yusuke1997/dblp-id-title huggingface dataset:
Classification with Maximum Entropy Modeling of Predictive Association Rules
Case-Based Label Ranking
Data Mining of Multi-categorized Data
Life Cycle Modeling of News Events Using Aging Theory
Improving Knowledge-Based System Performance by Experience
Constructing Intermediate Concepts by Decomposition of Real Functions
On Interactive Concept-Learning and Assimilation
Independent Subspace Analysis on Innovations
Semi-supervised Collaborative Text Classification
Improving Boosting by Exploiting Former Assumptions
Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures
Test-Cost Sensitive Classification Based on Conditioned Loss Functions
Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract)
Annealed Discriminant Analysis
Description Contrasting in Incremental Concept Formation
Existence and Nonexistence of Complete Refinement Operators
The Effects of Noise on Efficient Incremental Induction (Extended Abstract)
ILP Experiments in Detecting Traffic Problems
Exploiting Unlabeled Data in Content-Based Image Retrieval
Cost-Sensitive Pruning of Decision Trees
The Role of Prototypicality in Exemplar-Based Learning
Partially Isomorphic Generalization and Analogical Reasoning
Probabilistic Models for Action-Based Chinese Dependency Parsing
Evaluation of Learning Systems: An Artificial Data-Based Approach
Controlling Constructive Induction in CIPF: An MDL Approach
Applying Support Vector Machines to Imbalanced Datasets
Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization
Learning Classification Rules Using Lattices (Extended Abstract)
Efficient Large Scale Linear Programming Support Vector Machines
The Extension Matrix Approach to Attribute Based Learning
Knowledge Representation in Machine Learning
Learning Models of Relational Stochastic Processes
Discriminative Clustering: Optimal Contingency Tables by Learning Metrics
Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings
Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features
Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings
NeuroLinear: A System for Extracting Oblique Decision Rules from Neural Networks
An Iterative and Bottom-up Procedure for Proving-by-Example
An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks
A Framework for Learning Rules from Multiple Instance Data
Spline Embedding for Nonlinear Dimensionality Reduction
Hybrid Classification: Using Axis-Parallel and Oblique Subdivisions of the Attribute Space (Extended Abstract)
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example
Shrinkage Estimator for Bayesian Network Parameters
Knowledge States and Meta-Knowledge Maintenance
Funtional Inductive Logic Programming with Queries to the User
The Enron Corpus: A New Dataset for Email Classification Research
A Comparison of Approaches for Learning Probability Trees
Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence
Variance Optimized Bagging
Learning Linear Constraints in Inductive Logic Programming
Early Screening for Castric Cancer Using machine Learning Techniques
Stepwise Induction of Multi-target Model Trees
MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition
A Selective Sampling Strategy for Label Ranking
The Evaluation of Predictive Learners: Some Theoretical and Empirical Results
A Geometric Approach to Feature Selection
Simple Test Strategies for Cost-Sensitive Decision Trees
Learning in One-Shot Strategic Form Games
Subsumption and Refinement in Model Inference
Machine Learning: ECML-98, 10th European Conference on Machine Learning, Chemnitz, Germany, April 21-23, 1998, Proceedings
Source Separation with Gaussian Process Models
Improving SVM Text Classification Performance through Threshold Adjustment
Mining Complex Data, ECML/PKDD 2007 Third International Workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers
Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods
Learning an Outlier-Robust Kalman Filter
Social Agents Playing a Periodical Policy
Dynamic Discretization of Continuous Values from Time Series
An Analysis of Stopping and Filtering Criteria for Rule Learning
Learning Context-Free Grammars with a Simplicity Bias
Identifying Unrecognizable Regular Languages by Queries
Multi-armed Bandit Algorithms and Empirical Evaluation
