Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence | Paper Citation Record

Observation bbee5fce-7468-4416-9b87-8f38a6b409c7 · outbound

This paper cites A gradient method for multilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A gradient method for multilevel optimization

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This paper cites Betty: An automatic differentiation library for multilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Betty: An automatic differentiation library for multilevel optimization

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This paper cites When nas meets robustness: In search of robust architectures against adversarial attacks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence When nas meets robustness: In search of robust architectures against adversarial attacks

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This paper cites Provably convergent federated trilevel learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Provably convergent federated trilevel learning

Reference 4

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This paper cites The computational complexity of multi-level linear programs.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence The computational complexity of multi-level linear programs

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This paper cites Mixed-integer multi-level optimization through multi-parametric programming.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Mixed-integer multi-level optimization through multi-parametric programming

Reference 6

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This paper cites Computational difficulties of bilevel linear programming.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Computational difficulties of bilevel linear programming

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This paper cites A review on bilevel optimization: From classical to evolutionary approaches and applications.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A review on bilevel optimization: From classical to evolutionary approaches and applications

Reference 8

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Observation d3aac9b0-70e6-400d-ac6b-98ee89e04323 · outbound

This paper cites Communication-efficient stochastic zeroth-order optimization for federated learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Communication-efficient stochastic zeroth-order optimization for federated learning

Reference 9

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This paper cites Zeroth-order methods for nondifferentiable, nonconvex, and hierarchical federated optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order methods for nondifferentiable, nonconvex, and hierarchical federated optimization

Reference 10

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This paper cites Zeroth-order stochastic variance reduction for nonconvex optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order stochastic variance reduction for nonconvex optimization

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Observation e65c27a2-d1c0-42ee-a930-48b211f89513 · outbound

This paper cites Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization

Reference 12

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Observation 69496f40-972f-4d9c-af02-94ddbd6e7c7e · outbound

This paper cites Stochastic zeroth-order optimization in high dimensions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic zeroth-order optimization in high dimensions

Reference 13

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Observation 6f37f70c-4aeb-49be-bd2b-3463cb69c409 · outbound

This paper cites Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models

Reference 14

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Observation 5cb6a5bd-0392-404d-bcaa-08b9d3fa5d6d · outbound

This paper cites Zeroth-order non-convex learning via hierarchical dual averaging.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order non-convex learning via hierarchical dual averaging

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This paper cites A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization

Reference 16

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Observation a0c4fb39-eabf-4b0b-a3a7-79328df7526a · outbound

This paper cites Can stochastic zeroth-order frank-wolfe method converge faster for non- convex problems? In International conference on machine learning, pages 3377–3386.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Can stochastic zeroth-order frank-wolfe method converge faster for non- convex problems? In International conference on machine learning, pages 3377–3386

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Observation 3e4147d7-9bfe-440d-9018-b74b5754ae94 · outbound

This paper cites Zeroth-order optimization with weak dimension dependency.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order optimization with weak dimension dependency

Reference 18

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Observation 70cfb9f5-96c8-4331-93eb-e2a23b62218e · outbound

This paper cites Zeroth-order optimization for composite problems with functional constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order optimization for composite problems with functional constraints

Reference 19

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Observation 92fe52e3-08e9-4e97-9b16-0d745066ce18 · outbound

This paper cites Escaping saddle points in zeroth-order optimization: the power of two-point estimators.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Escaping saddle points in zeroth-order optimization: the power of two-point estimators

Reference 20

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Observation 9978564d-9e4c-4294-af88-fc8c253f60c5 · outbound

This paper cites Black-box generalization: Stability of zeroth-order learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box generalization: Stability of zeroth-order learning

Reference 21

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This paper cites Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks

Reference 22

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Observation 1a3d4ad7-02d0-4022-98e7-59b3d8363552 · outbound

This paper cites An optimal structured zeroth-order algorithm for non-smooth optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence An optimal structured zeroth-order algorithm for non-smooth optimization

Reference 23

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This paper cites A comprehensive linear speedup analysis for asynchronous stochastic parallel optimization from zeroth-order to first-order.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A comprehensive linear speedup analysis for asynchronous stochastic parallel optimization from zeroth-order to first-order

Reference 24

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This paper cites Distributed zero-order algorithms for nonconvex multiagent optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zero-order algorithms for nonconvex multiagent optimization

