On the public citation graph
Cost-Sensitive Learning of Classification Knowledge and Its Applications in Robotics
0 signed · 162 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf00114265openalex-snapshot
Knowledge Acquisition Via Incremental Conceptual Clustering
inferredcites →https://doi.org/10.1007/bf00114778openalex-snapshot
The use of background knowledge in decision tree induction
inferredcites →https://doi.org/10.1007/bf00116249openalex-snapshot
Chunking in Soar: The anatomy of a general learning mechanism
inferredcites →https://doi.org/10.1007/bf00116250openalex-snapshot
Explanation-based generalization: A unifying view
inferredcites →https://doi.org/10.1007/bf01530999openalex-snapshot
Incorporating statistical information into expert classification systems to reduce classification costs
inferredcites →https://doi.org/10.1016/0004-3702(82)90040-6openalex-snapshot
Generalization as search
inferredcites →https://doi.org/10.1016/0004-3702(88)90013-6openalex-snapshot
Defining operationality for explanation-based learning
inferredcites →https://doi.org/10.1016/0921-8890(91)90013-bopenalex-snapshot
A cost-sensitive machine learning method for the approach and recognize task
inferredcites →https://doi.org/10.1016/b978-0-934613-03-3.50040-4openalex-snapshot
Generalization as Search
inferredcites →https://doi.org/10.1016/b978-0-934613-64-4.50017-7openalex-snapshot
ID5: An Incremental ID3
inferredcites →https://doi.org/10.1016/b978-1-4832-1446-7.50034-0openalex-snapshot
Explanation-Based Generalization: A Unifying View
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50096-5openalex-snapshot
FOCUSED CONCEPT FORMATION
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50098-9openalex-snapshot
INCREMENTAL, INSTANCE-BASED LEARNING OF INDEPENDENT AND GRADED CONCEPT DESCRIPTIONS
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50099-0openalex-snapshot
Cost-Sensitive Concept Learning of Sensor Use in Approach and Recognition
inferredcites →https://doi.org/10.1016/s0364-0213(84)80005-1openalex-snapshot
EPAM-like models of recognition and learning
inferredcites →https://doi.org/10.1023/a:1022609710832openalex-snapshot
The Use of Background Knowledge in Decision Tree Induction
inferredcites →https://doi.org/10.1023/a:1022639103969openalex-snapshot
Chunking in Soar: The Anatomy of a General Learning Mechanism
inferredcites →https://doi.org/10.1023/a:1022691120807openalex-snapshot
Explanation-Based Generalization: A Unifying View
inferredcites →https://doi.org/10.1109/icpr.1990.118066openalex-snapshot
Minimum cost aspect classification: a module of a vision algorithm compiler
inferredcites →https://doi.org/10.1109/robot.1990.126276openalex-snapshot
Feature-utility measures for automatic vision programming
inferredcites →https://doi.org/10.1117/12.969905openalex-snapshot
Execution Monitoring for a Mobile Robot System
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/11564096_36openalex-snapshot
Simple Test Strategies for Cost-Sensitive Decision Trees
inferred← citeshttps://doi.org/10.1007/11564126_29openalex-snapshot
Hybrid Cost-Sensitive Decision Tree
inferred← citeshttps://doi.org/10.1007/3-540-49292-5_22openalex-snapshot
Boosting Cost-Sensitive Trees
inferred← citeshttps://doi.org/10.1007/3-540-61532-6_3openalex-snapshot
Cost-sensitive specialization
inferred← citeshttps://doi.org/10.1007/978-1-4613-0471-5_6openalex-snapshot
Active Learning for Vision-Based Robot Grasping
inferred← citeshttps://doi.org/10.1007/978-1-4615-5725-8_2openalex-snapshot
Feature Weighting for Lazy Learning Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-030-51186-9_19openalex-snapshot
A New Approach for Multi-agent Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/978-3-540-74958-5_52openalex-snapshot
Test-Cost Sensitive Classification Based on Conditioned Loss Functions
inferred← citeshttps://doi.org/10.1007/978-3-540-75175-5_47openalex-snapshot
Experiments on Classifiers Obtained Via Decision Tree Induction Methods with Different Attribute Acquisition Cost Limit
inferred← citeshttps://doi.org/10.1007/978-3-540-76719-0_44openalex-snapshot
Cost-Time Sensitive Decision Tree with Missing Values
inferred← citeshttps://doi.org/10.1007/978-3-642-15387-7_54openalex-snapshot
Test-Cost Sensitive Classification on Data with Missing Values in the Limited Time
inferred← citeshttps://doi.org/10.1007/978-3-642-16493-4_46openalex-snapshot
Test-Cost Sensitive Classification Using Greedy Algorithm on Training Data
inferred← citeshttps://doi.org/10.1007/978-3-642-17316-5_1openalex-snapshot
Cost Sensitive Classification in Data Mining
inferred← citeshttps://doi.org/10.1007/978-3-642-21222-2_30openalex-snapshot
Costs-Sensitive Classification in Multistage Classifier with Fuzzy Observations of Object Features
inferred← citeshttps://doi.org/10.1007/978-3-642-23154-4_27openalex-snapshot
Costs-Sensitive Classification in Two-Stage Binary Classifier
inferred← citeshttps://doi.org/10.1007/978-3-642-23199-5_5openalex-snapshot
ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves
inferred← citeshttps://doi.org/10.1007/978-3-642-25853-4_19openalex-snapshot
Cost-Sensitive Decision Tree for Uncertain Data
inferred← citeshttps://doi.org/10.1007/978-3-642-27660-6_51openalex-snapshot
Cost-Sensitive Classification with Unconstrained Influence Diagrams
inferred← citeshttps://doi.org/10.1007/978-3-642-28487-8_40openalex-snapshot
Comparison of Cost for Zero-One and Stage-Dependent Fuzzy Loss Function
inferred← citeshttps://doi.org/10.1007/978-3-642-29336-8_27openalex-snapshot
Cost-Sensitive Detection of Malicious Applications in Mobile Devices
inferred← citeshttps://doi.org/10.1007/978-3-642-31900-6_45openalex-snapshot
A Competition Strategy to Cost-Sensitive Decision Trees
inferred← citeshttps://doi.org/10.1007/bf00117446openalex-snapshot
Active learning for vision-based robot grasping
inferred← citeshttps://doi.org/10.1007/s00170-026-18657-7openalex-snapshot
Critical samples focusing based intelligent optimization of shear thickening polishing process
inferred← citeshttps://doi.org/10.1007/s00500-018-3244-4openalex-snapshot
Bayesian inference by reversible jump MCMC for clustering based on finite generalized inverted Dirichlet mixtures
inferred← citeshttps://doi.org/10.1007/s00521-015-1896-xopenalex-snapshot
Online classifier adaptation for cost-sensitive learning
inferred← citeshttps://doi.org/10.1007/s10044-015-0503-1openalex-snapshot
Approaching the accuracy–cost conflict in embedded classification system design
inferred← citeshttps://doi.org/10.1007/s10458-019-09407-zopenalex-snapshot
Decomposition methods with deep corrections for reinforcement learning
inferred← citeshttps://doi.org/10.1007/s10514-021-09981-wopenalex-snapshot
A fully distributed multi-robot navigation method without pre-allocating target positions
inferred← citeshttps://doi.org/10.1007/s10726-006-9062-6openalex-snapshot
Partitioning for Profit: An Empirical Study of Methods for Handling Unequal Costs of Error in Predictive Data Mining
inferred← citeshttps://doi.org/10.1007/s10994-020-05874-8openalex-snapshot
Classification with costly features as a sequential decision-making problem
inferred← citeshttps://doi.org/10.1007/s10994-024-06565-4openalex-snapshot
Classification with costly features in hierarchical deep sets
inferred← citeshttps://doi.org/10.1016/b978-1-55860-335-6.50022-2openalex-snapshot
Rule Induction for Semantic Query Optimization
inferred← citeshttps://doi.org/10.1016/j.artint.2020.103400openalex-snapshot
Using POMDPs for learning cost sensitive decision trees
inferred← citeshttps://doi.org/10.1016/j.asoc.2020.106570openalex-snapshot
2-stage modified random forest model for credit risk assessment of P2P network lending to “Three Rurals” borrowers
inferred← citeshttps://doi.org/10.1016/j.dam.2007.05.060openalex-snapshot
Multi-group support vector machines with measurement costs: A biobjective approach
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.115902openalex-snapshot
Integration of aggressive bound tightening and Mixed Integer Programming for Cost-sensitive feature selection in medical diagnosis
inferred← citeshttps://doi.org/10.1016/j.ins.2008.11.032openalex-snapshot
Building a cost-constrained decision tree with multiple condition attributes
inferred← citeshttps://doi.org/10.1016/j.ins.2009.03.007openalex-snapshot
A hierarchical model for test-cost-sensitive decision systems
inferred← citeshttps://doi.org/10.1016/j.ins.2011.01.035openalex-snapshot
