yusuke1997/dblp-id-title huggingface dataset:
BMWk Revisited - Generalization and Formalization of an Algorithm for Detecting Recursive Relations in Term Sequences
Extending Learning to Multiple Agents: Issues and a Model for Multi-Agent Machine Learning (MA-ML)
A Robust Boosting Algorithm
Induction of Recursive Bayesian Classifiers
Iteratively Extending Time Horizon Reinforcement Learning
Induction in Noisy Domains
Improving the Robustness and Encoding Complexity of Behavioural Clones
Complexity of Computing Generalized VC-Dimensions
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner
Using Subclasses to Improve Classification Learning
Inducing Models of human Control Skills
Classification Approach towards Banking and Sorting Problems
Robustness Analyses of Instance-Based Collaborative Recommendation
Predicate Invention and Learning from Positive Examples Only
COllective INtelligence with Sequences of Actions - Coordinating Actions in Multi-agent Systems
Using Plausible Explanations to Bias Empirical Generalizations in Weak Theory Domains
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences
Using Constraints to Building Version Spaces
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling
Lazy Induction of Descriptions for Relational Case-Based Learning
Boosting Density Function Estimators
Justification-Based Selection of Training Examples for Case Base Reduction
Rotational Prior Knowledge for SVMs
An Analogical Method to do Incremental Learning of Concepts
FOSSIL: A Robust Relational Learner
Learning Different Types of New Attributes by Combining the Neural Network and Iterative Attribute Construction
A Comparitive Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems
Counting Positives Accurately Despite Inaccurate Classification
Multi-view Discriminative Sequential Learning
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
Interpretable Neural Networks with BP-SOM
Reasoning and Learning in Probabilistic and Possibilistic Networks: An Overview
Population Diversity in Permutation-Based Genetic Algorithm
Learning to Control Dynamic Systems with Automatic Quantization
Fisher Kernels for Relational Data
Learning of Qualitative Models
Weighted Kernel Regression for Predicting Changing Dependencies
Using Semantic Distance in a Content-Based Heterogeneous Information Retrieval System
Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)
Efficient Case Based Feature Construction
First Connectomics Challenge: From Imaging to Connectivity
Learning to Complete Sentences
Case-Based Learning: Beyond Classification of Feature Vectors
Machine Learning in the Next Five Years
Coevolutionary, Distributed Search for Inducing Concept Description
Multi-objective Classification with Info-Fuzzy Networks
SAMIA: A Bottom-Up Learning Method Using a Simulated Annealing Algorithm
Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games
Seed Space and Version Space: Generalizing from Approximations
Beyond Occam's Razor: Process-Oriented Evaluation
Learning What People (Don't) Want
Model Driven Learning of Disjunctive Concepts
Comparing Instance-Averaging with Instance-Filtering Learning Algorithms
An Overview of Evolutionary Computation
Using Hard Classifiers to Estimate Conditional Class Probabilities
Learning through Progressive Refinement
Goal Regression with Opponent
Active Learning with Irrelevant Examples
Optimizing Feature Sets for Structured Data
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
An Unsupervised Learning Algorithm for Rank Aggregation
A Short Note About the Application of Polynomial Kernels with Fractional Degree in Support Vector Learning
The Utilization of Context Signals in the Analysis of ABR Potentials by Application of Neural Networks
Extraction of Knowledge from Data Using Constrained Neural Networks
Metric-Based Inductive Learning Using Semantic Height Functions
Inverting Implication with Small Training Sets
To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles
Importance Sampling Techniques in Neural Detector Training
Constant Rate Approximate Maximum Margin Algorithms
Stability Based Sparse LSI/PCA: Incorporating Feature Selection in LSI and PCA
Empirical Learning of Natural Language Processing Task
Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies
Learning to Order: A Relational Approach
Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers
Safe Q-Learning on Complete History Spaces
Knowledge Discovery from Very Large Databases Using Frequent Concept Lattices
A Comparison of Ranking Methods for Classification Algorithm Selection