Reference 25

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This paper cites Fine-grained theoretical analysis of federated zeroth-order optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fine-grained theoretical analysis of federated zeroth-order optimization

Reference 26

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This paper cites Distributed zero-order optimization under adversarial noise.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zero-order optimization under adversarial noise

Reference 27

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This paper cites Distributed zeroth order optimization over random networks: A kiefer-wolfowitz stochastic approximation approach.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zeroth order optimization over random networks: A kiefer-wolfowitz stochastic approximation approach

Reference 28

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This paper cites Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Meta- learning to improve pre-training

Reference 30

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This paper cites Learning from mistakes–a framework for neural architecture search.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Learning from mistakes–a framework for neural architecture search

Reference 31

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This paper cites Convex optimization algorithms.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Convex optimization algorithms

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This paper cites Cutting plane methods in machine learning.Optimization for Machine Learning, pages 185–218, 2011.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Cutting plane methods in machine learning.Optimization for Machine Learning, pages 185–218, 2011

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed robust optimization (DRO), part I: Framework and example

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This paper cites A polyhedral approximation framework for convex and robust distributed optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A polyhedral approximation framework for convex and robust distributed optimization

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Asynchronous distributed bilevel optimization

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This paper cites Robust beamforming for downlink multi-cell systems: A bilevel optimization perspective.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Robust beamforming for downlink multi-cell systems: A bilevel optimization perspective

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This paper cites Centralized and federated learning for predictive vnf autoscaling in multi-domain 5g networks and beyond.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Centralized and federated learning for predictive vnf autoscaling in multi-domain 5g networks and beyond

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Advances in asynchronous parallel and distributed optimization

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This paper cites ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting

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This paper cites A fully first-order method for stochastic bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A fully first-order method for stochastic bilevel optimization

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This paper cites A conditional gradient- based method for simple bilevel optimization with convex lower-level problem.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A conditional gradient- based method for simple bilevel optimization with convex lower-level problem

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Darts: Differentiable architecture search

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This paper cites A general stochastic approach to solving problems with hard and soft constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A general stochastic approach to solving problems with hard and soft constraints

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This paper cites An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic first-and zeroth-order methods for nonconvex stochastic program- ming

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This paper cites On Penalty-based Bilevel Gradient Descent Method.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence On Penalty-based Bilevel Gradient Descent Method

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Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Improved penalty method via doubly stochastic gradients for bilevel hyperparameter optimization

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This paper cites Convex optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Convex optimization

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This paper cites A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems

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This paper cites Complexities in projection-free stochastic non-convex minimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Complexities in projection-free stochastic non-convex minimization

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This paper cites Enhancing the resilience of llms against grey-box extractions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Enhancing the resilience of llms against grey-box extractions

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This paper cites Random gradient-free minimization of convex functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Random gradient-free minimization of convex functions

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Observation c1240d61-38d7-42a6-ba24-6a97c5e965dd · outbound

This paper cites Accelerated zeroth-order method for non-smooth stochastic convex optimization problem with infinite variance.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Accelerated zeroth-order method for non-smooth stochastic convex optimization problem with infinite variance

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.301308Z

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Observation 1f898507-b49d-4995-ba54-16912c1d3a99 · outbound

This paper cites Distributionally robust federated averaging.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributionally robust federated averaging

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.770461Z

Source-reported events for the cited work

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Observation 18db01f0-37ed-4feb-8bb1-18893a931826 · outbound

This paper cites Robust optimization over multiple domains.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Robust optimization over multiple domains

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.755864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f1c78f3-fb9f-468e-8d7b-9c184a0bdda6 · outbound

This paper cites Stochastic composite mirror descent: Optimal bounds with high probabilities.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic composite mirror descent: Optimal bounds with high probabilities

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.740926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 97673eae-14ed-4c3e-82b7-4f87aa37961a · outbound

This paper cites Asynchronous stochastic gradient descent with delay compensation.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Asynchronous stochastic gradient descent with delay compensation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.726586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0f07b1fa-770f-49c8-aa03-47cc462e6b4f · outbound

This paper cites Momentum-based variance reduction in non-convex sgd.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Momentum-based variance reduction in non-convex sgd

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.321987Z

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Unavailable: canonical work link unavailable.

Observation 46157436-cc4f-42f7-8731-722ed96dc2f9 · outbound

This paper cites Conflict-averse gradient descent for multi-task learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Conflict-averse gradient descent for multi-task learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.326077Z

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Observation f81eac78-1ed7-4fbf-813e-766f57c558c1 · outbound

This paper cites Truncated back-propagation for bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Truncated back-propagation for bilevel optimization

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.693787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 641843ad-7bd0-4a94-89bd-78df95454bb0 · outbound

This paper cites Decentralized stochastic bilevel optimization with improved per-iteration complexity.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Decentralized stochastic bilevel optimization with improved per-iteration complexity

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.679831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ff36d036-0dad-4aaa-a832-5c79754f81ed · outbound

This paper cites Non-convex bilevel optimization with time-varying objective functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Non-convex bilevel optimization with time-varying objective functions

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.664575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0539c1b5-b516-43d6-87e0-6a49efc0e3e4 · outbound

This paper cites Revisiting zeroth-order optimization for memory-efficient llm fine-tuning: A benchmark.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Revisiting zeroth-order optimization for memory-efficient llm fine-tuning: A benchmark

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.650101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 60ffe417-3390-479f-9f70-79422fdadedb · outbound

This paper cites Subspace selection based prompt tuning with nonconvex nonsmooth black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Subspace selection based prompt tuning with nonconvex nonsmooth black-box optimization

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.634567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 40b136e8-984d-4954-88a7-9721feffdd23 · outbound

This paper cites Optimal rates for zero-order convex optimization: The power of two function evaluations.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Optimal rates for zero-order convex optimization: The power of two function evaluations

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.618989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 89d8bf18-8c08-4e4a-9ad8-7dde7f40117f · outbound

This paper cites Black-box tuning for language- model-as-a-service.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box tuning for language- model-as-a-service

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.603958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b6312f70-8ccd-43d1-ae72-9be0442b6c14 · outbound

This paper cites Fairness-guided few-shot prompting for large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fairness-guided few-shot prompting for large language models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.588161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 163473f0-3ba3-4333-b45c-e8835ae0f464 · outbound

This paper cites Grammar prompting for domain-specific language generation with large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Grammar prompting for domain-specific language generation with large language models

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.573530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 565d5bd5-28c4-4e5b-9e01-a9ed8eace726 · outbound

This paper cites Black-box prompt learning for pre-trained language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box prompt learning for pre-trained language models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.559059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f2fdcbe9-ae00-497b-8a61-50c2cc82b891 · outbound

This paper cites Poisonprompt: Backdoor attack on prompt-based large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Poisonprompt: Backdoor attack on prompt-based large language models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.374209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e08e1c3-bf9a-418f-b90b-967c268911cb · outbound

This paper cites Qwen Technical Report.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Qwen Technical Report

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.378394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e42a5d5-b01f-45f4-931b-e6e3443dc5b3 · outbound

This paper cites Glue: A multi-task benchmark and analysis platform for natural language understanding.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Glue: A multi-task benchmark and analysis platform for natural language understanding

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.382930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c793e8bf-abd5-49bd-8eae-8139099fc72f · outbound

This paper cites Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by gaussian-guided latent alignment.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by gaussian-guided latent alignment

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.526125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation df9a19a2-fd6c-4430-82bd-8a9ea6430753 · outbound

This paper cites Gradient-based learning applied to document recognition.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Gradient-based learning applied to document recognition

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.393825Z

Source-reported events for the cited work

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Observation f27c5e95-fb1d-41d3-a8e3-73ee46f6ec6b · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.398123Z

Source-reported events for the cited work

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Observation 20be34c0-2a01-4f4b-95bd-3a472c06acec · outbound

This paper cites Cold case: The lost mnist digits.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Cold case: The lost mnist digits

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.501228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9b383205-7306-4fe3-998e-b6136a3c7027 · outbound

This paper cites A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.486108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fd34abbb-0c55-407c-95ea-83938f5d8bb4 · outbound

This paper cites Using hard constraints for representing soft constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Using hard constraints for representing soft constraints

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.471639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a9ffa79d-36bc-4b0d-ba03-42208ffcab99 · outbound

This paper cites Combining hard and soft constraints in quantum constraint- satisfaction systems.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Combining hard and soft constraints in quantum constraint- satisfaction systems

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.456469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bffaaca4-b0f9-41c1-a97a-6454edd8a38b · outbound

This paper cites Bilevel optimization: Convergence analysis and enhanced design.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bilevel optimization: Convergence analysis and enhanced design

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.440419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 929f43d3-1f01-4207-942f-ee31d8fd0564 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Model-agnostic meta-learning for fast adaptation of deep networks

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.425458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee49a28b-9d09-44cb-bd7d-22a9aba75db9 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Towards deep learning models resistant to adversarial attacks

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.429948Z

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Observation 95d3da26-dc08-467d-87ee-b0303a81b7e9 · outbound

This paper cites Revisiting and advancing fast adversarial training through the lens of bi-level optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Revisiting and advancing fast adversarial training through the lens of bi-level optimization

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.405740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a2c4bc43-5e3e-4583-a9a6-9958a21ef20e · outbound

This paper cites Distributed distributionally robust optimization with non-convex objectives.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed distributionally robust optimization with non-convex objectives

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.389653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f7c4393-204e-475c-9f45-81ce97965a42 · outbound

This paper cites Provably faster algorithms for bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Provably faster algorithms for bilevel optimization

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.442411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20ae0d95-291b-4a4f-95e5-f4ea1d5fa2d5 · outbound

This paper cites Bilevel programming for hyperparameter optimization and meta-learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bilevel programming for hyperparameter optimization and meta-learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.446552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c821d092-9333-42a9-a1e5-8cb5db9c49a6 · outbound

This paper cites Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.355376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 695db97f-a203-40a6-8ffc-a272dd794531 · outbound

This paper cites Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.341215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d19c0783-471b-4231-b534-07080a5eedc6 · outbound

This paper cites Timeautoad: Autonomous anomaly detection with self- supervised contrastive loss for multivariate time series.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Timeautoad: Autonomous anomaly detection with self- supervised contrastive loss for multivariate time series

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.326892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5d462cb2-b08a-466b-bab7-aed47192056a · outbound

This paper cites Fedal: Black-box federated knowledge distillation enabled by adversarial learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fedal: Black-box federated knowledge distillation enabled by adversarial learning

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.312624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation af6c0fdd-aec8-4e58-9b93-b740efb8bb90 · outbound

This paper cites Deep Learning for Classical Japanese Literature.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Deep Learning for Classical Japanese Literature

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T19:10:52.468158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93f8898e-a0da-4f3c-825a-21ed255b05b5 · outbound

This paper cites Adadelay: Delay adaptive distributed stochastic optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Adadelay: Delay adaptive distributed stochastic optimization

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.298064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f104d94-0a9f-4c5c-bbdc-a4cfe3227ba0 · outbound

This paper cites Distributed Zeroth-Order Stochastic Optimization in Time-varying Networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed Zeroth-Order Stochastic Optimization in Time-varying Networks

Reference 94

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:10:52.705038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4d092559-1342-47af-92a2-c12a229c6064 · outbound

This paper cites Projection- free methods for stochastic simple bilevel optimization with convex lower-level problem.Advances in Neural Information Processing Systems, 36, 2024.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Projection- free methods for stochastic simple bilevel optimization with convex lower-level problem.Advances in Neural Information Processing Systems, 36, 2024

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.285101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3dfd6886-d1e4-4165-914c-af0a17e16e18 · outbound

This paper cites signsgd via zeroth-order oracle.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence signsgd via zeroth-order oracle

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.270791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7135e7db-5192-4a1e-92d4-94721f80349d · outbound

This paper cites Bome! bilevel optimization made easy: A simple first-order approach.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bome! bilevel optimization made easy: A simple first-order approach

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.256189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 71cab522-8bd3-48ea-bba8-fef0cbd0b8b0 · outbound

This paper cites A novel chattering-free discrete sliding mode controller with disturbance compensation for zinc roasting temperature distribution control.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A novel chattering-free discrete sliding mode controller with disturbance compensation for zinc roasting temperature distribution control

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.242224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 675f19e5-a81e-4273-ad0a-a68cab53892d · outbound

This paper cites Decentralized multi-level compositional optimization algorithms with level-independent convergence rate.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Decentralized multi-level compositional optimization algorithms with level-independent convergence rate

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.226906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f6e58254-7e82-4beb-a751-739a5f5d296a · outbound

This paper cites On the convergence of local stochastic compositional gradient descent with momentum.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence On the convergence of local stochastic compositional gradient descent with momentum

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:10:53.212223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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