The CASH algorithm-cost-sensitive attribute selection using histograms
inferred← citeshttps://doi.org/10.1016/j.ins.2016.09.054openalex-snapshot
A cost sensitive decision tree algorithm based on weighted class distribution with batch deleting attribute mechanism
inferred← citeshttps://doi.org/10.1016/j.ins.2017.09.013openalex-snapshot
Cost-sensitive and hybrid-attribute measure multi-decision tree over imbalanced data sets
inferred← citeshttps://doi.org/10.1016/j.ins.2022.11.062openalex-snapshot
Multi-agent broad reinforcement learning for intelligent traffic light control
inferred← citeshttps://doi.org/10.1016/j.jss.2011.10.007openalex-snapshot
Decision tree classifiers sensitive to heterogeneous costs
inferred← citeshttps://doi.org/10.1016/j.knosys.2010.01.008openalex-snapshot
Cost-sensitive classification with respect to waiting cost
inferred← citeshttps://doi.org/10.1016/j.knosys.2015.10.008openalex-snapshot
Classification with test costs and background knowledge
inferred← citeshttps://doi.org/10.1016/j.knosys.2020.106145openalex-snapshot
A mixed integer linear programming support vector machine for cost-effective feature selection
inferred← citeshttps://doi.org/10.1016/j.neucom.2008.01.021openalex-snapshot
Highlighting heterogeneous samples to support vector machines’ training
inferred← citeshttps://doi.org/10.1016/j.patrec.2010.05.028openalex-snapshot
Qualitative test-cost sensitive classification
inferred← citeshttps://doi.org/10.1016/j.patrec.2016.06.018openalex-snapshot
Beyond accuracy: Learning selective Bayesian classifiers with minimal test cost
inferred← citeshttps://doi.org/10.1016/j.techfore.2026.124831openalex-snapshot
Credit risk management in peer-to-peer lending platforms: A systematic literature review
inferred← citeshttps://doi.org/10.1016/s0004-3702(03)00019-5openalex-snapshot
Possibilistic instance-based learning
inferred← citeshttps://doi.org/10.1016/s0950-7051(99)00019-2openalex-snapshot
On rule interestingness measures
inferred← citeshttps://doi.org/10.1023/a:1006593614256openalex-snapshot
A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms
inferred← citeshttps://doi.org/10.1023/a:1007432422702openalex-snapshot
Rapid Concept Learning for Mobile Robots
inferred← citeshttps://doi.org/10.1023/a:1008850021368openalex-snapshot
Rapid Concept Learning for Mobile Robots
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:1018280807006openalex-snapshot
Active Learning for Vision-Based Robot Grasping
inferred← citeshttps://doi.org/10.1093/comjnl/bxw015openalex-snapshot
A Cost-Sensitive Decision Tree Learning Algorithm Based on a Multi-Armed Bandit Framework
inferred← citeshttps://doi.org/10.1109/69.929904openalex-snapshot
Debiasing training data for inductive expert system construction
inferred← citeshttps://doi.org/10.1109/access.2018.2876885openalex-snapshot
A Cross-Domain Recommendation Algorithm for D2D Multimedia Application Systems
inferred← citeshttps://doi.org/10.1109/cit.2008.workshops.51openalex-snapshot
A Strategy for Attributes Selection in Cost-Sensitive Decision Trees Induction
inferred← citeshttps://doi.org/10.1109/edocw.2009.5331975openalex-snapshot
Decision support oriented Enterprise Architecture metamodel management using classification trees
inferred← citeshttps://doi.org/10.1109/eit.2014.6871784openalex-snapshot
Decision tree classification algorithm based on cost and benefit dual-sensitive
inferred← citeshttps://doi.org/10.1109/gcis.2009.229openalex-snapshot
A Benefit-Cost Based Method for Cost-Sensitive Decision Trees
inferred← citeshttps://doi.org/10.1109/icaica50127.2020.9182532openalex-snapshot
The modeling and verification of DSDM in airport taxi
inferred← citeshttps://doi.org/10.1109/icca.2003.1595102openalex-snapshot
A Foundation for Robot Learning
inferred← citeshttps://doi.org/10.1109/iccv.2013.31openalex-snapshot
Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees
inferred← citeshttps://doi.org/10.1109/icdm.2004.10042openalex-snapshot
A Biobjective Model to Select Features with Good Classification Quality and Low Cost
inferred← citeshttps://doi.org/10.1109/icdm.2004.10092openalex-snapshot
Test-Cost Sensitive Naive Bayes Classification
inferred← citeshttps://doi.org/10.1109/icdm.2004.10108openalex-snapshot
Cost-Guided Class Noise Handling for Effective Cost-Sensitive Learning
inferred← citeshttps://doi.org/10.1109/icdm.2005.74openalex-snapshot
Handling Generalized Cost Functions in the Partitioning Optimization Problem through Sequential Binary Programming
inferred← citeshttps://doi.org/10.1109/icdm.2012.116openalex-snapshot
Cost-Sensitive Online Classification
inferred← citeshttps://doi.org/10.1109/icdm.2015.51openalex-snapshot
Cost-Sensitive Online Classification with Adaptive Regularization and Its Applications
inferred← citeshttps://doi.org/10.1109/icmlc.2015.7340890openalex-snapshot
Parameter learning using ant colony optimization for minimal time cost reduction
inferred← citeshttps://doi.org/10.1109/icmlc.2015.7340902openalex-snapshot
Cost-sensitive decision tree with probabilistic pruning mechanism
inferred← citeshttps://doi.org/10.1109/icsmc.1994.399821openalex-snapshot
Generating natural-language like robot motion command set through machine learning
inferred← citeshttps://doi.org/10.1109/iros55552.2023.10341423openalex-snapshot
A Generic Framework for Byzantine-Tolerant Consensus Achievement in Robot Swarms
inferred← citeshttps://doi.org/10.1109/jcai.2009.118openalex-snapshot
Cost-sensitive Decision Tree with Missing Values and Multiple Cost Scales
inferred← citeshttps://doi.org/10.1109/malware.2015.7413684openalex-snapshot
Automatically combining static malware detection techniques
inferred← citeshttps://doi.org/10.1109/robot.1996.503568openalex-snapshot
Interactive task planning through natural language
inferred← citeshttps://doi.org/10.1109/taai51410.2020.00028openalex-snapshot
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation
inferred← citeshttps://doi.org/10.1109/tbme.2021.3113593openalex-snapshot
CAFS: Cost-Aware Features Selection Method for Multimodal Stress Monitoring on Wearable Devices
inferred← citeshttps://doi.org/10.1109/tkde.2002.1000348openalex-snapshot
An instance-weighting method to induce cost-sensitive trees
inferred← citeshttps://doi.org/10.1109/tkde.2005.176openalex-snapshot
Cost-constrained data acquisition for intelligent data preparation
inferred← citeshttps://doi.org/10.1109/tkde.2005.188openalex-snapshot
"Missing is useful": missing values in cost-sensitive decision trees
inferred← citeshttps://doi.org/10.1109/tkde.2006.131openalex-snapshot
Test strategies for cost-sensitive decision trees
inferred← citeshttps://doi.org/10.1109/tkde.2006.155openalex-snapshot
Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering
inferred← citeshttps://doi.org/10.1109/tkde.2006.84openalex-snapshot
Test-cost sensitive classification on data with missing values
inferred← citeshttps://doi.org/10.1109/tkde.2013.157openalex-snapshot
Cost-Sensitive Online Classification
inferred← citeshttps://doi.org/10.1109/tkde.2017.2778097openalex-snapshot
Second-Order Online Active Learning and Its Applications
inferred← citeshttps://doi.org/10.1109/tsmcc.2011.2157494openalex-snapshot
A Survey of Evolutionary Algorithms for Decision-Tree Induction
inferred← citeshttps://doi.org/10.1109/wf-iot.2018.8355116openalex-snapshot
Extending the battery lifetime of wearable sensors with embedded machine learning
inferred← citeshttps://doi.org/10.1109/yac66630.2025.11150007openalex-snapshot
A cost-sensitive statistical fault detection method based on correlation analysis
inferred← citeshttps://doi.org/10.1111/j.1468-0394.2005.00311.xopenalex-snapshot
Inducing safer oblique trees without costs
inferred← citeshttps://doi.org/10.1111/j.1468-0394.2010.00515.xopenalex-snapshot
Cost‐sensitive methods of constructing hierarchical classifiers
inferred← citeshttps://doi.org/10.1111/j.1468-0394.2010.00573.xopenalex-snapshot
An empirical comparison of cost‐sensitive decision tree induction algorithms
inferred← citeshttps://doi.org/10.1137/1.9781611972832.23openalex-snapshot
Cost-Sensitive Double Updating Online Learning and Its Application to Online Anomaly Detection
inferred← citeshttps://doi.org/10.1142/s1469026812500113openalex-snapshot
A GENETIC PROGRAMMING-BASED LEARNING ALGORITHMS FOR PRUNING COST-SENSITIVE CLASSIFIERS
inferred← citeshttps://doi.org/10.1145/1015330.1015369openalex-snapshot
Decision trees with minimal costs
inferred← citeshttps://doi.org/10.1145/1143844.1143946openalex-snapshot
Feature value acquisition in testing
inferred← citeshttps://doi.org/10.1145/1247480.1247551openalex-snapshot
Addressing diverse user preferences in SQL-query-result navigation
inferred← citeshttps://doi.org/10.1145/1322263.1322285openalex-snapshot
A framework for the automated generation of power-efficient classifiers for embedded sensor nodes
inferred← citeshttps://doi.org/10.1145/2339530.2339555openalex-snapshot
A simple methodology for soft cost-sensitive classification
inferred← citeshttps://doi.org/10.1145/2431211.2431215openalex-snapshot
A survey of cost-sensitive decision tree induction algorithms
inferred← citeshttps://doi.org/10.1145/3506734openalex-snapshot
Constraint Enforcement on Decision Trees: A Survey
inferred← citeshttps://doi.org/10.1155/2013/754698openalex-snapshot
Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors
inferred← citeshttps://doi.org/10.1186/s12859-020-3361-9openalex-snapshot
Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms
inferred← citeshttps://doi.org/10.12733/jics20101547openalex-snapshot
Data-driven Decision Tree Learning Algorithm Based on Data Relativity
inferred← citeshttps://doi.org/10.12733/jics20102163openalex-snapshot
A Backtracking Approach to Minimal Cost Feature Selection of Numerical Data
inferred← citeshttps://doi.org/10.12733/jics20105758openalex-snapshot
A Heuristic Algorithm to Attribute Reduction with Simple Common-cost
inferred← citeshttps://doi.org/10.1287/isre.11.2.137.11777openalex-snapshot
Mean-Risk Trade-Offs in Inductive Expert Systems
inferred← citeshttps://doi.org/10.1371/journal.pone.0197564openalex-snapshot
Rough sets and Laplacian score based cost-sensitive feature selection
inferred← citeshttps://doi.org/10.1609/aaai.v32i1.11779openalex-snapshot
MDP-Based Cost Sensitive Classification Using Decision Trees
inferred← citeshttps://doi.org/10.1609/aaai.v33i01.33013959openalex-snapshot
Classification with Costly Features Using Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1613/jair.120openalex-snapshot
Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm
inferred← citeshttps://doi.org/10.31274/rtd-180813-17070openalex-snapshot
A new approach of top-down induction of decision trees for knowledge discovery
inferred← citeshttps://doi.org/10.3156/jsoft.17.279openalex-snapshot
Interaction Design for Adaptation
inferred← citeshttps://doi.org/10.3182/20110828-6-it-1002.02522openalex-snapshot
Lower-bound Estimate for Cost-sensitive Decision Trees*
inferred← citeshttps://doi.org/10.3389/fenrg.2021.686616openalex-snapshot
Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators
inferred← citeshttps://doi.org/10.4304/jcp.9.8.1897-1903openalex-snapshot
Cost-sensitive Naïve Bayes Classification of Uncertain Data
inferred← citeshttps://doi.org/10.48550/arxiv.1211.2512openalex-snapshot
Minimal cost feature selection of data with normal distribution measurement errors
inferred← citeshttps://doi.org/10.48550/arxiv.1211.4122openalex-snapshot
Cost-sensitive C4.5 with post-pruning and competition
inferred← citeshttps://doi.org/10.48550/arxiv.1212.3185openalex-snapshot
Cost-Sensitive Feature Selection of Data with Errors
inferred← citeshttps://doi.org/10.48550/arxiv.1511.09337openalex-snapshot
Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1707.00536openalex-snapshot
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
inferred← citeshttps://doi.org/10.48550/arxiv.1710.09515openalex-snapshot
Soft Methodology for Cost-and-error Sensitive Classification
inferred← citeshttps://doi.org/10.48550/arxiv.2008.06298openalex-snapshot
Feature Selection Methods for Cost-Constrained Classification in Random Forests
inferred← citeshttps://doi.org/10.48550/arxiv.cs/0212034openalex-snapshot
Types of Cost in Inductive Concept Learning
inferred← citeshttps://doi.org/10.48550/arxiv.cs/0212039openalex-snapshot
Low Size-Complexity Inductive Logic Programming: The East-West Challenge Considered as a Problem in Cost-Sensitive Classification
inferred← citeshttps://doi.org/10.5555/3234847.3234868openalex-snapshot
On-Board Feature Extraction from Acceleration Data for Activity Recognition
inferred← citeshttps://doi.org/10.82465/6615openalex-snapshot
A Study of Cost-sensitive Attribute Reducts
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.