Learning Process Models with Missing Data
Dual Strategy Active Learning
Induction of Qualitative Trees
Averaging Over Decision Stumps
Wrapping Web Information Providers by Transducer Induction
KBG: A Generator of Knowledge Bases
An Empirical Study of MetaCost Using Boosting Algorithms
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
Extraction of Recurrent Patterns from Stratified Ordered Trees
IPSA: Inductive Protein Structure Analysis
Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning
Inductive Genetic Programming with Decision Trees
Multi-objective Genetic Programming for Multiple Instance Learning
Panel: Evaluating and Changing Representation in Concept Acquisition
Exploiting Extremely Rare Features in Text Categorization
Concept Formation in Expressive Description Logics
Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption Test
Message-Based Bucket Brigade: An Algorithm for the Apportionment of Credit Problem
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes
Complexity Dimensions and Learnability
Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining
Biases and Their Effects in Inductive Logic Programming
Natural Actor-Critic
Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem
Panel: Causality and Learning
Refinement of Rule Sets with JoJo
Reinforcement Learning for MDPs with Constraints
Combinatorial Markov Random Fields
A Multistrategy Learning Approach to Domain Modeling and Knowledge Acquisition
TildeCRF: Conditional Random Fields for Logical Sequences
Multiclass Alternating Decision Trees
Additive Groves of Regression Trees
Improving the Ranking Performance of Decision Trees
Learning Balls of Strings with Correction Queries
FENDER: An Approach to Theory Restructuring (Extended Abstract)
Using Diversity in Preparing Ensembles of Classifiers Based on Different Feature Subsets to Minimize Generalization Error
A Case Study in Loyality and Satisfaction Research
Efficient Hyperkernel Learning Using Second-Order Cone Programming
Comparing Rule Measures for Predictive Association Rules
Discovery of Constraints and Data Dependencies in Databases (Extended Abstract)
Panel: Applications of Machine Learning: Notes from the Panel Members
Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction
Text Categorization Using Transductive Boosting
Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures
Margin-Based Active Learning for Structured Output Spaces
On the Boosting Pruning Problem
COBBIT - A Control Procedure for COBWEB in the Presence of Concept Drift
A Multiple Model Cost-Sensitive Approach for Intrusion Detection
Learning Disjunctive Normal Forms in a Dual Classifier System (Extended Abstract)
Constructive Induction for Classifying Time Series
On Changing Continuous Attributes into Ordered Discrete Attributes
Statistical Debugging Using Latent Topic Models
Revising Engineering Models: Combining Computational Discovery with Knowledge
Phase Transitions and Stochastic Local Search in k-Term DNF Learning
Model-Based Online Learning of POMDPs
A Study on the Performance of Large Bayes Classifier
Planning and Learning in Environments with Delayed Feedback
Machine Learning: ECML-94, European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, Proceedings
First-Order Learning for Web Mining
Bayesian and Information-Theories Priors for Bayesian Network Parameters
Learning and Exploitation Do Not Conflict Under Minimax Optimality
Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning
Towards 'Interactive' Active Learning in Multi-view Feature Sets for Information Extraction
Sample PAC-Learnability in Model Inference
A Multistrategy Approach to the Classification of Phases in Business Cycles
Analysis of Rachmaninoff's Piano Performances Using Inductive Logic Programming (Extended Abstract)
Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection
K -Means with Large and Noisy Constraint Sets
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
Support Vector Machines with Example Dependent Costs
Error-Correcting Output Codes for Local Learners
An Efficient Approximation to Lookahead in Relational Learners
IDDD: An Inductive, Domain Dependent Decision Algorithm
Estimating Attributed Central Orders: An Empirical Comparison
EM Algorithm for Symmetric Causal Independence Models
Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data
Proceedings of the 4th European Working Session on Learning, Montpellier, France, 4-6 December 1989
Adaptive Online Time Allocation to Search Algorithms
Characterizing Markov Decision Processes
