yusuke1997/dblp-id-title huggingface dataset:
Neu-BrAuER: A Neuromorphic Braille Letters Audio-Reader for Commercial Edge Devices
Selection and Statistical Validation of Features and Prototypes
Random Similarity Forests
S&P360: Multidimensional Perspective on Companies from Online Data Sources
Infection Hot Spot Mining from Social Media Trajectories
Game Theoretic Explanations for Graph Neural Networks
Ipseity - A Laboratory for Synthesizing and Validating Artificial Cognitive Systems in Multi-agent Systems
Privacy-Preserving Decision Trees Training and Prediction
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties
Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions
Interestingness in Attribute-Oriented Induction (AOI): Multiple-Level Rule Generation
For Visualization-Based Analysis Tools in Knowledge Discovery Process: A Multilayer Perceptron versus Principal Components Analysis: A Comparative Study
A Practical Approach to Reduce the Learning Bias Under Covariate Shift
All-for-One and One-for-All: Deep Learning-Based Feature Fusion for Synthetic Speech Detection
Automatic Tool Wear Inspection by Cascading Sensor and Image Data
Adversarial Sample Detection Through Neural Network Transport Dynamics
Machine Learning Approaches to Hybrid Music Recommender Systems
Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies
Single-Fold Distillation for Diffusion Models
Construction and Training of Multi-Associative Graph Networks
Collaboration-based Social Tag Prediction in the Graph of Annotated Web Pages
SoccerMix: Representing Soccer Actions with Mixture Models
Nyström Sketches
The Relation of Closed Itemset Mining, Complete Pruning Strategies and Item Ordering in Apriori-Based FIM Algorithms
Introducing Noise in Decentralized Training of Neural Networks
Adding Temporal Semantics to Association Rules
CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting
Player Vectors: Characterizing Soccer Players' Playing Style from Match Event Streams
Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning
Testing Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin Allocation
FIPER: A Visual-Based Explanation Combining Rules and Feature Importance
Towards Geometry-Preserving Domain Adaptation for Fault Identification
Logics and Statistics for Association Rules and Beyond Abstract of Tutorial
Preserving the World Heritage: Post-earthquake Monitoring Based on Structural Break Testing with Deep Temporal Convolutional Features
Clustering Image Search Results by Entity Disambiguation
Large-Scale Nonlinear Variable Selection via Kernel Random Features
Learning to Control Local Search for Combinatorial Optimization
Hypothesis Testing for Class-Conditional Label Noise
Hierarchical Learning Machines and Neuroscience of Visual Cortex
The Sensitivity of Latent Dirichlet Allocation for Information Retrieval
Deep Over-sampling Framework for Classifying Imbalanced Data
Relative Unsupervised Discretization for Association Rule Mining
Address Validation in Transportation and Logistics: A Machine Learning Based Entity Matching Approach
Learning to Build High-Fidelity and Robust Environment Models
Real-Time Lane Configuration with Coordinated Reinforcement Learning
Action Set Based Policy Optimization for Safe Power Grid Management
Exploring Contrastive Learning for Long-Tailed Multi-label Text Classification
PrivateCTGAN: Adapting GAN for Privacy-Aware Tabular Data Sharing
An Entropy-Based Approach for Generating Multi-dimensional Sequential Patterns
Traffic Jams Detection Using Flock Mining
A Human-Centric Assessment of the Usefulness of Attribution Methods in Computer Vision
Tight Optimistic Estimates for Fast Subgroup Discovery
M 2 SP: Mining Sequential Patterns Among Several Dimensions
Neural Hybrid Recommender: Recommendation Needs Collaboration
Exceptional Model Mining
ClaRe: Classification and Regression Tool for Multivariate Time Series
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), Porto, Portugal, September 7th, 2015
Use of Performance Metrics to Forecast Success in the National Hockey League
Continuous-Time Markov-Switching GARCH Process with Robust State Path Identification and Volatility Estimation
Learning Exemplar-Represented Manifolds in Latent Space for Classification
Arbogodaï, a New Approach for Decision Trees
Itemset Based Sequence Classification
Mining Data for Financial Applications - 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
SITS-P2miner: Pattern-Based Mining of Satellite Image Time Series
Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces
Usefulness of Unsupervised Ensemble Learning Methods for Time Series Forecasting of Aggregated or Clustered Load
Fast Projections onto ℓ1, q -Norm Balls for Grouped Feature Selection
Which Topic Will You Follow?
