Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency | Paper Citation Record

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This paper cites write newline.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency write newline

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This paper cites Finding approximate local minima faster than gradient descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Finding approximate local minima faster than gradient descent

Reference 2

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This paper cites New local search approximation techniques for maximum generalized satisfiability problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency New local search approximation techniques for maximum generalized satisfiability problems

Reference 3

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This paper cites Decentralized active information acquisition: Theory and application to multi-robot slam.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized active information acquisition: Theory and application to multi-robot slam

Reference 4

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This paper cites Diverse client selection for federated learning via submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Diverse client selection for federated learning via submodular maximization

Reference 5

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This paper cites Joint and separate convexity of the bregman distance.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Joint and separate convexity of the bregman distance

Reference 6

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This paper cites Guarantees for greedy maximization of non-submodular functions with applications.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Guarantees for greedy maximization of non-submodular functions with applications

Reference 7

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This paper cites Guaranteed non-convex optimization: Submodular maximization over continuous domains.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Guaranteed non-convex optimization: Submodular maximization over continuous domains

Reference 8

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This paper cites Continuous Submodular Function Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Continuous Submodular Function Maximization

Reference 9

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This paper cites An o (n) algorithm for quadratic knapsack problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An o (n) algorithm for quadratic knapsack problems

Reference 10

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This paper cites Maximizing a monotone submodular function subject to a matroid constraint.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Maximizing a monotone submodular function subject to a matroid constraint

Reference 11

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This paper cites Submodular function maximization via the multilinear relaxation and contention resolution schemes.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodular function maximization via the multilinear relaxation and contention resolution schemes

Reference 12

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This paper cites Convergence analysis of a proximal-like minimization algorithm using bregman functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Convergence analysis of a proximal-like minimization algorithm using bregman functions

Reference 13

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This paper cites Online continuous submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online continuous submodular maximization

Reference 14

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Observation 91f28cb1-a94e-41e7-811f-f617e784076e · outbound

This paper cites Submodular set functions, matroids and the greedy algorithm: tight worst-case bounds and some generalizations of the rado-edmonds theorem.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodular set functions, matroids and the greedy algorithm: tight worst-case bounds and some generalizations of the rado-edmonds theorem

Reference 15

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Observation b54dc5ee-2cbd-4aaf-b4f4-4453d021a780 · outbound

This paper cites Scalable distributed planning for multi-robot, multi-target tracking.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Scalable distributed planning for multi-robot, multi-target tracking

Reference 16

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Observation 405bef8a-8cb0-4609-8ec1-f99f9494fce8 · outbound

This paper cites Approximate submodularity and its applications: Subset selection, sparse approximation and dictionary selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Approximate submodularity and its applications: Subset selection, sparse approximation and dictionary selection

Reference 17

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Observation 9d7a75bf-aacc-4082-97a4-10ce12be01d8 · outbound

This paper cites Jacobi-style iteration for distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Jacobi-style iteration for distributed submodular maximization

Reference 18

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This paper cites Turning down the noise in the blogosphere.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Turning down the noise in the blogosphere

Reference 19

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This paper cites Combatting dimensional collapse in llm pre-training data via diversified file selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Combatting dimensional collapse in llm pre-training data via diversified file selection

Reference 20

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Observation 3ac6586e-240b-4d57-be7b-afc2ffa7e280 · outbound

This paper cites Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator

Reference 21

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This paper cites The power of local search: Maximum coverage over a matroid.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The power of local search: Maximum coverage over a matroid

Reference 22

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Observation b739f55c-1de4-4fe2-ba30-57a22f3d249c · outbound

This paper cites Monotone submodular maximization over a matroid via non-oblivious local search.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Monotone submodular maximization over a matroid via non-oblivious local search

Reference 23

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This paper cites An analysis of approximations for maximizing submodular set functions—ii.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An analysis of approximations for maximizing submodular set functions—ii

Reference 24

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This paper cites On the convergence of distributed stochastic bilevel optimization algorithms over a network.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On the convergence of distributed stochastic bilevel optimization algorithms over a network

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.716494Z

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This paper cites Distributed submodular maximization with limited information.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed submodular maximization with limited information

Reference 26

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This paper cites Cvx: Matlab software for disciplined convex programming, version 2.1, 2014.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Cvx: Matlab software for disciplined convex programming, version 2.1, 2014

