Cover Image

Adaptive Threshold-Driven Continuous Greedy Method for Scalable Submodular Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rostami, Mohammadreza, Kia, Solmaz S.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Combinatorics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FedMPDD: Communication-Efficient Federated Learning with Privacy Preservation Attributes via Projected Directional Derivative
by: Rostami, Mohammadreza, et al.
Published: (2025)

Scalar Federated Learning for Linear Quadratic Regulator
by: Rostami, Mohammadreza, et al.
Published: (2026)

ResQue Greedy: Rewiring Sequential Greedy for Improved Submodular Maximization
by: Gallart, Joan Vendrell, et al.
Published: (2025)

Time-Varying Convex Optimization with $O(n)$ Computational Complexity
by: Rostami, M., et al.
Published: (2024)

Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
by: Zhou, Julien, et al.
Published: (2024)

FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks
by: Rostami, M., et al.
Published: (2024)

Complement Submodular Information Measures for Balanced and Robust Data Selection
by: Iyer, Rishabh
Published: (2026)

Lower Bounds for Greedy Teaching Set Constructions
by: Compton, Spencer, et al.
Published: (2025)

Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
by: Rostami, M., et al.
Published: (2024)

GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
by: Fahrbach, Matthew, et al.
Published: (2024)

Submodular Maximization Subject to Uniform and Partition Matroids: From Theory to Practical Applications and Distributed Solutions
by: Kia, Solmaz S.
Published: (2025)

Scalable Structure Learning for Sparse Context-Specific Systems
by: Rios, Felix Leopoldo, et al.
Published: (2024)

Lower Bound on the Greedy Approximation Ratio for Adaptive Submodular Cover
by: Harris, Blake, et al.
Published: (2024)

Optimality Gap of Decentralized Submodular Maximization under Probabilistic Communication
by: Vendrell, Joan, et al.
Published: (2024)

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

CSGO: Constrained-Softassign Gradient Optimization For Large Graph Matching
by: Shen, Binrui, et al.
Published: (2022)

Towards a General Framework for Predicting and Explaining the Hardness of Graph-based Combinatorial Optimization Problems using Machine Learning and Association Rule Mining
by: Sharman, Bharat, et al.
Published: (2025)

Curvature Beyond Positivity: Greedy Guarantees for Arbitrary Submodular Functions
by: Chen, Yixin, et al.
Published: (2026)

Efficient Combinatorial Optimization via Heat Diffusion
by: Ma, Hengyuan, et al.
Published: (2024)

Optimal Mixed Integer Linear Optimization Trained Multivariate Classification Trees
by: Alston, Brandon, et al.
Published: (2024)

Performance-Guaranteed Solutions for Multi-Agent Optimal Coverage Problems using Submodularity, Curvature, and Greedy Algorithms
by: Welikala, Shirantha, et al.
Published: (2024)

A Pragmatic Method for Comparing Clusterings with Overlaps and Outliers
by: DeWolfe, Ryan, et al.
Published: (2026)

Generating Hadamard matrices with transformers
by: Williamson, Geordie, et al.
Published: (2026)

Invariant-Based Diagnostics for Graph Benchmarks
by: von Moos, Richard, et al.
Published: (2026)

An Optimal Sauer Lemma Over $k$-ary Alphabets
by: Hanneke, Steve, et al.
Published: (2026)

Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them
by: Hordan, Snir, et al.
Published: (2026)

Neural Algorithmic Reasoning for Approximate $k$-Coloring with Recursive Warm Starts
by: Vanderbush, Knut, et al.
Published: (2026)

Complex non-backtracking matrix for directed graphs
by: Sando, Keishi, et al.
Published: (2025)

Theoretical Insights into Line Graph Transformation on Graph Learning
by: Yang, Fan, et al.
Published: (2024)

A classification model based on a population of hypergraphs
by: Barton, Samuel, et al.
Published: (2024)

Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?
by: Mundinger, Konrad, et al.
Published: (2025)

Reinforcement learning for graph theory, Parallelizing Wagner's approach
by: Bouffard, Alix, et al.
Published: (2025)

Optimal Mistake Bounds for Transductive Online Learning
by: Chase, Zachary, et al.
Published: (2025)

A Multi-Level Framework for Multi-Objective Hypergraph Partitioning: Combining Minimum Spanning Tree and Proximal Gradient
by: Li, Yingying, et al.
Published: (2025)

Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape
by: Karhadkar, Kedar, et al.
Published: (2023)

Heating Up Quasi-Monte Carlo Graph Random Features: A Diffusion Kernel Perspective
by: Feinberg, Brooke, et al.
Published: (2024)

Estimating the stability number of a random graph using convolutional neural networks
by: Davila, Randy
Published: (2024)

GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions
by: Gopal, Shivaram, et al.
Published: (2024)

Greedy Gossiping
by: Williams, Kada
Published: (2025)

The Banach-Butterfly Invariant: Influence-Adaptive Walsh Geometry for Ternary Polynomial Threshold Functions
by: Pavlov, Gorgi
Published: (2026)