A Bayesian Approach for Classification Rule Mining in Quantitative Databases
Contextual Data Augmentation for Task-Oriented Dialog Systems
Thompson Sampling for Optimizing Stochastic Local Search
SPIN! Data Mining System Based on Component Architecture
Embeddings Based Parallel Stacked Autoencoder Approach for Dimensionality Reduction and Predictive Maintenance of Vehicles
VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences
Present and Future Generalization of Synthetic Image Detectors
Applying Machine Learning for Traffic Forecasting in Porto, Portugal
FedDNA: Federated Learning with Decoupled Normalization-Layer Aggregation for Non-IID Data
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast
Learning with Ensembles of Randomized Trees : New Insights
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Frame-Based Optimal Design
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017
MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings
Clustering Distributed Sensor Data Streams
XRR: Explainable Risk Ranking for Financial Reports
Efficient Spatial Classification Using Decoupled Conditional Random Fields
Ranked Tiling
Learning from Demonstrations: Is It Worth Estimating a Reward Function?
Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement
Don't Be Afraid of Simpler Patterns
Detecting Sexually Explicit Content in the Context of the Child Sexual Abuse Materials (CSAM): End-to-End Classifiers and Region-Based Networks
Learning from Demonstration Using MDP Induced Metrics
Active Preference Optimization for Sample Efficient RLHF
A Web Crawling Environment to Support Financial Strategies and Trend Correlation - - Extended Abstract -
Enhancing Traffic Congestion Estimation with Social Media by Coupled Hidden Markov Model
Sparse Unsupervised Dimensionality Reduction Algorithms
Knowledge Discovery - A Control Theory Perspective
Constructing Nonlinear Discriminants from Multiple Data Views
Graph Machine Learning for Fast Product Development from Formulation Trials
Neural Gaussian Conditional Random Fields
Discovering SpatioTemporal Warning Contexts from Non-emergency Call Reports
Learning to Infer Social Ties in Large Networks
Embedded Face Recognition for Personalized Services in the Assistive Robotics
A Peculiarity-based Exploration of Syntactical Patterns: a Computational Study of Stylistics
How Much Training Data Is Memorized in Overparameterized Autoencoders? An Inverse Problem Perspective on Memorization Evaluation
Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering
Improving Novel Anomaly Detection with Domain-Invariant Latent Representations
Exploring Counterfactual Explanations for Classification and Regression Trees
Bandit Max-Min Fair Allocation
EARLIN: Early Out-of-Distribution Detection for Resource-Efficient Collaborative Inference
Fooling Partial Dependence via Data Poisoning
Cost Sensitive Evaluation of Instance Hardness in Machine Learning
Achieving Counterfactual Explanation for Sequence Anomaly Detection
Real-Time Anomaly Prediction from Cryptocurrency Time Series
Recognizing Complex Activities by a Temporal Causal Network-Based Model
The Pattern Ordering Problem
Conversations on Twitter: Structure, Pace, Balance
FedPHP: Federated Personalization with Inherited Private Models
A KDD Process for Discrimination Discovery
Demonstrator on Counterfactual Explanations for Differentially Private Support Vector Machines
Flexible Grid-Based Clustering
Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery
Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings
Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems
Discovering Neutrinos Through Data Analytics
Unsupervised Bayesian Part of Speech Inference with Particle Gibbs
Ranking the Uniformity of Interval Pairs
Discovering Nested Communities
Modelling Input Varying Correlations between Multiple Responses
Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach
Mining Research Topic-Related Influence between Academia and Industry
Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities
GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid
Systematical Evaluation of Solar Energy Supply Forecasts
Reachability Analysis and Modeling of Dynamic Event Networks
LioNets: Local Interpretation of Neural Networks Through Penultimate Layer Decoding
Proceedings of the Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV 2016) co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2016), Riva del Garda, Italy, September 23, 2016
ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations
Aspect-Based Complaint and Cause Detection: A Multimodal Generative Framework with External Knowledge Infusion
Squeezing Correlated Neurons for Resource-Efficient Deep Neural Networks
Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression
Burnt Area Extraction from High-Resolution Satellite Images Based on Anomaly Detection
Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering
Improved Counter Based Algorithms for Frequent Pairs Mining in Transactional Data Streams
Semi-supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-labelling
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning
Detecting Face Synthesis Using a Concealed Fusion Model
Spatiotemporal Covariance Neural Networks
Semi-structured Document Annotation Using Entity and Relation Types
Predicate-Based Explanation of a Reinforcement Learning Agent via Action Importance Evaluation
Reinforcement Learning Meets Microeconomics: Learning to Designate Price-Dependent Supply and Demand for Automated Trading
Position Preserving Multi-Output Prediction
Finding simple temporal cycles in an interaction network
Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation
Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators
A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data
GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction
A Habit Detection Algorithm (HDA) for Discovering Recurrent Patterns in Smart Meter Time Series
Efficiently Finding Arbitrarily Scaled Patterns in Massive Time Series Databases
Posterior Consistency for Missing Data in Variational Autoencoders
The Use of the Label Hierarchy in Hierarchical Multi-label Classification Improves Performance
Learning Association Rules for Pharmacogenomic Studies
Probabilistic Graphs for Sensor Data-Driven Modelling of Power Systems at Scale
Voronoi Diagram Encoded Hashing
Deep Reinforcement Learning (DRL) for Portfolio Allocation
Modeling the Business Process by Mining Multiple Databases
Honest Mirror: Quantitative Assessment of Player Performance in an ODI Cricket Match
NBcoded: Network Attack Classifiers Based on Encoder and Naive Bayes Model for Resource Limited Devices
Representation Learning in Graphs for Credit Card Fraud Detection
Information-Theoretic Transfer Learning Framework for Bayesian Optimisation
Anti-discrimination Analysis Using Privacy Attack Strategies
KANITE: Kolmogorov-Arnold Networks for ITE Estimation
Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks
Efficient Frequent Query Discovery in FARMER
Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning
Marine Mammal Species Classification Using Convolutional Neural Networks and a Novel Acoustic Representation
Attribute and Context-Aware Multi-Behavior Model for Unique-Item Recommendation
Sharing RapidMiner Workflows and Experiments with OpenML
Data Analytics for Renewable Energy Integration - 4th ECML PKDD Workshop, DARE 2016, Riva del Garda, Italy, September 23, 2016, Revised Selected Papers
Quantification Over Time
Active Learning Is Planning: Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes
Assessing the Difficulty of Labelling an Instance in Crowdworking
Clustering in the Presence of Concept Drift
KAT5: Knowledge-Aware Transfer Learning with a Text-to-Text Transfer Transformer
Automatic Feature Engineering Through Monte Carlo Tree Search
Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space
A Bilevel Reinforcement Learning Framework with Language Prior Knowledge
Parameter Learning in Probabilistic Databases: A Least Squares Approach
To Ensemble or Not Ensemble: When Does End-to-End Training Fail?
Checking Robustness of Representations Learned by Deep Neural Networks
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part X
Online Deep Hybrid Ensemble Learning for Time Series Forecasting
Data Mining in Schizophrenia Research - Preliminary Analysis
Sequential Rule Analysis of ICU Patient Vital Signals and Alarms
Leveraging Bagging for Evolving Data Streams
A Two-Level Learning Hierarchy of Concept Based Keyword Extraction for Tag Recommendations
Adventures in Personalized Information Access
Explaining a Random Survival Forest by Extracting Prototype Rules
Mining Marathon Training Data to Generate Useful User Profiles
A Light Weight Cardiac Monitoring System for On-device ECG Analysis
SOS-EW: System for Overdose Spike Early Warning Using Drug Mover's Distance-Based Hawkes Processes
Heterogeneous Network Decomposition and Weighting with Text Mining Heuristics
Detecting Events in a Million New York Times Articles
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III
Experiments in Meta-level Learning with ILP
Understanding the Benefits of Forgetting When Learning on Dynamic Graphs
Learning a Distance Metric for Object Identification Without Human Supervision
From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge
Summary Extraction on Data Streams in Embedded Systems
Contrastive Representations for Label Noise Require Fine-Tuning
Homological Time Series Analysis of Sensor Signals from Power Plants
Finding Relevant Multivariate Models for Multi-plant Photovoltaic Energy Forecasting
A Theoretical Framework for Exploratory Data Mining: Recent Insights and Challenges Ahead
A Modified and Fast Perceptron Learning Rule and its Use for Tag Recommendations in Social Bookmarking Systems
Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis
Rough Set Theory as a Data Mining Technique: A Case Study in Epidemiology and Cancer Incidence Prediction
MetaBags: Bagged Meta-Decision Trees for Regression
2nd Workshop on Learning with Imbalanced Domains: Preface
Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems
Towards Automatically Refining Low-Quality Domain Knowledge: A Case Study in Healthcare
Scalable Nonlinear AUC Maximization Methods
CourboSpark: Decision Tree for Time-series on Spark
Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results
Neural Symbolic Music Genre Transfer Insights
Proceedings of the First Workshop on Data Science for Social Good co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Dicovery in Databases, SoGood@ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016
DyCOD - Determining Cash on Delivery Limits for Real-Time E-commerce Transactions via Constrained Optimisation Modelling
Incremental Sensitivity Analysis for Kernelized Models
Graph Attention Transformer for Unsupervised Multivariate Time Series Anomaly Detection
Learning Gradient Boosted Multi-label Classification Rules
Fast Gaussian Pairwise Constrained Spectral Clustering
An Algorithmic Framework for Decentralised Matrix Factorisation
Combinatorial Approach for Data Binarization
Improved Topology Features for Node Classification on Heterophilic Graphs
Wiser than the Wisest of Crowds: The Asch Effect and Polarization Revisited
A Hybrid Recommendation System Based on Bidirectional Encoder Representations
Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control
Are Network Attacks Outliers? A Study of Space Representations and Unsupervised Algorithms
Generalized Agreement Statistics over Fixed Group of Experts
Multi-core Structural SVM Training
A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data
Identifying lncRNA-Disease Relationships via Heterogeneous Clustering
Symbolic Prompt Tuning Completes the App Promotion Graph
Embed Wisely: An Ensemble Approach to Predict ICD Coding
Support Vector Machines for Differential Prediction
Rough Set Theory and Rule Induction Techniques for Discovery of Attribute Dependencies in Medical Information Systems
Z-Embedding: A Spectral Representation of Event Intervals for Efficient Clustering and Classification
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering
Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks
Think Out of the Package: Recommending Package Types for E-Commerce Shipments
Monte Carlo Search Algorithms for Network Traffic Engineering
Towards Automated Relational Data Wrangling
Hybrid Self Adaptive Learning Scheme for Simple and Multiple Drift-like Fault Diagnosis in Wind Turbine Pitch Sensors
Clustering Sargassum Mats from Earth Observation Data
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
Learning Approximate MRFs from Large Transaction Data
Mining Hierarchical Decision Rules from Clinical Databases Using Rough Sets aaand Medical Diagnostic Model
Efficiency of Coordinate Descent Methods for Structured Nonconvex Optimization
Bayesian Models for Structured Sparse Estimation via Set Cover Prior
On Spatial Measures of Geographic Relevance for Geotagged Social Media Content
Generalizing Knowledge in Decentralized Rule-Based Models
Algorithms for Constructing of Decision Trees
Credible Review Detection with Limited Information Using Consistency Features
Invariant Lipschitz Bandits: A Side Observation Approach
Proceedings of ECML PKDD (The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases) Discovery Challenge 2009, Bled, Slovenia, September 7, 2009
From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity Clustering
Sparsity in Bayesian Blind Source Separation and Deconvolution
SEWeP: A Web Mining System Supporting Semantic Personalization
Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation
DeepCluster: A General Clustering Framework Based on Deep Learning
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Quantifying the Resilience of Inductive Classification Algorithms
Synthesizing Diabetic Foot Ulcer Images with Diffusion Model
Itemset Classified Clustering
Tensor Factorization Using Auxiliary Information
DialCSP: A Two-Stage Attention-Based Model for Customer Satisfaction Prediction in E-commerce Customer Service
Training Parameterized Quantum Circuits with Triplet Loss
Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories
Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain
Competitive Online Generalized Linear Regression under Square Loss
A Novel Scalable and Data Efficient Feature Subset Selection Algorithm
Sequence Generation Using Unwords
All You Need is Color: Image Based Spatial Gene Expression Prediction Using Neural Stain Learning
DeepCore: Simple Fingerprint Construction for Differentiating Homologous and Piracy Models
Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing
Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams
Multimodal Sensor Fusion for Daily Living Activity Recognition in Active Assisted Living for Older Adults
RAE: A Rule-Driven Approach for Attribute Embedding in Property Graph Recommendation
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression
Enhancing Table Retrieval with Dual Graph Representations
Weak Supervision and Clustering-Based Sample Selection for Clinical Named Entity Recognition
Feature Selection Stability Assessment Based on the Jensen-Shannon Divergence
Deep Structural Point Process for Learning Temporal Interaction Networks
Ranking the Teams in European Football Leagues with Agony
Calibrating Distance Metrics Under Uncertainty
Machine Learning for Natural Language Processing (and Vice Versa?)
A Light-Weight Deep Residual Network for Classification of Abnormal Heart Rhythms on Tiny Devices
Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial
Automatically Detecting and Rating Product Aspects from Textual Customer Reviews
Coordinate Transformations for Characterization and Cluster Analysis of Spatial Configurations in Football
Discovering Audience Groups and Group-Specific Influencers
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees
Scalable Feature Selection for Multi-class Problems
Improved Multi-label Propagation for Small Data with Multi-objective Optimization
Block-Level Surrogate Models for Inference Time Estimation in Hardware-Aware Neural Architecture Search
Good news and bad news: Do online investor sentiments reaction to return news asymmetric?
Efficient Fine-Tuning Large Language Models for Knowledge-Aware Response Planning
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings
Strategic Mitigation Against Wireless Attacks on Autonomous Platoons
MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders Are Better Dense Retrievers
Multi-agent Heterogeneous Stochastic Linear Bandits
Convergence of Min-Sum-Min Message-Passing for Quadratic Optimization
Deep Online Storage-Free Learning on Unordered Image Streams
UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN
Cross-Domain Conditional Diffusion Models for Time Series Imputation