Cover Image

Submodular Framework for Structured-Sparse Optimal Transport

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Manupriya, Piyushi, Jawanpuria, Pratik, Gurumoorthy, Karthik S., Jagarlapudi, SakethaNath, Mishra, Bamdev
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MMD-Regularized Unbalanced Optimal Transport
by: Manupriya, Piyushi, et al.
Published: (2020)

Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
by: Manupriya, Piyushi, et al.
Published: (2025)

Consistent Optimal Transport with Empirical Conditional Measures
by: Manupriya, Piyushi, et al.
Published: (2023)

UniPROT: Uniform Prototype Selection via Partial Optimal Transport with Submodular Guarantees
by: Chanda, Prateek, et al.
Published: (2026)

A Riemannian Approach to Ground Metric Learning for Optimal Transport
by: Jawanpuria, Pratik, et al.
Published: (2024)

Learning Counterfactually Fair Models via Improved Generation with Neural Causal Models
by: Kher, Krishn Vishwas, et al.
Published: (2025)

Riemannian coordinate descent algorithms on matrix manifolds
by: Han, Andi, et al.
Published: (2024)

Riemannian Optimization for Hadamard Products of Low-Rank Matrices
by: Jawanpuria, Pratik, et al.
Published: (2026)

A Framework for Bilevel Optimization on Riemannian Manifolds
by: Han, Andi, et al.
Published: (2024)

A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks
by: Mishra, Neel, et al.
Published: (2024)

Generalized infinite dimensional Alpha-Procrustes based geometries
by: Goomanee, Salvish, et al.
Published: (2025)

Unsupervised Structural-Counterfactual Generation under Domain Shift
by: Kher, Krishn Vishwas, et al.
Published: (2025)

Riemannian Federated Learning via Averaging Gradient Streams
by: Huang, Zhenwei, et al.
Published: (2024)

On the Generalization and Robustness in Conditional Value-at-Risk
by: Mulumudi, Dinesh Karthik, et al.
Published: (2026)

Federated Learning on Riemannian Manifolds with Differential Privacy
by: Huang, Zhenwei, et al.
Published: (2024)

SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining
by: Han, Andi, et al.
Published: (2024)

LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
by: Zhao, Lanxin, et al.
Published: (2026)

Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds
by: Li, Yibang, et al.
Published: (2026)

Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)

FedSEA: Achieving Benefit of Parallelization in Federated Online Learning
by: Sahu, Harekrushna, et al.
Published: (2026)

Nyström Approximation on Manifolds
by: Nie, Hantao, et al.
Published: (2026)

The Ground Cost for Optimal Transport of Angular Velocity
by: Elamvazhuthi, Karthik, et al.
Published: (2025)

Displacement-Sparse Neural Optimal Transport
by: Chen, Peter, et al.
Published: (2025)

Nearly Minimax Optimal Submodular Maximization with Bandit Feedback
by: Tajdini, Artin, et al.
Published: (2023)

Sparse Partial Optimal Transport via Quadratic Regularization
by: Tran, Khang, et al.
Published: (2025)

Optimal Decision Tree and Adaptive Submodular Ranking with Noisy Outcomes
by: Jia, Su, et al.
Published: (2023)

Discretely Beyond $1/e$: Guided Combinatorial Algorithms for Submodular Maximization
by: Chen, Yixin, et al.
Published: (2024)

Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
by: Bharadwaj, Shreyas, et al.
Published: (2025)

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport
by: Wu, Di, et al.
Published: (2025)

Submodular Reinforcement Learning
by: Prajapat, Manish, et al.
Published: (2023)

Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression
by: Cao, Tue M., et al.
Published: (2026)

Signal from Structure: Exploiting Submodular Upper Bounds in Generative Flow Networks
by: Larouche, Alexandre, et al.
Published: (2026)

Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel
by: Chen, Yixin, et al.
Published: (2021)

Manifold Learning with Sparse Regularised Optimal Transport
by: Zhang, Stephen, et al.
Published: (2023)

Procurement Auctions via Approximately Optimal Submodular Optimization
by: Deng, Yuan, et al.
Published: (2024)

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport
by: Zeng, Siqi, et al.
Published: (2024)

OptiMAG: Structure-Semantic Alignment via Unbalanced Optimal Transport
by: Zuo, Yilong, et al.
Published: (2026)

Structured Matching via Cost-Regularized Unbalanced Optimal Transport
by: Pardini, Emanuele, et al.
Published: (2025)

Optimal Transport for Structure Learning Under Missing Data
by: Vo, Vy, et al.
Published: (2024)

Scalable Submodular Policy Optimization via Pruned Submodularity Graph
by: Anand, Aditi, et al.
Published: (2025)