Suvrit Sra · Ali Jadbabaie -
2022 Spotlight: Rethinking Convergence in Deep Learning: Beyond Stationary Points »
Jingzhao Zhang · Haochuan Li · Suvrit Sra · Ali Jadbabaie -
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 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: Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity »
Jingzhao Zhang · Hongzhou Lin · Subhro Das · Suvrit Sra · Ali Jadbabaie -
2022 Spotlight: Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity »
Jingzhao Zhang · Hongzhou Lin · Subhro Das · Suvrit Sra · Ali Jadbabaie -
2022 Poster: Understanding the unstable convergence of gradient descent »
Kwangjun Ahn · Jingzhao Zhang · Suvrit Sra -
2022 Spotlight: Understanding the unstable convergence of gradient descent »
Kwangjun Ahn · Jingzhao Zhang · Suvrit Sra -
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 -
2022 Poster: Scaling up Universal Methods for Convex Optimization »
Kimon Antonakopoulos · Dong Quan Vu · Volkan Cevher · Kfir Levy · Panayotis Mertikopoulos -
2022 Oral: Scaling up Universal Methods for Convex Optimization »
Kimon Antonakopoulos · Dong Quan Vu · Volkan Cevher · Kfir Levy · Panayotis Mertikopoulos -
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 -
2021 Poster: Provably Efficient Algorithms for Multi-Objective Competitive RL »
Tiancheng Yu · Yi Tian · Jingzhao Zhang · Suvrit Sra -
2021 Poster: Online Learning in Unknown Markov Games »
Yi Tian · Yuanhao Wang · Tiancheng Yu · Suvrit Sra -
2021 Spotlight: Online Learning in Unknown Markov Games »
Yi Tian · Yuanhao Wang · Tiancheng Yu · Suvrit Sra -
2021 Oral: Provably Efficient Algorithms for Multi-Objective Competitive RL »
Tiancheng Yu · Yi Tian · Jingzhao Zhang · Suvrit Sra -
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 -
2021 Poster: Three Operator Splitting with a Nonconvex Loss Function »
Alp Yurtsever · Varun Mangalick · Suvrit Sra -
2021 Spotlight: Three Operator Splitting with a Nonconvex Loss Function »
Alp Yurtsever · Varun Mangalick · Suvrit Sra -
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 -
2020 Poster: Strength from Weakness: Fast Learning Using Weak Supervision »
Joshua Robinson · Stefanie Jegelka · Suvrit Sra -
2020 Poster: Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions »
Jingzhao Zhang · Hongzhou Lin · Stefanie Jegelka · Suvrit Sra · Ali Jadbabaie -
2020 Poster: Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition »
Chi Jin · Tiancheng Jin · Haipeng Luo · Suvrit Sra · Tiancheng Yu -
2019 Poster: Escaping Saddle Points with Adaptive Gradient Methods »
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra -
2019 Oral: Escaping Saddle Points with Adaptive Gradient Methods »
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra -
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: Random Shuffling Beats SGD after Finite Epochs »
Jeff HaoChen · Suvrit Sra -
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: Random Shuffling Beats SGD after Finite Epochs »
Jeff HaoChen · Suvrit Sra -
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: A Conditional-Gradient-Based Augmented Lagrangian Framework »
Alp Yurtsever · Olivier Fercoq · 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: Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces »
Junhong Lin · Volkan Cevher -
2018 Oral: Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces »
Junhong Lin · Volkan Cevher -
2017 Poster: Robust Submodular Maximization: A Non-Uniform Partitioning Approach »
Ilija Bogunovic · Slobodan Mitrovic · Jonathan Scarlett · Volkan Cevher -
2017 Talk: Robust Submodular Maximization: A Non-Uniform Partitioning Approach »
Ilija Bogunovic · Slobodan Mitrovic · Jonathan Scarlett · Volkan Cevher