Volume under the ROC Surface for Multi-class Problems
Learning to Classify Documents with Only a Small Positive Training Set
Active Class Selection
Advances in Metalearning: ECML/PKDD Workshop on Meta-Knowledge Transfer
Backpropagation in Decision Trees for Regression
Uncertain Learning Agents (Abstract)
Deconvolutive Clustering of Markov States
On Usefulness of Outlier Elimination in Classification Tasks: Extended Abstract
On Minimizing the Position Error in Label Ranking
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
Panel: Four Stances on Knowledge Acquisition and Machine Learning
Towards Finite-Sample Convergence of Direct Reinforcement Learning
Optimal Stopping and Constraints for Diffusion Models of Signals with Discontinuities
Learning by Analogical Replay in PRODIGY: First Results
Analogical Logic Program Synthesis from Examples
Approximating Gaussian Processes with H 2 -Matrices
Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability
A Buffering Strategy to Avoid Ordering Effects in Clustering
Prioritizing Point-Based POMDP Solvers
Efficiently Determining the Starting Sample Size for Progressive Sampling
Filtered Reinforcement Learning
Clustering in Knowledge Embedded Space
Learning Features by Experimentation in Chess
Learning Stochastic Tree Edit Distance
How to Make AdaBoost.M1 Work for Weak Base Classifiers by Changing Only One Line of the Code
Learning Belief Network Structure from Data Under Causal Insufficiency
Dynamic Feature Selection in Incremental Hierarchical Clustering
Ensembles of Multi-instance Learners
Clustering Trees with Instance Level Constraints
Sparse Online Greedy Support Vector Regression
Constraint Selection by Committee: An Ensemble Approach to Identifying Informative Constraints for Semi-supervised Clustering
Part-of-Speech Tagging Using Decision Trees
A Minimum Descriptipn Length Approach to Grammar Inference
Possibilistic Induction in Decision-Tree Learning
Diversified SVM Ensembles for Large Data Sets
On Phase Transitions in Learning Sparse Networks
Measuring Quality of Concept Descriptions
Hinge Rank Loss and the Area Under the ROC Curve
An Evolutionary Function Approximation Approach to Compute Prediction in XCSF
Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique
Learning Metrics Between Tree Structured Data: Application to Image Recognition
Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains
Classification with Support Hyperplanes
Is AI a Sub-Field of Computer Science - or is AI the Science of Explanations?
Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning
Minimax TD-Learning with Neural Nets in a Markov Game
Comparing the Bayes and Typicalness Frameworks
Search-Based Class Discretization
Acquiring Object-Knowledge for Learning Systems
Finding Composite Episodes
Right of Inference: Nearest Rectangle Learning Revisited
Pruning Decision Trees with Misclassification Costs
Industrial Applications of ML: Illustrations for the KAML Dilemma and the CBR Dream
JIGSAW: Puzzling together RUTH and SPECTRE (Extended Abstract)
Using Accuracy in Scientific Discovery
Improving Control-Knowledge Acquisition for Planning by Active Learning
Feature Selection Filters Based on the Permutation Test
Learning Problem-Solving Concepts by Reflecting on Problem Solving
Strategy Learning for Reasoning Agents
A Tight Integration of Pruning and Learning (Extended Abstract)
Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework
Training Support Vector Machines with Multiple Equality Constraints
Learning in Agent-Oriented Worlds (Abstract)
Learning (k, l)-Contextual Tree Languages for Information Extraction
God Doesn't Always Shave with Occam's Razor - Learning When and How to Prune
Flexible Integration of Multiple Learning Methods into a Problem Solving Architecture
Margin-Sparsity Trade-Off for the Set Covering Machine
Abalearn: A Risk-Sensitive Approach to Self-play Learning in Abalone
Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings
Multi-level Boundary Classification for Information Extraction
Active Learning in Partially Observable Markov Decision Processes
Faster Performance Estimation for NAS with Embedding Proximity Score
Problem Decomposition for Behavioural Cloning
Ensembles of Multi-Objective Decision Trees
A Machine Learning Approach to Workflow Management