Infinite Ensemble Learning with Support Vector Machines
Representing Arguments as Background Knowledge for Constraining Gereralisation
Learning Patterns of Behavior by Observing System Events
Clustering and Metaclustering with Nonnegative Matrix Decompositions
A Study of Generalisation in Logic Programs
Learning and Inference for Clause Identification
Generating Neural Networks Through the Induction of Threshold Logic Unit Trees (Extended Abstract)
A Kernel Between Unordered Sets of Data: The Gaussian Mixture Approach
Learning from Relevant Tasks Only
Bayesian Learning with Mixtures of Trees
General Solution for Supervised Graph Embedding
A Host-Parasite Genetic Algorithm for Asymmetric Tasks
Using Machine Learning Techniques to Interpret Results from Discrete Event Simulation
Skill Acquisition Via Transfer Learning and Advice Taking
Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning
Batch Classification with Discrete Finite Mixtures
Speeding up Q(lambda)-Learning
Learning Verbal Transitivity Using LogLinear Models
Applying the Bayesian Evidence Framework to \nu -Support Vector Regression
PAC-Learning of Markov Models with Hidden State
An Integrated Approach to Learning Bayesian Networks of Rules
Spectral Clustering and Embedding with Hidden Markov Models
Toward an Ecplanatory Similarity Measure for Nearest-Neighbor Classification
Machine Learning: ECML 2002, 13th European Conference on Machine Learning, Helsinki, Finland, August 19-23, 2002, Proceedings
The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces
Bibliographical Notes
Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data
Recursive Lazy Learning for Modeling and Control
Induction of Recursive Program Schemes
Convergence Rate of Minimization Learning for Neural Networks
Metrics on Terms and Clauses
A New Way to Introduce Knowledge into Reinforcement Learning
Ibots Learn Genuine Team Solutions
Bayesian Active Learning for Sensitivity Analysis
Abstract Computer Models: Towards a New Method for Theorizing About Adaptive Agents
ARAS: Action Rules Discovery Based on Agglomerative Strategy
Bayesian Inference for Sparse Generalized Linear Models
Using Lattice-Based Framework as a Tool for Feature Extraction
Learning by Explanation of Failures
Concept Sublattices
DQL: A New Updating Strategy for Reinforcement Learning Based on Q-Learning
Efficient Inference in Large Conditional Random Fields
Revisiting Fisher Kernels for Document Similarities
Composing Functions to Speed up Reinforcement Learning in a Changing World
Some Lower Bounds for the Computational Complexity of Inductive Logic Programming
Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modelling
Hybrid Algorithms with Instance-Based Classification
Economic Induction: A Case Study
Convergent Gradient Ascent in General-Sum Games
Bottom-Up Induction of Oblivious Read-Once Decision Graphs
A Mixture Approach to Novelty Detection Using Training Data with Outliers
Global Data Analysis and the Fragmentation Problem in Decision Tree Induction
Offspring-annotated probabilistic context-free grammars
Classifier Loss Under Metric Uncertainty
Inference of a Subclass of Context Free Grammars Using Positive Samples
Pairwise Preference Learning and Ranking
Stacking with an Extended Set of Meta-level Attributes and MLR
An Application of Machine Learning in the Domain of Loan Analysis
Discovering Dynamics with Genetic Programming
Machine Learning in the World Wide Web
Inference of Finite Automata: Reducing the Search Space with an Ordering of Pairs of States
Continuous Mimetic Evolution
Roulette Sampling for Cost-Sensitive Learning
Learning Classification with Both Labeled and Unlabeled Data
Efficient Pairwise Classification
Logistic Model Trees
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Rule Induction with CN2: Some Recent Improvements
Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31 - June 2, 2000, Proceedings
Automated Knowledge Acquisition for PROSPECTOR-like Expert Systems
Color Image Segmentation: Kernel Do the Feature Space
Naive Bayesian Classifier Committees
Machine Learning: ECML-93, European Conference on Machine Learning, Vienna, Austria, April 5-7, 1993, Proceedings
Classification Learning Using All Rules
A Strategy for Constructing New Predicates in First-Order Logic
Random k -Labelsets: An Ensemble Method for Multilabel Classification
Improving Example-Guided Unfolding
Panel: Application of Empirical Discovery in Knowledge Acquisition
Bagging Using Statistical Queries
Scale-Space Based Weak Regressors for Boosting
Nonrigid Embeddings for Dimensionality Reduction
A Model for Generalization Based on Confirmatory Induction
Document Representation for One-Class SVM
Learnability in the Presence of Noise
Pruning Multivariate Decision Trees by Hyperplane Merging
Inducing Head-Driven PCFGs with Latent Heads: Refining a Tree-Bank Grammar for Parsing
Inductive Generalization: A Logical Framework
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
Modeling Highway Traffic Volumes
Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees
Understanding Probabilistic Classifiers
A Hybrid Nearest-Neighbor and Nearest-Hyperrectangle Algorithm
Analyzing Co-training Style Algorithms
Explanation-Based Generalization and Constraint Propagation with Interval Labels
An Optimal Best-First Search Algorithm for Solving Infinite Horizon DEC-POMDPs
Exploiting Context When Learning to Classify
Abduction and Induction for Explanation-Based Learning
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
Specialization of Recursive Predicates
Classification of Ordinal Data Using Neural Networks
Multimodal Function Optimizing by a New Hybrid Nonlinear Simplex Search and Particle Swarm Algorithm
Learning When to Collaborate among Learning Agents
Integrated Learning and Planning Based on Truncating Temporal Differences
Estimating Attributes: Analysis and Extensions of RELIEF
Efficient Prediction-Based Validation for Document Clustering
Building Committees by Clustering Models Based on Pairwise Similarity Values
Improving Rocchio with Weakly Supervised Clustering
ML Techniques and Text Analysis
The Power of Decision Tables
Feature Selection Using Rough Sets Theory
On Testing the Missing at Random Assumption
Learning by Failure to Prove
Decision Tree Instability and Active Learning
ECML/PKDD Workshop on Meta-Knowledge Transfer, 23 September 2022, Grenoble, France
Inductive Learning of Characteristic Concept Description from Small Sets of Classified Examples
Analogical Reasoning for Logic Programming
Classification on Data with Biased Class Distribution
A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes
An Adaptive Kernel Method for Semi-supervised Clustering
RIONA: A Classifier Combining Rule Induction and k-NN Method with Automated Selection of Optimal Neighbourhood
Mining TCP/IP Traffic for Network Intrusion Detection by Using a Distributed Genetic Algorithm
Unsupervised Grammar Induction in a Framework of Information Compression by Multiple Alignment, Unification and Search
Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions
Boosting Applied toe Word Sense Disambiguation
Model Selection in Omnivariate Decision Trees
Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators
Some Improvements on Event-Sequence Temporal Region Methods
Learning Trading Rules with Inductive Logic Programming
Problem Solvers that Learn
An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk
Left Aligned Grammars - Identifying a class of Context-free Grammar in the limit from Positive Data
Layered Learning
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery
Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language
Concept Formation in Complex Domains
A Simple Approach to Ordinal Classification
Simultaneous Concept Learning of Fuzzy Rules
The Piecewise Linear Classifier DIPOL92
Effcient combination of pairwise feature networks
A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses
Multiple-Knowledge Representation in Concept Learning
A Guided Tour Through Hypothesis Spaces in ILP
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
An Inductive Logic Programming Framework to Learn a Concept from Ambiguous Examples
Fitting the Smallest Enclosing Bregman Ball
Fast Non-negative Dimensionality Reduction for Protein Fold Recognition
Class Probability Estimation and Cost-Sensitive Classification Decisions
On the Proper Definition of Minimality in Specialization and Theory Revision
Discovering Strong Principles of Expressive Music Performance with the PLCG Rule Learning Strategy
Fast Spectral Clustering of Data Using Sequential Matrix Compression
Theoretical Results on Reinforcement Learning with Temporally Abstract Options
Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract
Boosting Trees for Cost-Sensitive Classifications
Abstracting Background Knowledge for Concept Learning
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions
A Simple Lexicographic Ranker and Probability Estimator
Mixtures of Kikuchi Approximations
REFINER: A Case-Based Differential Diagnosis Aide for Knowledge Acquisition and Knowledge Refinement