Reference 27

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This paper cites The impact of information in distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The impact of information in distributed submodular maximization

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.688144Z

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This paper cites Gradient methods for submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Gradient methods for submodular maximization

Reference 29

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Observation 80e102ef-1adf-4214-b993-dfaad01ef345 · outbound

This paper cites Introduction to online convex optimization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Introduction to online convex optimization

Reference 30

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This paper cites Matrix analysis.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Matrix analysis

Reference 31

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This paper cites Online optimization: Competing with dynamic comparators.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online optimization: Competing with dynamic comparators

Reference 32

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Observation 61a76936-4fd3-465b-bbee-b604093b4c65 · outbound

This paper cites Metaxas, and Marco Pavone.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Metaxas, and Marco Pavone

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.648337Z

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Observation 72cfd201-d0a8-4e82-843b-a0bd0dcbd67a · outbound

This paper cites Visual prompting upgrades neural network sparsification: A data-model perspective.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Visual prompting upgrades neural network sparsification: A data-model perspective

Reference 34

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Observation fd4e926d-5de4-415c-afbc-953b5cd03ac8 · outbound

This paper cites APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

Reference 35

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This paper cites How to escape saddle points efficiently.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency How to escape saddle points efficiently

Reference 36

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This paper cites Playing games with approximation algorithms.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Playing games with approximation algorithms

Reference 37

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Observation d3416e02-59b7-449a-826b-fa8c5ef6af12 · outbound

This paper cites Maximizing the spread of influence through a social network.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Maximizing the spread of influence through a social network

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.614990Z

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Observation 3c7fb20d-a036-43e9-b4a2-e5c4ad4d21ee · outbound

This paper cites On syntactic versus computational views of approximability.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On syntactic versus computational views of approximability

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.605625Z

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This paper cites Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies

Reference 40

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Observation de3ecbf3-94d9-4672-bb94-101055ab04ab · outbound

This paper cites An end-to-end submodular framework for data-efficient in-context learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An end-to-end submodular framework for data-efficient in-context learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.587636Z

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Observation efec36ff-7a33-4551-bf1d-c5088b04b380 · outbound

This paper cites Convergence Rate of Frank-Wolfe for Non-Convex Objectives.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Convergence Rate of Frank-Wolfe for Non-Convex Objectives

Reference 42

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Observation c75a0072-e53f-4d07-b8c4-961235d0a931 · outbound

This paper cites Functional analysis.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Functional analysis

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.578488Z

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Observation 2970570c-bba9-41c5-a2dd-38d6cc47f3e7 · outbound

This paper cites Submodularity of optimal sensor placement for traffic networks.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity of optimal sensor placement for traffic networks

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.569450Z

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Observation 9b9be261-c349-4d23-ae51-167feb4682ff · outbound

This paper cites Improved Projection-free Online Continuous Submodular Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Improved Projection-free Online Continuous Submodular Maximization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T20:42:38.909277Z

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Observation 0d41207c-081f-425f-8896-a3e663e321c4 · outbound

This paper cites Multi-document summarization via budgeted maximization of submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Multi-document summarization via budgeted maximization of submodular functions

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.559929Z

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Observation 93ba6f4e-e2d8-41d4-a822-73b4400c9a83 · outbound

This paper cites A class of submodular functions for document summarization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A class of submodular functions for document summarization

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.550593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 952b41f3-5ab8-4877-b798-e97763032a19 · outbound

This paper cites Distributed resilient submodular action selection in adversarial environments.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed resilient submodular action selection in adversarial environments

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.541253Z

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Observation 6cd4e9ab-2e39-4f25-a598-f2fcc2dfd15d · outbound

This paper cites The role of information in distributed resource allocation.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The role of information in distributed resource allocation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.531412Z

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Observation 3b81af62-9da5-434c-8fa4-c32aa2ac8b55 · outbound

This paper cites Fast constrained submodular maximization: Personalized data summarization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Fast constrained submodular maximization: Personalized data summarization

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.521755Z

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Observation c244cf97-5c5b-4a08-9e10-3d509888f9e9 · outbound

This paper cites Distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed submodular maximization

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.511527Z

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Observation 343b0202-8e02-4a9c-b6b4-d5a016f6d8c0 · outbound