An Information Geometric Perspective on Active Learning
Learning Domain Theories using Abstract Beckground Knowledge
Generalization-Based Similarity for Conceptual Clustering
FOIL: A Midterm Report
Learning to Solve Complex Tasks for Reactive Systems (Extended Abstract)
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Combining Cross-Validation and Search
Learning While Exploring: Bridging the Gaps in the Eligibility Traces
A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems
Complexity Approximation Principle and Rissanen's Approach to Real-Valued Parameters
Rule Combination in Inductive Learning
NeurIPS’22 Cross-Domain MetaDL competition: Design and baseline results
Nonnegative Lagrangian Relaxation of K -Means and Spectral Clustering
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
Getting Order Independence in Incremental Learning
A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks
Experiments on Solving Multiclass Learning Problems by n 2 -classifier
Machine Learning: ECML-97, 9th European Conference on Machine Learning, Prague, Czech Republic, April 23-25, 1997, Proceedings
Evaluating Feature Selection for SVMs in High Dimensions
Efficient Computation of Recursive Principal Component Analysis for Structured Input
The Cost of Learning Directed Cuts
Wrapper Generation via Grammar Induction
Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract)
Finding Hidden Factors Using Independent Component Analysis
Interpretable Meta-Score for Model Performance: Extended Abstract
Extending Explanation-Based Generalization by Abstraction Operators
Error Estimators for Pruning Regression Trees
Languages as Hyperplanes: Grammatical Inference with String Kernels
Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study
Hidden Markov Models with Patterns and Their Application to Integrated Circuit Testing
Improving the AUC of Probabilistic Estimation Trees
Evaluating Misclassifications in Imbalanced Data
Integrating Models of Knowledge and Machine Learning
The Representation Race - Preprocessing for Handling Time Phenomena
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
Feature Subset Selection in Text-Learning
Signal Correlation Prediction Using Convolutional Neural Networks
Automatic Synthesis of Control Programs by Combination of Learning and Problem Solving Methods (Extended Abstract)
Bandit Based Monte-Carlo Planning
Pertinent Background Knowledge for Learning Protein Grammars
Cost-Sensitive Decision Tree Learning for Forensic Classification
Graph-Based Domain Mapping for Transfer Learning in General Games
Intensional Learning of Logic Programs
Problem Decomposition and the Learning of Skills
Geometric Properties of Naive Bayes in Nominal Domains
Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers
Learning a Classifier with Very Few Examples: Analogy Based and Knowledge Based Generation of New Examples for Character Recognition
Exploiting Classifier Combination for Early Melanoma Diagnosis Support
Missing Data in Kernel PCA
Generalization under Implication by using Or-Introduction
Mode Directed Path Finding
Scaling Boosting by Margin-Based Inclusionof Features and Relations
An Axiomatic Approach to Feature Term Generalization
Batch Reinforcement Learning with State Importance
Variational Extensions to EM and Multinomial PCA
Incremental Learning of Context Free Grammars by Extended Inductive CYK Algorithm
Evaluation of Topographic Clustering and Its Kernelization
A New Pairwise Ensemble Approach for Text Classification
Feature Selection: Near Set Approach
Visualizations for Assessing Convergence and Mixing of MCMC
Sensitivity Analysis of the Result in Binary Decision Trees
Machine Learning as an Experimental Science
Neighborhood-Based Local Sensitivity
Imitation Learning Using Graphical Models
Proceedings of the Third European Working Session on Learning, EWSL 1988, Turing Institute, Glasgow, UK, October 3-5, 1988
Distributional Features for Text Categorization
A Model Based Method for Automatic Facial Expression Recognition
An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games
Network Game and Boosting
Representation and Induction of Musical Structures for Computer Assisted Composition
Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems
Trust Region Meta Learning for Policy Optimization
Improving Term Extraction by System Combination Using Boosting
Fast Variational Inference for Gaussian Process Models Through KL-Correction
An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learning
Proceedings of the Neural Connectomics Workshop at ECML 2014, Porto, Portugal, September 7, 2015
Robust Probabilistic Calibration
Characterizing the Applicability of Classification Algorithms Using Meta-Level Learning
K -SVCR. A Multi-class Support Vector Machine
Graph Based Semi-supervised Learning with Sharper Edges
Two Contributions of Constraint Programming to Machine Learning
The Huller: A Simple and Efficient Online SVM
Bayesian Learning of Markov Network Structure
Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry
An Instance-Based Learning Method for Database: An Information Theoretic Approach
Investigation and Reduction of Discretization Variance in Decision Tree Induction
A Two-Level Learning Method for Generalized Multi-instance Problems
On Prediction by Data Compression
Integrating EBL with automatic Text Analysis
Two Methods for Improving Inductive Logic Programming Systems
An Information-Theoretic Framework for High-Order Co-clustering of Heterogeneous Objects
Theta-Subsumption for Structural Matching
Text Categorization with Support Vector Machines: Learning with Many Relevant Features
Conditions for Occam's Razor Applicability and Noise Elimination
Multi-class Ensemble-Based Active Learning
Learning from Positive and Unlabeled Examples with Different Data Distributions
Conceptual Clustering Applied to Ontologies
Proceedings of the Workshop and Tutorial on Learning Contex-Free Grammars, ECML 2003, Cavtat-Dubrovnik, Croatia, September 22-26, 2003
Probabilistic Explanation Based Learning
An Induction-based Control for Genetic Algorithms (Extended Abstract)
Ranking with Predictive Clustering Trees
Relative Unsupervised Discretization for Regresseion Problems
ASSISTANT 86: A Knowledge-Elicitation Tool for Sophisticated Users
Shift of Bias in Learning from Drug Compounds: The Fleming Project
Class-Driven Statistical Discretization of Continuous Attributes (Extended Abstract)
An Efficient and Effective Procedure for Updating a Competence Model for Case-Based Reasoners
Rademacher Penalization over Decision Tree Prunings
Could Active Perception Aid Navigation of Partially Observable Grid Worlds?
Sequence Discrimination Using Phase-Type Distributions
Policy Gradient Critics
Inducing Polynomial Equations for Regression
Improvement of Systems Management Policies Using Hybrid Reinforcement Learning
Robust Bayesian Linear Classifier Ensembles
Short-Term Profiling for a Case-Based Reasoning
Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings
Simplifying Decision Trees by Pruning and Grafting: New Results (Extended Abstract)
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
The System FLORA: Learning from Type-Varying Training Sets
Discriminative Sequence Labeling by Z-Score Optimization
Determining Property Relevance in Concept Formation by Computing Correlation Between Properties
Panel: Learning in Distributed Systems and Multi-Agent Environments
Ensembles of Nearest Neighbor Forecasts
Optimizing Local Probability Models for Statistical Parsing
Case Exchange Strategies in Multiagent Learning
Learning Hard Concepts
Optimising Performance of Competing Search Engines in Heterogeneous Web Environments
Using Text Mining and Link Analysis for Software Mining
A Similar Fragments Merging Approach to Learn Automata on Proteins
Co-operative Reinforcement Learning By Payoff Filters (Extended Abstract)
Learning from Message Pairs for Automatic Email Answering
Some advances regarding ontologies and neuro-symbolic artificial intelligence
Propagation of Q-values in Tabular TD(lambda)
Learnability of Constrained Logic Programs
Learning Control Knowledge Within an Explanation-Based Learning Framework
On Discriminative Joint Density Modeling
Estimating the Predictive Accuracy of a Classifier
Estimation of Mixture Models Using Co-EM
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Incremental Learning of Control Knowledge for Nonlinear Problem Solving
Learning When Negative Examples Abound
Searching in the Forest for Local Bayesian Optimization
Leveraging Lexical Semantics to Infer Context-Free Grammars
Can Complexity Theory Benefit from Learning Theory?
Ordinal Classification with Decision Rules
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
Learning to Classify X-Ray Images Using Relational Learning
Using MDP Characteristics to Guide Exploration in Reinforcement Learning
Reliable Classifications with Machine Learning
Robust k -DNF Learning via Inductive Belief Merging
On Pairwise Naive Bayes Classifiers
Integrating an Explanation-Based Learning Mechanism into a General Problem-Solver
Learning with Hilbert Cubes
Bayes Optimal Instance-Based Learning
Learning in Dynamically Changing Domains: Theory Revision and Context Dependence Issues
A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker
SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data
An Analytic and Empirical Comparison of Two Methods for Discovering Probabilistic Causal Relationships
Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers
Improved Pairwise Coupling Classification with Correcting Classifiers
Model Combination in the Multiple-Data-Batches Scenario
Localized Alternative Cluster Ensembles for Collaborative Structuring
Effective Voting of Heterogeneous Classifiers
Scope Classification: An Instance-Based Learning Algorithm with a Rule-Based Characterisation
Effective Learning in Dynamic Environments by Explicit Context Tracking
Improving Random Forests
Automatic Acquisition of Lexical Knowledge from Sparse and Noisy Data
Learning Rules to Improve a Machine Translation System
Learning to Fly Simple and Robust
Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space
Fisher Kernels for Logical Sequences
A Distance-Based Approach for Action Recommendation
Constructing Decision Trees in Noisy Domains
Combining Bias and Variance Reduction Techniques for Regression Trees
Parallel and Distributed Search for Structure in Multivariate Time Series
Learning and Classifying Under Hard Budgets
Discovering Word Meanings Based on Frequent Termsets
Constructing and Sharing Perceptual Distiinctions
An Inductive Learning Approach to the Problem of Predicting a Protein's Secondary Structure from Its Amino Acid Sequence
Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging
Naive Bayesian Classifiers for Ranking
Partially Supervised Text Classification: Combining Labeled and Unlabeled Documents Using an EM-like Scheme
On the Utility of Predicate Invention in Inductive Logic Programming
Semi-definite Manifold Alignment
(Agnostic) PAC Learning Concepts in Higher-Order Logic
Controlled Redundancy in Incremental Rule Learning
Machine Learning - EWSL-91, European Working Session on Learning, Porto, Portugal, March 6-8, 1991, Proceedings
On the Role of Machine Learning in Knowledge-Based Control
Q-Learning and Redundancy Reduction in Classifier Systems with Internal State
When Does Overfitting Decrease Prediction Accuracy in Induced Decision Trees and Rule Sets?
Conditional Independence Trees
Discriminant Feature Analysis for Music Timbre Recognition and Automatic Indexing
Learning Nonrecursive Definitions of Relations with LINUS
A Kernel Approach for Learning from almost Orthogonal Patterns
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning
On the Practice of Branching Program Boosting
Learning Relations with Closing the World (Extended Abstract)
Undercomplete Blind Subspace Deconvolution Via Linear Prediction
Evidence that Incremental Delta-Bar-Delta Is an Attribute-Efficient Linear Learner
Learning of Variability for Invariant Statistical Pattern Recognition
Performance evaluation of dynamic multi-swarm particle swarm optimizer with different constraint handling methods on path planning problems
Super-fit and population size reduction in compact Differential Evolution
Research on evolution hardware design based on memetic algorithm
A memetic algorithm for uncertain Capacitated Arc Routing Problems
Hybrid Algorithm based on Differential Immune Clone with Orthogonal design method
2013 IEEE Workshop on Memetic Computing, MC 2013, Singapore, Singapore, April 16-19, 2013
A hybrid imperialist competitive-gravitational attraction search algorithm to optimize cloud service composition
PSO based memetic algorithm for face recognition Gabor filters selection
Optimal Testing Resource Allocation for modular software systems based-on multi-objective evolutionary algorithms with effective local search strategy
Neural meta-memes framework for managing search algorithms in combinatorial optimization
On the analysis of a (1+1) adaptive memetic algorithm
Prediction of protein-protein interactions from amino acid sequences using extreme learning machine combined with auto covariance descriptor
2011 IEEE Workshop on Memetic Computing, MC 2011, Paris, France, April 11-15, 2011
Multi-objective immune algorithm with dynamic memetic Cauchy mutation
Memetic figure selection for cluster expansion in binary alloy systems
On the effect of population size and selection mechanism from the viewpoint of collaboration between exploration and exploitation
A coevolving memetic algorithm for simultaneous partitional clustering and feature weighting
System optimization of a 5.8 GHz ETC receiver using Memetic algorithm
A graph-based memetic approach to sketch geolocation
Probabilistic memetic algorithm for flowshop scheduling
Re-sampling search: A seriously simple memetic approach with a high performance
Analysis of Facile Programs: A Case Study
Type Checking for a Multiset Rewriting Language
Polymorphic Subtyping for Effect Analysis: The Dynamic Semantics
Parallel Implementation of Functional Languages
Prorities in Statecharts
Analysis and Verification of Multiple-Agent Languages, 5th LOMAPS Workshop, Stockholm, Sweden, June 24-26, 1996, Selected Papers