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Learning from Recursive, Tree Structured Examples
Using String Kernels to Identify Famous Performers from Their Playing Style
Cascade Evaluation of Clustering Algorithms
A Minimization Approach to Propositional Inductive Learning
Predicate Invention in ILP - an Overview
Counter-Example Generation-Based One-Class Classification
Self-evaluated Learning Agent in Multiple State Games
Prototype, Nearest Neighbor and Hybrid Algorithms for Time Series Classification (Extended Abstract)
Decision-Tree Based Neural Network (Extended Abstract)
Experiments with Cost-Sensitive Feature Evaluation
POM Centric Multi-aspect Data Analysis for Investigating Human Problem Solving Function
A Normalization Method for Contextual Data: Experience from a Large-Scale Application
On Concept Space and Hypothesis Space in Case-Based Learning Algorithms
Kernel-Based Grouping of Histogram Data
A Discriminative Approach for the Retrieval of Images from Text Queries
Properties of Inductive Logic Programming in Function-Free Horn Logic
Contextual Adaptive Clustering of Web and Text Documents with Personalization
A Markov Network Based Factorized Distribution Algorithm for Optimization
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
Machine Learning of Plan Robustness Knowledge About Instances
Simulating Children Learning and Explaining Elementary Heat Transfer Phenomena: A Multistrategy System at Work
Nonparametric Regularization of Decision Trees
Human-Agent Interaction and Machine Learning
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Transductive Gaussian Process Regression with Automatic Model Selection
Model Approximation for HEXQ Hierarchical Reinforcement Learning
Pairwise Classification as an Ensemble Technique
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search
Analytical Negative Generalization and Empirical Negative Generalization are not Cumulative: A Case Study
Patching Proofs for Reuse (Extended Abstract)
Finite-Element Methods with Local Triangulation Refinement for Continuous Reimforcement Learning Problems
Patching Approximate Solutions in Reinforcement Learning
Induction of Feature Terms With INDIE
Evaluating Accuracies of a Trading Rule Mining Method Based on Temporal Pattern Extraction
Inducing Hidden Markov Models to Model Long-Term Dependencies
Predicate Invention in Inductive Data Engineering
Dynamic Integration with Random Forests
iBoost: Boosting Using an i nstance-Based Exponential Weighting Scheme
Integrated Learning Architectures
Static Learning for an Adaptive Theorem Prover
A Note on Refinement Operators
The Incremental Analogy Machine: A Computational Model of Analogy
Cluster-Grouping: From Subgroup Discovery to Clustering
Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference
Experiments in Value Function Approximation with Sparse Support Vector Regression
An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes
Associative Clustering
Severe Class Imbalance: Why Better Algorithms Aren't the Answer
Improving Numerical Prediction with Qualitative Constraints
Class Noise Mitigation Through Instance Weighting
Similarity-Based Alignment and Generalization
Collaborative Learning of Term-Based Concepts for Automatic Query Expansion
Multiple-Instance Learning Via Random Walk
Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings
Adapting to Drift in Continuous Domains (Extended Abstract)
Nondeterministic Discretization of Weights Improves Accuracy of Neural Networks
Cost-Sensitive Learning of SVM for Ranking
A Context Similarity Measure
A Monotonic Measure for Optimal Feature Selection
Decision Tree Pruning as a Search in the State Space
On Applying Tabling to Inductive Logic Programming
Support Vector Machines for Polycategorical Classification
Learning to Play a Highly Complex Game from Human Expert Games
Language Series Revisited: The Complexity of Hypothesis Spaces in ILP (Extended Abstract)
The Effect of Numeric Features on the Scalability of Inductive Learning Programs
Ensemble Learning with Supervised Kernels
A Clustering Model Based on Matrix Approximation with Applications to Cluster System Log Files
Error Analysis of Automatic Speech Recognition Using Principal Direction Divisive Partitioning
Supervised Neural Network Structure Recovery
Combining Classifiers by Constructive Induction
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
Explanation-Based Generalization in Game Playing: Quantitative Results
Batch Classification with Applications in Computer Aided Diagnosis
On Estimating Probabilities in Tree Pruning