Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable | Paper Citation Record

Observation 4019962a-83ed-4129-b8a9-451a02ac9056 · outbound

This paper cites Natural gradient works efficiently in learning.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Natural gradient works efficiently in learning

Reference 1

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Observation 999271e3-3eaa-4553-90cc-4ce0b3292191 · outbound

This paper cites Why natural gradient? In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing , volume 2, pages 1213–1216, 1998.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Why natural gradient? In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing , volume 2, pages 1213–1216, 1998

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.099603Z

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Observation b96b07d7-fa4b-442e-bf05-bbd761e99cb2 · outbound

This paper cites Intrinsic robustness of global asymptotic stability.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Intrinsic robustness of global asymptotic stability

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.082598Z

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Observation 7eaf27d4-9a56-427a-be3f-9c70c3dcb97c · outbound

This paper cites Robust accelerated gradient methods for smooth strongly convex functions.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Robust accelerated gradient methods for smooth strongly convex functions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.063967Z

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Observation e7440cc7-edd5-4ab8-8ea9-ec991c929b0e · outbound

This paper cites Nonlinear Programming.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Nonlinear Programming

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.043932Z

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Observation cd20acbc-cb7f-4d1d-a109-b61f8e1523fa · outbound

This paper cites Bertsekas and John N.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Bertsekas and John N

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.025793Z

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Observation 0f0fb140-d289-44b5-9538-15fdd4b0f1be · outbound

This paper cites Bertsekas and John N.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Bertsekas and John N

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:14.008641Z

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Observation be855d86-ddfa-458a-9178-2dc3fc2ba59b · outbound

This paper cites Poveda, and Emiliano Dall’Anese.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Poveda, and Emiliano Dall’Anese

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.988481Z

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Observation 9175930b-44d0-4652-b7cf-9f569b2d61db · outbound

This paper cites On Topological and Metrical Properties of Stabilizing Feedback Gains: the MIMO Case.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable On Topological and Metrical Properties of Stabilizing Feedback Gains: the MIMO Case

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.626378Z

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Observation a7cdc2d0-2449-4b25-aab7-3b91cc0ff182 · outbound

This paper cites Policy Gradient-based Algorithms for Continuous-time Linear Quadratic Control.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Policy Gradient-based Algorithms for Continuous-time Linear Quadratic Control

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.633866Z

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Observation db794b79-1aae-420d-91fc-10fcb94a2f3e · outbound

This paper cites The role of convexity in saddle-point dynamics: Lyapunov function and robustness.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable The role of convexity in saddle-point dynamics: Lyapunov function and robustness

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.969875Z

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Observation 23d14a74-a7a5-4ec0-8d62-f71cbf6a4adc · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.949753Z

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Observation 4028b3bb-5135-490c-80ec-1b507d9bcdb5 · outbound

This paper cites Input-to-state stability of a bilevel proximal gradient descent algorithm.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Input-to-state stability of a bilevel proximal gradient descent algorithm

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.930740Z

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Observation b012db8f-86ac-46b7-93bf-c426a387724b · outbound

This paper cites A robust accelerated optimization algorithm for strongly convex functions.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable A robust accelerated optimization algorithm for strongly convex functions

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.912461Z

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Observation 51bee6ce-6aaf-4aa4-90dc-d10ceecc7e87 · outbound

This paper cites First- order methods of smooth convex optimization with inexact oracle.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable First- order methods of smooth convex optimization with inexact oracle

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.893678Z

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Observation e4d4c17c-9fbb-4761-abea-6b04ee2fe145 · outbound

This paper cites Global convergence of policy gradient methods for the linear quadratic regulator.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Global convergence of policy gradient methods for the linear quadratic regulator

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.865495Z

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Observation 8e072483-5ea6-44e2-a4f4-57c2f2787876 · outbound

This paper cites Convex open subsets of Rn are homeomorphic to n-dimensional open balls.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Convex open subsets of Rn are homeomorphic to n-dimensional open balls

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.845775Z

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Observation d7c8da69-1c98-4884-b743-73bbd93c9b18 · outbound

This paper cites On a Newton-like method for solving algebraic Riccati equations.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable On a Newton-like method for solving algebraic Riccati equations

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.824018Z

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Observation d0dfad06-2497-4aa6-81e6-438859f0012e · outbound

This paper cites Stability of Motion.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Stability of Motion

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.805104Z

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Observation a9a71c16-27cb-47fe-97a0-ddb407f3e78f · outbound

This paper cites Dissipativity theory for Nesterov’s accelerated method.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Dissipativity theory for Nesterov’s accelerated method

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.786798Z

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Observation dd2d125b-618a-41b7-9837-943891c47a9d · outbound

This paper cites Toward a theoretical foundation of policy optimization for learning control policies.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Toward a theoretical foundation of policy optimization for learning control policies

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.766428Z

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Observation 35fd2368-b261-47b8-bc56-9ec91759050d · outbound

This paper cites Robust Adaptive Dynamic Programming.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Robust Adaptive Dynamic Programming

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.745815Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dbe865fe-925a-4d6a-8002-caa5c87faf5a · outbound

This paper cites Learning- based control: A tutorial and some recent results.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Learning- based control: A tutorial and some recent results

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.726637Z

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Observation cf2b99d2-ddb4-4653-8fa7-55a70f83bd95 · outbound

This paper cites Teel, and Laurent Praly.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Teel, and Laurent Praly

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.710621Z

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Observation 5baed8f2-cc54-44d8-a602-d778740a65c0 · outbound

This paper cites Input-to-state stability for discrete-time nonlinear systems.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Input-to-state stability for discrete-time nonlinear systems

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.693820Z

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Observation b51150e6-2443-4396-9f99-7addf3c5a6af · outbound

This paper cites A converse Lyapunov theorem for discrete-time systems with disturbances.Systems & Control Letters , 45(1):49–58, 2002.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable A converse Lyapunov theorem for discrete-time systems with disturbances.Systems & Control Letters , 45(1):49–58, 2002

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.675025Z

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Observation 16ea31a4-9822-4321-a7d6-e71f5ce3fb49 · outbound

This paper cites Dynamical, symplectic and stochastic perspectives on gradient-based optimization.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Dynamical, symplectic and stochastic perspectives on gradient-based optimization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.655528Z

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Observation c56d7e03-92c5-4e48-b078-afa1192b1014 · outbound

This paper cites Contributions to the theory of optimal control.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Contributions to the theory of optimal control

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.636984Z

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Observation 37c57029-541e-4b73-a109-666a42f80ef4 · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the Polyak- Lojasiewicz condition.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Linear convergence of gradient and proximal-gradient methods under the Polyak- Lojasiewicz condition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.617829Z

Source-reported events for the cited work

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Observation 10c9d03d-7308-4d35-b9c9-5c48c71cdf24 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Adam: A Method for Stochastic Optimization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.749598Z

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Observation a71d7601-e957-4c7c-8e65-413851ecd323 · outbound

This paper cites Kleinman.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Kleinman

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.601820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3894cd58-7db7-49f9-905c-9d2b61d9e4fc · outbound

This paper cites Actor-critic algorithms.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Actor-critic algorithms

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.580992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 59a6bae2-7a33-4ce1-8c51-fdd5e980a2c7 · outbound

This paper cites Analysis and design of optimization algorithms via integral quadratic constraints.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Analysis and design of optimization algorithms via integral quadratic constraints

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.562526Z

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Observation fb9eaf88-1f2f-4f50-9e6e-9c9db6f543af · outbound

This paper cites Levine and Michael Athans.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Levine and Michael Athans

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.544113Z

Source-reported events for the cited work

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Observation c90f5fc9-214f-4003-858e-5f51a2984132 · outbound

This paper cites Distributed reinforcement learning for decentralized linear quadratic control: A derivative-free policy optimization approach.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Distributed reinforcement learning for decentralized linear quadratic control: A derivative-free policy optimization approach

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.526285Z

Source-reported events for the cited work

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Observation 50667f4e-144f-46f2-8dbe-2fe561bb7f25 · outbound

This paper cites Continuous control with deep reinforcement learning.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Continuous control with deep reinforcement learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.783504Z

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Observation 5214e0e1-8790-4643-9938-238424868ae4 · outbound

This paper cites A topological property of real analytic subsets (in French).

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable A topological property of real analytic subsets (in French)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.509192Z

Source-reported events for the cited work

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Observation 11e386de-8597-4cc1-98a5-b78fc902733e · outbound

This paper cites Computational methods for parametric LQ problems–A survey.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Computational methods for parametric LQ problems–A survey

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.493900Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8172d8f-52ea-4034-a86b-e6fe6b31dbd9 · outbound

This paper cites Jovanovi´ c.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Jovanovi´ c

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.476911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 76c478a3-8a5f-48f1-a808-c54f31599749 · outbound

This paper cites Jovanovi´ c.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Jovanovi´ c

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.459655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0f85367e-a48b-42c0-8d1c-35ce48362f59 · outbound

This paper cites A systematic approach to Lyapunov analyses of continuous- time models in convex optimization.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable A systematic approach to Lyapunov analyses of continuous- time models in convex optimization

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.443427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d25a08f3-bb37-4652-8ba6-c7633a772090 · outbound

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

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Introductory Lectures on Convex Optimization: A Basic Course , volume 87

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.426749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e736fc66-6d01-40ea-8d40-c6a9ad01c242 · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.409918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f1ad3848-a1cd-4d11-b936-b63aab38a848 · outbound

This paper cites Robust policy iteration for continuous-time linear quadratic regulation.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Robust policy iteration for continuous-time linear quadratic regulation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.393241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4318f1e7-4995-441e-92cf-25060c7bcef4 · outbound

This paper cites Robust reinforcement learning: A case study in linear quadratic regulation.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Robust reinforcement learning: A case study in linear quadratic regulation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.371538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f52f9c84-9dbd-48b4-8f5a-9d3be1828dc6 · outbound

This paper cites The Matrix Cookbook, October 2008.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable The Matrix Cookbook, October 2008

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.352957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e57c7a3-0010-4314-b93c-a9f00b3fc389 · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.335404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 522cceb8-a2be-4012-ad8c-7c87fd1e4e43 · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.319946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bb844e5a-9b80-440c-abee-0fa777322a4a · outbound

This paper cites Poveda and Miroslav Krsti´ c.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Poveda and Miroslav Krsti´ c

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.304422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0ddc2ee8-46fa-4b6f-ab8a-83b476d948ae · outbound

This paper cites Trust region policy optimization.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Trust region policy optimization

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.289006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a8b8f215-5c0a-409b-ac3e-accfebf6859e · outbound

This paper cites Proximal Policy Optimization Algorithms.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Proximal Policy Optimization Algorithms

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.873024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c50d164f-ac3e-44d7-bf67-99fb1c607b16 · outbound

This paper cites Error stability properties of generalized gradient-type algorithms.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Error stability properties of generalized gradient-type algorithms

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.270111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6419b562-5a10-45d9-b89d-977eca8bfb1e · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.252592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 851de88d-8042-4e74-b2e2-bf24074db82d · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.235398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 14191f79-04d1-4c48-ad55-0865ede48d24 · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.219659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fa8790fb-ef6d-4a83-bf25-418212936911 · outbound

This paper cites an unresolved cited work.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:45:13.203682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 95bbea3b-6883-4778-8aec-5493d388dd5a · outbound

This paper cites Robustness and averaging properties of a large-amplitude, high-frequency extremum seeking control scheme.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Robustness and averaging properties of a large-amplitude, high-frequency extremum seeking control scheme

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.186332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e6322a2-f4d4-4d88-bc37-dadab952639e · outbound

This paper cites Sutton and Andrew G.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Sutton and Andrew G

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.166994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20a424fe-ebb3-4bd9-a6be-a2a262212b35 · outbound

This paper cites Trace bounds on the solution of the algebraic matrix Riccati and Lyapunov equation.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Trace bounds on the solution of the algebraic matrix Riccati and Lyapunov equation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.151397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1309a86b-5fc1-44b0-b692-2017633ee5e4 · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.134619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c824cba6-82f2-4f86-b1a6-546ac7a88f83 · outbound

This paper cites Wilson, Ben Recht, and Michael I.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Wilson, Ben Recht, and Michael I

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.114022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9968761c-2e80-410f-8a8b-cfd4a49b15a5 · outbound

This paper cites Wesley Wilson.

Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable Wesley Wilson

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:45:13.092738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers