The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Error bounds and convergence analysis of feasible descent methods: a general approach
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Iterative Solution of Nonlinear Equations in Several Variables
Ortega, J. M., & Rheinboldt, W. C. (2000) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9780898719468 · Cited by 6,860
Parallel and Distributed Computation: Numerical Methods
Bertsekas, D. P., & Tsitsiklis, J. N. (1989) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 5,293
Linear and nonlinear programming.
(1986) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(86)90092-3 · Cited by 4,805
Iterative Solution of Nonlinear Equations in Several Variables
I., E., Ortega, J. M., & Rheinboldt, W. C. (1971) · Mathematics of Computation · doi:10.2307/2004942 · Cited by 4,408
Monotone Operators and the Proximal Point Algorithm
Rockafellar, R. T. (1976) · SIAM Journal on Control and Optimization · doi:10.1137/0314056 · Cited by 3,559
Linear and Nonlinear Programming
Luenberger, D. G., & Ye, Y. (2008) · International Series in Operations Research & Management Science · doi:10.1007/978-0-387-74503-9 · Cited by 2,804
Bregman, L. M. (1967) · USSR Computational Mathematics and Mathematical Physics · doi:10.1016/0041-5553(67)90040-7 · Cited by 2,618
Distributed asynchronous deterministic and stochastic gradient optimization algorithms
Tsitsiklis, J., Bertsekas, D., & Athans, M. (1986) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1986.1104412 · Cited by 1,967
The extragradient method for finding saddle points and other problems
Korpelevich, G. M. (1976) · Medical Entomology and Zoology · Cited by 1,607
Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
Rockafellar, R. T. (1976) · Mathematics of Operations Research · doi:10.1287/moor.1.2.97 · Cited by 1,175
Constrained minimization methods
Levitin, E. S., & Polyak, B. T. (1966) · USSR Computational Mathematics and Mathematical Physics · doi:10.1016/0041-5553(66)90114-5 · Cited by 846
On the Convergence of the Proximal Point Algorithm for Convex Minimization
Güler, O. (1991) · SIAM Journal on Control and Optimization · doi:10.1137/0329022 · Cited by 681
Convex programming in Hilbert space
Goldstein, A. A. (1964) · Bulletin of the American Mathematical Society · doi:10.1090/s0002-9904-1964-11178-2 · Cited by 633
Projected Newton Methods for Optimization Problems with Simple Constraints
Bertsekas, D. P. (1982) · SIAM Journal on Control and Optimization · doi:10.1137/0320018 · Cited by 613
On the Goldstein-Levitin-Polyak gradient projection method
Bertsekas, D. P. (1976) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1976.1101194 · Cited by 583
On the convergence of the coordinate descent method for convex differentiable minimization
Luo, Z. Q., & Tseng, P. (1992) · Journal of Optimization Theory and Applications · doi:10.1007/bf00939948 · Cited by 502
Self-citationA quadratic programming procedure
Hildreth, C. (1957) · Naval Research Logistics Quarterly · doi:10.1002/nav.3800040113 · Cited by 378
Generalized equations and their solutions, part II: Applications to nonlinear programming
Robinson, S. M. (1982) · Mathematical programming studies · doi:10.1007/bfb0120989 · Cited by 367
Projection methods for variational inequalities with application to the traffic assignment problem
Bertsekas, D. P., & Gafni, E. M. (1982) · Mathematical Programming Studies · doi:10.1007/bfb0120965 · Cited by 333
Solution of symmetric linear complementarity problems by iterative methods
Mangasarian, O. L. (1977) · Journal of Optimization Theory and Applications · doi:10.1007/bf01268170 · Cited by 327
Two-Metric Projection Methods for Constrained Optimization
Gafni, E. M., & Bertsekas, D. P. (1984) · SIAM Journal on Control and Optimization · doi:10.1137/0322061 · Cited by 234
Optimisation : méthodes numériques
Auslender, A. (1976) · Masson eBooks · Cited by 210
On the Linear Convergence of Descent Methods for Convex Essentially Smooth Minimization
Luo, Z.-Q. T., & Tseng, P. (1992) · SIAM Journal on Control and Optimization · doi:10.1137/0330025 · Cited by 190
Self-citationDistributed asynchronous optimal routing in data networks
Tsitsiklis, J. N., & Bertsekas, D. P. (1986) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1986.1104261 · Cited by 140
Iterative Methods for Large Convex Quadratic Programs: A Survey
Lin, Y., & Pang, J. (1987) · SIAM Journal on Control and Optimization · doi:10.1137/0325023 · Cited by 123
Minimizing Certain Convex Functions
Warga, J. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111043 · Cited by 97
Combined Primal–Dual and Penalty Methods for Convex Programming
Kort, B., & Bertsekas, D. P. (1976) · SIAM Journal on Control and Optimization · doi:10.1137/0314020 · Cited by 95
A convex programming procedure
D'Esopo, D. A. (1959) · Naval Research Logistics Quarterly · doi:10.1002/nav.3800060105 · Cited by 74
On the Convergence Rate of Dual Ascent Methods for Linearly Constrained Convex Minimization
Luo, Z.-Q. T., & Tseng, P. (1993) · Mathematics of Operations Research · doi:10.1287/moor.18.4.846 · Cited by 74
Self-citationOn the Rate of Convergence of a Partially Asynchronous Gradient Projection Algorithm
Tseng, P. (1991) · SIAM Journal on Optimization · doi:10.1137/0801036 · Cited by 69
Self-citationLuo, Z.-Q. T., & Tseng, P. (1991) · SIAM Journal on Control and Optimization · doi:10.1137/0329057 · Cited by 64
Self-citationPang, J. (1986) · Journal of Optimization Theory and Applications · doi:10.1007/bf00939250 · Cited by 39
Cited by
Wright, S. J. (2015) · Mathematical Programming · doi:10.1007/s10107-015-0892-3 · Cited by 1,438
Error bounds in mathematical programming
Pang, J.-S. (1997) · Mathematical Programming · doi:10.1007/bf02614322 · Cited by 441
Successive overrelaxation for support vector machines
Mangasarian, O. L., & Musicant, D. R. (1999) · IEEE Transactions on Neural Networks · doi:10.1109/72.788643 · Cited by 438
Non-convex Optimization for Machine Learning
Jain, P., & Kar, P. (2017) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000058 · Cited by 364
Metadata
- Authors
- Luo, Z.-Q., & Tseng, P.
- Venue
- Annals of Operations Research
- Published
- 1993-03
- Volume
- 46-47
- Issue
- 1
- Pages
- 157-178
- ISSN
- 0254-5330 (ISSN-L)
- 1572-9338
- OpenAlex
- W2093417350
- Cited by
- 420
- References
- 32
- FWCI
- 1.62
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.