Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm | Paper Citation Record

Observation 7fe6007d-7948-45e4-a9e7-6fb62f70210c · outbound

This paper cites A fast iterative shrinkage-thresholding algorithm for linear inverse problems.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A fast iterative shrinkage-thresholding algorithm for linear inverse problems

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Adaptive Regularization for Nonconvex Optimization Using Inexact Function Values and Randomly Perturbed Derivatives

Reference 2

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Topology optimization: theory, methods, and applications

Reference 3

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This paper cites An investigation of newton-sketch and subsampled newton methods.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm An investigation of newton-sketch and subsampled newton methods

Reference 4

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This paper cites An Adaptive Sampling Sequential Quadratic Programming Method for Equality Constrained Stochastic Optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm An Adaptive Sampling Sequential Quadratic Programming Method for Equality Constrained Stochastic Optimization

Reference 5

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This paper cites Global convergence rate anal- ysis of a generic line search algorithm with noise.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Global convergence rate anal- ysis of a generic line search algorithm with noise

Reference 6

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Nonlinear programming

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This paper cites Nonlinear programming: concepts, algorithms, and applications to chemical processes.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Nonlinear programming: concepts, algorithms, and applications to chemical processes

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This paper cites Adaptive sampling strategies for stochastic optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Adaptive sampling strategies for stochastic optimization

Reference 9

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This paper cites Exact and inexact subsam- pled newton methods for optimization.IMA Journal of Numerical Analysis, 39(2):545– 578, 2019.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Exact and inexact subsam- pled newton methods for optimization.IMA Journal of Numerical Analysis, 39(2):545– 578, 2019

Reference 10

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This paper cites A progressive batching l-bfgs method for machine learning.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A progressive batching l-bfgs method for machine learning

Reference 11

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This paper cites Optimization methods for large- scale machine learning.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Optimization methods for large- scale machine learning

Reference 12

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This paper cites On the use of stochastic hessian information in unconstrained optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm On the use of stochastic hessian information in unconstrained optimization

Reference 13

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This paper cites Sample size se- lection in optimization methods for machine learning.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Sample size se- lection in optimization methods for machine learning

Reference 14

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This paper cites First-and second-order high probability complexity bounds for trust-region methods with noisy oracles.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm First-and second-order high probability complexity bounds for trust-region methods with noisy oracles

Reference 15

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This paper cites Accelerated methods for nonconvex optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Accelerated methods for nonconvex optimization

Reference 16

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This paper cites On the global convergence of trust region algorithms using inexact gradient information.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm On the global convergence of trust region algorithms using inexact gradient information

Reference 17

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This paper cites Global convergence rate analysis of uncon- strained optimization methods based on probabilistic models.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Global convergence rate analysis of uncon- strained optimization methods based on probabilistic models

Reference 18

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This paper cites A nonlinear conjugate gradi- ent method with complexity guarantees and its application to nonconvex regression.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A nonlinear conjugate gradi- ent method with complexity guarantees and its application to nonconvex regression

Reference 19

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This paper cites Libsvm: a library for support vector machines.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Libsvm: a library for support vector machines

Reference 20

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This paper cites Exploiting negative curvature in deterministic and stochastic optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Exploiting negative curvature in deterministic and stochastic optimization

Reference 21

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This paper cites Trust- region newton-cg with strong second-order complexity guarantees for nonconvex opti- mization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Trust- region newton-cg with strong second-order complexity guarantees for nonconvex opti- mization

Reference 22

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This paper cites Optimization of energy systems.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Optimization of energy systems

Reference 23

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This paper cites Gradient descent can take exponential time to escape saddle points.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Gradient descent can take exponential time to escape saddle points

Reference 24

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This paper cites A modified newton method for mini- mization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A modified newton method for mini- mization

Reference 25

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This paper cites Computing modified newton di- rections using a partial cholesky factorization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Computing modified newton di- rections using a partial cholesky factorization

Reference 26

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This paper cites Hybrid deterministic-stochastic methods for data fitting.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Hybrid deterministic-stochastic methods for data fitting

Reference 27

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This paper cites Curvilinear path steplength algorithms for minimization which use directions of negative curvature.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Curvilinear path steplength algorithms for minimization which use directions of negative curvature

Reference 28

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This paper cites Deep learning.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Deep learning

Reference 29

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This paper cites Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms

Reference 30

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Adaptive filter theory

Reference 31

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This paper cites Methods of conjugate gradients for solving linear systems , volume 49.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Methods of conjugate gradients for solving linear systems , volume 49

Reference 32

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This paper cites How to escape saddle points efficiently.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm How to escape saddle points efficiently

Reference 33

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This paper cites Principal component analysis for special types of data.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Principal component analysis for special types of data

Reference 34

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This paper cites An iteration method for the solution of the eigenvalue problem of linear differential and integral operators.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm An iteration method for the solution of the eigenvalue problem of linear differential and integral operators

Reference 35

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Planning algorithms

Reference 36

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This paper cites Gen- eration of whole-body optimal dynamic multi-contact motions.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Gen- eration of whole-body optimal dynamic multi-contact motions

Reference 37

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This paper cites A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees

Reference 38

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This paper cites Adaptive negative curvature descent with applications in non-convex optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Adaptive negative curvature descent with applications in non-convex optimization

Reference 39

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Observation 2b14d727-50d4-4823-8e7f-c0a5d59ea2ed · outbound

This paper cites On Noisy Negative Curvature Descent: Competing with Gradient Descent for Faster Non-convex Optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm On Noisy Negative Curvature Descent: Competing with Gradient Descent for Faster Non-convex Optimization

Reference 40

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This paper cites Statistical consistency and asymptotic normality for high-dimensional robust m-estimators.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Statistical consistency and asymptotic normality for high-dimensional robust m-estimators

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.262268Z

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Observation f83015f6-578e-4f48-a745-7dee15efea33 · outbound

This paper cites Deep learning via hessian-free optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Deep learning via hessian-free optimization

Reference 42

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Observation b25a5947-e9a6-447f-bc43-7fe4fc490b22 · outbound

This paper cites On the use of directions of negative curvature in a modified newton method.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm On the use of directions of negative curvature in a modified newton method

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.244045Z

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Observation 1c4d120e-d611-4d47-a72a-343514dfcf02 · outbound

This paper cites Some np-complete problems in quadratic and nonlinear programming.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Some np-complete problems in quadratic and nonlinear programming

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.235108Z

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This paper cites Numerical optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Numerical optimization

Reference 45

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Observation 37e2405a-4894-41e3-b598-137a1184ef04 · outbound

This paper cites Quadratic programming with one negative eigenvalue is np-hard.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Quadratic programming with one negative eigenvalue is np-hard

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.220068Z

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Observation eca33d95-639b-4c1f-85f4-6f419c8a01f3 · outbound

This paper cites Digital signal processing: principles, algorithms, and applications, 4/E.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Digital signal processing: principles, algorithms, and applications, 4/E

Reference 47

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This paper cites Engineering optimization: theory and practice.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Engineering optimization: theory and practice

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.206009Z

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Observation c372cc29-5499-48bd-ac90-866536fc9910 · outbound

This paper cites A generic approach for escaping saddle points.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A generic approach for escaping saddle points

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.196085Z

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Observation 7efa281e-15a5-40d2-86f8-f5a86c0ccc0a · outbound

This paper cites A newton-cg algorithm with complexity guarantees for smooth unconstrained optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm A newton-cg algorithm with complexity guarantees for smooth unconstrained optimization

Reference 50

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This paper cites Complexity analysis of second-order line- search algorithms for smooth nonconvex optimization.SIAM Journal on Optimization, 28(2):1448–1477, 2018.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Complexity analysis of second-order line- search algorithms for smooth nonconvex optimization.SIAM Journal on Optimization, 28(2):1448–1477, 2018

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.182227Z

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Observation 75380be6-f679-452b-a729-5eb80b2f117a · outbound

This paper cites Chemical process: design and integration.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Chemical process: design and integration

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.172877Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 59c9c5d4-cc85-46ce-875a-b5bf98ee7ac2 · outbound

This paper cites The conjugate gradient method and trust regions in large scale optimization.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm The conjugate gradient method and trust regions in large scale optimization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.163285Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c587241e-a537-4ea6-bd56-e5ab9e460b9e · outbound

This paper cites John Wiley & Sons, 2013.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm John Wiley & Sons, 2013

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.153910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8f862df7-ca79-46d6-8eaa-a4170582987f · outbound

This paper cites Newton-type methods for non- convex optimization under inexact Hessian information.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Newton-type methods for non- convex optimization under inexact Hessian information

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.144599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7e853053-115a-4cde-9b60-5ce0e43d013c · outbound

This paper cites Robust linear regression: A review and comparison.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Robust linear regression: A review and comparison

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:52:08.135606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41ed7f94-500b-4966-b6b4-0f4928b94d7d · outbound

This paper cites From Symmetry to Geometry: Tractable Nonconvex Problems.

Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm From Symmetry to Geometry: Tractable Nonconvex Problems

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T19:52:08.047656Z

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