This paper cites Decentralized submodular maximization: Bridging discrete and continuous settings.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized submodular maximization: Bridging discrete and continuous settings

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.501741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 47eea9fb-c388-49e0-b219-e91059290cf8 · outbound

This paper cites Distributed optimization over time-varying directed graphs.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed optimization over time-varying directed graphs

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.492345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d7999030-76ac-4330-b15e-281130eff157 · outbound

This paper cites Distributed subgradient methods for multi-agent optimization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed subgradient methods for multi-agent optimization

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.482660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 08e6250b-cb19-45e3-bbdb-67633e58965d · outbound

This paper cites Achieving geometric convergence for distributed optimization over time-varying graphs.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Achieving geometric convergence for distributed optimization over time-varying graphs

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.473087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0ed2c420-13c1-489a-98bc-4e02c6e74ded · outbound

This paper cites An analysis of approximations for maximizing submodular set functions—i.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An analysis of approximations for maximizing submodular set functions—i

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T20:42:38.943939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 769073b7-c2bd-4f74-a363-16d796cb66ca · outbound

This paper cites Nemirovsky and D.B.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Nemirovsky and D.B

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.457633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 01b9bc97-406c-43c3-8629-1f640822e928 · outbound

This paper cites Introductory Lectures on Convex Optimization: A Basic Course, volume 87.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Introductory Lectures on Convex Optimization: A Basic Course, volume 87

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.448556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5464934d-13b4-49e5-925c-4ae3d0db540d · outbound

This paper cites An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.439316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5e0745ab-0a36-40d9-889d-38670f9dc41e · outbound

This paper cites A unified approach for maximizing continuous dr-submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A unified approach for maximizing continuous dr-submodular functions

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.429666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ef4d7b7b-b4e3-4574-81c7-79e37babf088 · outbound

This paper cites Nadew, Christopher John Quinn, and Vaneet Aggarwal.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Nadew, Christopher John Quinn, and Vaneet Aggarwal

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.420401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3de148ae-2b4a-480f-a274-d1c9b4d3b639 · outbound

This paper cites Near-optimal multi-agent learning for safe coverage control.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Near-optimal multi-agent learning for safe coverage control

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.409205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a534abec-dede-4844-83af-69c53fa12daa · outbound

This paper cites Distributed stochastic gradient tracking methods.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed stochastic gradient tracking methods

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.400284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a02ab6c3-7de3-4071-9fcb-61c0f912bc87 · outbound

This paper cites Distributed greedy algorithm for multi-agent task assignment problem with submodular utility functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed greedy algorithm for multi-agent task assignment problem with submodular utility functions

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.391111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 744237cc-eb0c-446e-af8d-0231fce5c808 · outbound

This paper cites Decomposable submodular maximization in federated setting.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decomposable submodular maximization in federated setting

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.381884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 96d1b86f-e970-4f08-8734-16ac7be9466c · outbound

This paper cites Distributed strategy selection: A submodular set function maximization approach.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed strategy selection: A submodular set function maximization approach

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.372780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 037ef1dd-3247-4adc-9273-b4a1bb7450f4 · outbound

This paper cites Optimal algorithms for submodular maximization with distributed constraints.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Optimal algorithms for submodular maximization with distributed constraints

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.363198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 12eeba83-c695-430d-ba04-21c61a704207 · outbound

This paper cites Resilient active information acquisition with teams of robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Resilient active information acquisition with teams of robots

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.353200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9c4b6291-764c-4c0b-bf88-1327da1685c0 · outbound

This paper cites Distributed online optimization in dynamic environments using mirror descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed online optimization in dynamic environments using mirror descent

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.344256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d5cb0708-3c15-453a-b90b-4e5e75b58e1e · outbound

This paper cites Efficient informative sensing using multiple robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Efficient informative sensing using multiple robots

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.334819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5f03b3d5-56fc-4b84-b731-17b1d26ca220 · outbound

This paper cites An online algorithm for maximizing submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An online algorithm for maximizing submodular functions

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.325996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a081e94d-f102-41dc-8f1b-8d194b61d124 · outbound

This paper cites Submodularity and curvature: The optimal algorithm (combinatorial optimization and discrete algorithms).

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity and curvature: The optimal algorithm (combinatorial optimization and discrete algorithms)

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.317063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5634f4bb-1c57-42ec-9068-fef4651d1f9c · outbound

This paper cites Symmetry and approximability of submodular maximization problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Symmetry and approximability of submodular maximization problems

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.304685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ccd2855a-fbf5-43a1-9b50-44aa8ddab693 · outbound

This paper cites Bandit multi-linear dr-submodular maximization and its applications on adversarial submodular bandits.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Bandit multi-linear dr-submodular maximization and its applications on adversarial submodular bandits

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.295573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a3ce273-cfc4-4d2b-9489-5b5910891bdd · outbound

This paper cites An empirical study of user engagement in influencer marketing on weibo and wechat.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An empirical study of user engagement in influencer marketing on weibo and wechat

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.286537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72138928-c1ba-423c-8a50-7ae9403c82ce · outbound

This paper cites Using document summarization techniques for speech data subset selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Using document summarization techniques for speech data subset selection

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.277421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b078945-549a-43ed-93f0-818653e920aa · outbound

This paper cites Submodularity in data subset selection and active learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity in data subset selection and active learning

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.267719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d101e4b3-6a11-4fd6-8d57-7b80bfc2120d · outbound

This paper cites Decentralized gradient tracking for continuous dr-submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized gradient tracking for continuous dr-submodular maximization

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.258072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30c025bf-45e4-4255-9b41-8d5ec57c0788 · outbound

This paper cites Online submodular coordination with bounded tracking regret: Theory, algorithm, and applications to multi-robot coordination.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online submodular coordination with bounded tracking regret: Theory, algorithm, and applications to multi-robot coordination

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.248936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0b093079-da53-4bd8-a4d4-7f4afc25a554 · outbound

This paper cites On the convergence of decentralized gradient descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On the convergence of decentralized gradient descent

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.239716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 69b3962d-015d-4a97-9eda-69fe94c06c08 · outbound

This paper cites Stochastic continuous submodular maximization: Boosting via non-oblivious function.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Stochastic continuous submodular maximization: Boosting via non-oblivious function

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.230108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b936baff-8a86-42c1-9efb-266385226909 · outbound

This paper cites Communication-efficient decentralized online continuous dr-submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Communication-efficient decentralized online continuous dr-submodular maximization

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.220782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d145699e-4209-4e17-b01a-5e04ddec62cb · outbound

This paper cites Boosting Gradient Ascent for Continuous DR-submodular Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Boosting Gradient Ascent for Continuous DR-submodular Maximization

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:42:39.090502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 92c29081-f9a6-42ec-a93d-909dd6e1137d · outbound

This paper cites Minimax optimal q learning with nearest neighbors.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Minimax optimal q learning with nearest neighbors

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.210706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2275dcd2-74af-4d7f-a531-0882a8996bb0 · outbound

This paper cites A huber loss minimization approach to mean estimation under user-level differential privacy.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A huber loss minimization approach to mean estimation under user-level differential privacy

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.200008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a77bdfe1-0252-4252-8029-4630fc454c92 · outbound

This paper cites A huber loss minimization approach to byzantine robust federated learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A huber loss minimization approach to byzantine robust federated learning

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.190000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b6ffbbb7-e452-4769-ac7b-6029cdff8eee · outbound

This paper cites Risk-aware submodular optimization for multirobot coordination.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Risk-aware submodular optimization for multirobot coordination

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.179681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 96adf695-67a3-475a-b829-b78233b009d1 · outbound

This paper cites Resilient active target tracking with multiple robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Resilient active target tracking with multiple robots

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.170012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a057bfe9-2922-4601-8280-b26c071515d7 · outbound

This paper cites Projection-free decentralized online learning for submodular maximization over time-varying networks.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Projection-free decentralized online learning for submodular maximization over time-varying networks

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:42:39.160071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ea9b0420-23f4-4496-a3ef-9db5593e49ca · outbound

This paper cites @esa (Ref.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency @esa (Ref

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-08T20:42:39.048767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd28cc2-acfe-4c47-a71e-bdb330904553 · outbound

This paper cites an unresolved cited work.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Unresolved cited work

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-08T20:42:39.052045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46e34410-7dd1-48af-8a8f-222e1848cd6f · outbound

This paper cites an unresolved cited work.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Unresolved cited work

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-08T20:42:39.055335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers