π
π
The Cartographer
Climbing LP Algorithms
December 31, 2020 Β· Declared Dead Β· π Symposium on the Theory of Computing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Leonid A. Levin
arXiv ID
2101.00101
Category
cs.DS: Data Structures & Algorithms
Cross-listed
math.OC
Citations
0
Venue
Symposium on the Theory of Computing
Last Checked
4 months ago
Abstract
NP (search) problems allow easy correctness tests for solutions. Climbing algorithms allow also easy assessment of how close to yielding the correct answer is the configuration at any stage of their run. This offers a great flexibility, as how sensible is any deviation from the standard procedures can be instantly assessed. An example is the Dual Matrix Algorithm (DMA) for linear programming, variations of which were considered by A.Y. Levin in 1965 and by Yamnitsky and myself in 1982. It has little sensitivity to numerical errors and to the number of inequalities. It offers substantial flexibility and, thus, potential for further developments.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted