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On the complexity of polyhedral separability

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Outgoing claims: the papers this work cites, builds on, or argues with.

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inferredcites →https://doi.org/10.1109/sfcs.1982.74openalex-snapshot
Linear-time algorithms for linear programming in R3 and related problems
inferredcites →https://doi.org/10.1137/0212052openalex-snapshot
Linear-Time Algorithms for Linear Programming in $R^3 $ and Related Problems
inferredcites →https://doi.org/10.1145/12130.12158openalex-snapshot
Classifying learnable geometric concepts with the Vapnik-Chervonenkis dimension
inferredcites →https://doi.org/10.1145/2422.322418openalex-snapshot
Linear Programming in Linear Time When the Dimension Is Fixed
inferredcites →https://doi.org/10.1145/323233.323271openalex-snapshot
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Digital disks and a digital compactness measure

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4006048openalex-extracted
inferred← citeshttps://doi.org/10.1006/jcss.1997.1475openalex-snapshot
Learning an Intersection of a Constant Number of Halfspaces over a Uniform Distribution
inferred← citeshttps://doi.org/10.1006/jcss.2001.1797openalex-snapshot
The Computational Complexity of Densest Region Detection
inferred← citeshttps://doi.org/10.1007/11564096_53openalex-snapshot
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes
inferred← citeshttps://doi.org/10.1007/3-540-40992-0_20openalex-snapshot
On Approximate Learning by Multi-layered Feedforward Circuits
inferred← citeshttps://doi.org/10.1007/3-540-45583-3_9openalex-snapshot
Minimizing the Quadratic Training Error of a Sigmoid Neuron Is Hard
inferred← citeshttps://doi.org/10.1007/3-540-49097-3_5openalex-snapshot
Hardness Results for Neural Network Approximation Problems
inferred← citeshttps://doi.org/10.1007/3-540-53832-1_47openalex-snapshot
Separation problems and circular arc systems
inferred← citeshttps://doi.org/10.1007/3-540-60220-8_52openalex-snapshot
On the complexity of approximating and illuminating three-dimensional convex polyhedra
inferred← citeshttps://doi.org/10.1007/3-540-61332-3_161openalex-snapshot
On the difficulty of designing good classifiers
inferred← citeshttps://doi.org/10.1007/978-0-585-27366-2_8openalex-snapshot
A View of Computational Learning Theory
inferred← citeshttps://doi.org/10.1007/978-1-4471-1599-1_97openalex-snapshot
Some Complexity Results for Perceptron Networks
inferred← citeshttps://doi.org/10.1007/978-1-4615-2696-4_10openalex-snapshot
On the Intractability of Loading Neural Networks
inferred← citeshttps://doi.org/10.1007/978-1-4615-2696-4_9openalex-snapshot
Learning an Intersection of K Halfspaces Over a Uniform Distribution
inferred← citeshttps://doi.org/10.1007/978-3-030-06164-7_11openalex-snapshot
Statistical Computational Learning
inferred← citeshttps://doi.org/10.1007/978-3-030-06222-4_1openalex-snapshot
Marketing Meets Data Science: Bridging the Gap
inferred← citeshttps://doi.org/10.1007/978-3-030-73879-2_26openalex-snapshot
Computational Aspects of Relaxation Complexity
inferred← citeshttps://doi.org/10.1007/978-3-319-10605-2_42openalex-snapshot
Model Selection by Linear Programming
inferred← citeshttps://doi.org/10.1007/978-3-319-24953-7_5openalex-snapshot
Improving Interpolants for Linear Arithmetic
inferred← citeshttps://doi.org/10.1007/978-3-319-32360-2_32openalex-snapshot
Recognition of Digital Polyhedra with a Fixed Number of Faces
inferred← citeshttps://doi.org/10.1007/978-3-319-66272-5_23openalex-snapshot
Recognition of Digital Polyhedra with a Fixed Number of Faces Is Decidable in Dimension 3
inferred← citeshttps://doi.org/10.1007/978-3-540-72504-6_48openalex-snapshot
Separation of Data Via Concurrently Determined Discriminant Functions
inferred← citeshttps://doi.org/10.1007/978-3-540-72665-4_8openalex-snapshot
Selecting Genotyping Oligo Probes Via Logical Analysis of Data
inferred← citeshttps://doi.org/10.1007/978-3-540-72870-2_39openalex-snapshot
A Heuristic Method for Selecting Support Features from Large Datasets
inferred← citeshttps://doi.org/10.1007/978-3-642-11269-0_16openalex-snapshot
The Parameterized Complexity of Some Geometric Problems in Unbounded Dimension
inferred← citeshttps://doi.org/10.1007/978-3-642-13562-0_5openalex-snapshot
The Complexity of Geometric Problems in High Dimension
inferred← citeshttps://doi.org/10.1007/978-3-642-31424-7_11openalex-snapshot
Interpolants as Classifiers
inferred← citeshttps://doi.org/10.1007/978-3-642-39799-8_22openalex-snapshot
Beautiful Interpolants
inferred← citeshttps://doi.org/10.1007/978-3-642-76980-1_44openalex-snapshot
Algorithmisches Lernen auf der Basis empirischer Daten
inferred← citeshttps://doi.org/10.1007/bf01299449openalex-snapshot
Bilinear separation of two sets inn-space
inferred← citeshttps://doi.org/10.1007/s00291-007-0089-0openalex-snapshot
A LAD-based method for selecting short oligo probes for genotyping applications
inferred← citeshttps://doi.org/10.1007/s00500-021-05758-6openalex-snapshot
Polyhedral separation via difference of convex (DC) programming
inferred← citeshttps://doi.org/10.1007/s10107-005-0694-0openalex-snapshot
A constraint generation algorithm for large scale linear programs using multiple-points separation
inferred← citeshttps://doi.org/10.1007/s10107-021-01623-4openalex-snapshot
Complexity of linear relaxations in integer programming
inferred← citeshttps://doi.org/10.1007/s10107-021-01754-8openalex-snapshot
Computational aspects of relaxation complexity: possibilities and limitations
inferred← citeshttps://doi.org/10.1007/s10115-020-01533-5openalex-snapshot
Warped softmax regression for time series classification
inferred← citeshttps://doi.org/10.1007/s10851-017-0711-yopenalex-snapshot
About the Decidability of Polyhedral Separability in the Lattice $$\mathbb {Z}^d$$ Z d
inferred← citeshttps://doi.org/10.1007/s10957-013-0458-6openalex-snapshot
Support Vector Machine Polyhedral Separability in Semisupervised Learning
inferred← citeshttps://doi.org/10.1007/s10994-015-5505-0openalex-snapshot
Committee polyhedral separability: complexity and polynomial approximation
inferred← citeshttps://doi.org/10.1007/s10994-024-06596-xopenalex-snapshot
Nested barycentric coordinate system as an explicit feature map for polyhedra approximation and learning tasks
inferred← citeshttps://doi.org/10.1016/0166-218x(91)90011-kopenalex-snapshot
Approximation algorithms for hitting objects with straight lines
inferred← citeshttps://doi.org/10.1016/0262-8856(95)01046-7openalex-snapshot
Learning-based method to recognize and localize glassware using laser range images
inferred← citeshttps://doi.org/10.1016/0885-064x(90)90012-3openalex-snapshot
On learning a union of half spaces
inferred← citeshttps://doi.org/10.1016/0890-5401(88)90049-1openalex-snapshot
Minimum polygonal separation
inferred← citeshttps://doi.org/10.1016/0925-7721(95)00006-uopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-323-95502-7.00180-9openalex-snapshot
DC Optimization Models for Machine Learning
inferred← citeshttps://doi.org/10.1016/j.amc.2007.01.051openalex-snapshot
Data separation via a finite number of discriminant functions: A global optimization approach
inferred← citeshttps://doi.org/10.1016/j.amc.2007.03.067openalex-snapshot
Nonlinear separation of data via Mixed 0–1 Integer and Linear Programming
inferred← citeshttps://doi.org/10.1016/j.cie.2006.06.015openalex-snapshot
Pattern classification by concurrently determined piecewise linear and convex discriminant functions
inferred← citeshttps://doi.org/10.1016/j.cor.2012.05.015openalex-snapshot
Supervised classification and mathematical optimization
inferred← citeshttps://doi.org/10.1016/j.cviu.2021.103299openalex-snapshot
Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts
inferred← citeshttps://doi.org/10.1016/j.disopt.2020.100620openalex-snapshot
Complexity of training ReLU neural network
inferred← citeshttps://doi.org/10.1016/j.ejco.2023.100077openalex-snapshot
A classification method based on a cloud of spheres
inferred← citeshttps://doi.org/10.1016/j.ic.2021.104771openalex-snapshot
New cryptographic hardness for learning intersections of halfspaces over boolean cubes with membership queries
inferred← citeshttps://doi.org/10.1016/j.ipl.2023.106402openalex-snapshot
Monochromatic Partitioning of Colored Points by Lines
inferred← citeshttps://doi.org/10.1016/j.scico.2017.04.010openalex-snapshot
Verification of linear hybrid systems with large discrete state spaces using counterexample-guided abstraction refinement
inferred← citeshttps://doi.org/10.1016/j.swevo.2021.100896openalex-snapshot
Grammatical evolution for constraint synthesis for mixed-integer linear programming
inferred← citeshttps://doi.org/10.1016/j.tcs.2005.09.008openalex-snapshot
On approximate learning by multi-layered feedforward circuits
inferred← citeshttps://doi.org/10.1016/j.tcs.2005.11.026openalex-snapshot
Counterexample-guided predicate abstraction of hybrid systems
inferred← citeshttps://doi.org/10.1016/j.tcs.2022.03.025openalex-snapshot
A characterization of 2-threshold functions via pairs of prime segments
inferred← citeshttps://doi.org/10.1016/j.tcs.2024.114778openalex-snapshot
Finding the Largest Separating Rectangle Among Two Point Sets
inferred← citeshttps://doi.org/10.1016/s0304-3975(01)00057-3openalex-snapshot
Hardness results for neural network approximation problems
inferred← citeshttps://doi.org/10.1016/s0377-2217(97)00297-xopenalex-snapshot
Hybrid extreme point tabu search
inferred← citeshttps://doi.org/10.1016/s0747-7171(08)80067-3openalex-snapshot
On the complexity of some geometric problems in unbounded dimension
inferred← citeshttps://doi.org/10.1016/s0893-6080(05)80010-3openalex-snapshot
Training a 3-node neural network is NP-complete
inferred← citeshttps://doi.org/10.1016/s0925-7721(97)00006-0openalex-snapshot
On the complexity of optimization problems for 3-dimensional convex polyhedra and decision trees
inferred← citeshttps://doi.org/10.1023/a:1009744630224openalex-snapshot
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
inferred← citeshttps://doi.org/10.1023/a:1013649822153openalex-snapshot
Polyhedral Separability Through Successive LP
inferred← citeshttps://doi.org/10.1051/ro/2018036openalex-snapshot
Undecidability and hardness in mixed-integer nonlinear programming
inferred← citeshttps://doi.org/10.1063/1.4965316openalex-snapshot
Nonlinear programming for classification problems in machine learning
inferred← citeshttps://doi.org/10.1080/10543406.2017.1372770openalex-snapshot
Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification
inferred← citeshttps://doi.org/10.1080/10556780512331318254openalex-snapshot
Ellipsoidal separation for classification problems
inferred← citeshttps://doi.org/10.1080/10556780600723252openalex-snapshot
Separation via polyhedral conic functions
inferred← citeshttps://doi.org/10.1080/10556780802264071openalex-snapshot
Non-smoothness in classification problems
inferred← citeshttps://doi.org/10.1109/18.737520openalex-snapshot
On the infeasibility of training neural networks with small mean-squared error
inferred← citeshttps://doi.org/10.1109/31.108507openalex-snapshot
An information theoretic design and training algorithm for neural networks
inferred← citeshttps://doi.org/10.1109/34.297960openalex-snapshot
Learning separations by Boolean combinations of half-spaces
inferred← citeshttps://doi.org/10.1109/72.363468openalex-snapshot
Classification of linearly nonseparable patterns by linear threshold elements
inferred← citeshttps://doi.org/10.1109/72.471360openalex-snapshot
On the complexity of training neural networks with continuous activation functions
inferred← citeshttps://doi.org/10.1109/cloudtech49835.2020.9365906openalex-snapshot
Novel Convex Polyhedron Classifier for Sentiment Analysis
inferred← citeshttps://doi.org/10.1109/grc.2006.1635836openalex-snapshot
Transductive Support Vector Classification for RNA Related Biological Abstracts
inferred← citeshttps://doi.org/10.1109/icpr.1992.201850openalex-snapshot
Learning separations by Boolean combinations of half-spaces
inferred← citeshttps://doi.org/10.1109/idaacs.2007.4488417openalex-snapshot
Constructing Large Margin Polytope Classifiers with a Multiclass Classification Algorithm
inferred← citeshttps://doi.org/10.1109/isvd.2011.21openalex-snapshot
Minimizing the Number of Separating Circles for Two Sets of Points in the Plane
inferred← citeshttps://doi.org/10.1109/rndm48015.2019.8949084openalex-snapshot
Challenges in Stochastic Binary Systems
inferred← citeshttps://doi.org/10.1109/sfcs.1993.366856openalex-snapshot
Learning an intersection of k halfspaces over a uniform distribution
inferred← citeshttps://doi.org/10.1109/sfcs.1996.548495openalex-snapshot
Learning linear transformations
inferred← citeshttps://doi.org/10.1109/sfcs.1997.646139openalex-snapshot
A random sampling based algorithm for learning the intersection of half-spaces
inferred← citeshttps://doi.org/10.1109/tac.2013.2266952openalex-snapshot
Designing Optimal Deadlock Avoidance Policies for Sequential Resource Allocation Systems Through Classification Theory: Existence Results and Customized Algorithms
inferred← citeshttps://doi.org/10.1109/tit.2021.3134898openalex-snapshot
Learning Convex Polyhedra With Margin
inferred← citeshttps://doi.org/10.1134/s0005117910030136openalex-snapshot
Computational complexity of recognition learning procedures in the class of piecewise-linear committee decision rules
inferred← citeshttps://doi.org/10.1134/s0005117915100082openalex-snapshot
On the problem polyhedral separability: A numerical solution
inferred← citeshttps://doi.org/10.1134/s0081543808060102openalex-snapshot
Combinatorial optimization problems related to the committee polyhedral separability of finite sets
inferred← citeshttps://doi.org/10.1134/s0081543815050119openalex-snapshot
Lower bounds for the number of hyperplanes separating two finite sets of points
inferred← citeshttps://doi.org/10.1134/s1054661808020089openalex-snapshot
Computational and approximational complexity of combinatorial problems related to the committee polyhedral separability of finite sets
inferred← citeshttps://doi.org/10.1137/s009753979630814xopenalex-snapshot
On the Difficulty of Designing Good Classifiers
inferred← citeshttps://doi.org/10.1145/180139.181009openalex-snapshot
On a learnability question associated to neural networks with continuous activations (extended abstract)
inferred← citeshttps://doi.org/10.1145/1857914.1857916openalex-snapshot
A random-sampling-based algorithm for learning intersections of halfspaces
inferred← citeshttps://doi.org/10.1145/2656045.2656064openalex-snapshot
Precise piecewise affine models from input-output data
inferred← citeshttps://doi.org/10.1145/3632410.3632491openalex-snapshot
Union of Convex Separators (UCS)
inferred← citeshttps://doi.org/10.1145/76359.76371openalex-snapshot
Learnability and the Vapnik-Chervonenkis dimension
inferred← citeshttps://doi.org/10.1162/089976602760408035openalex-snapshot
Training a Single Sigmoidal Neuron Is Hard
inferred← citeshttps://doi.org/10.1201/9780849305696.ch14openalex-snapshot
Implementation of Logical Analysis of Data for Oligo Probe Selection
inferred← citeshttps://doi.org/10.15388/informatica.2009.247openalex-snapshot
Complexity and Approximability of Committee Polyhedral Separability of Sets in General Position
inferred← citeshttps://doi.org/10.1609/aaai.v37i6.25878openalex-snapshot
On the Complexity of PAC Learning in Hilbert Spaces
inferred← citeshttps://doi.org/10.20382/jocg.v10i1a7openalex-snapshot
On the Parameterized Complexity of Red-Blue Points Separation
inferred← citeshttps://doi.org/10.2172/10133402openalex-snapshot
N-learners problem: Learning Boolean combinations of halfspaces
inferred← citeshttps://doi.org/10.4230/lipics.itcs.2021.22openalex-snapshot
Tight Hardness Results for Training Depth-2 ReLU Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1107.1564openalex-snapshot
Polyceptron: A Polyhedral Learning Algorithm
inferred← citeshttps://doi.org/10.48550/arxiv.1706.03268openalex-snapshot
Maximum Area Rectangle Separating Red and Blue Points
inferred← citeshttps://doi.org/10.48550/arxiv.1711.09156openalex-snapshot
Warped-Linear Models for Time Series Classification
inferred← citeshttps://doi.org/10.48550/arxiv.1811.01885openalex-snapshot
Learning Two Layer Rectified Neural Networks in Polynomial Time
inferred← citeshttps://doi.org/10.48550/arxiv.2005.06046openalex-snapshot
Red-Blue Point Separation for Points on a Circle
inferred← citeshttps://doi.org/10.48550/arxiv.2010.12227openalex-snapshot
Geometric Separability using Orthogonal Objects
inferred← citeshttps://doi.org/10.48550/arxiv.2012.12846openalex-snapshot
Improved Algorithm for Computing the Maximum-volume Bichromatic Separating Box
inferred← citeshttps://doi.org/10.48550/arxiv.2102.09798openalex-snapshot
Training Neural Networks is ER-complete
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