yusuke1997/dblp-id-title huggingface dataset:
Hypernode Graphs for Spectral Learning on Binary Relations over Sets
Adversarial Learned Molecular Graph Inference and Generation
Auto-clustering of Financial Reports Based on Formatting Style and Author's Fingerprint
Community Trend Outlier Detection Using Soft Temporal Pattern Mining
Proper Losses for Learning with Example-Dependent Costs
Scatteract: Automated Extraction of Data from Scatter Plots
Applying Machine Learning to Predict Closing Prices in Stock Market: A Case Study
How Data Availability Affects the Ability to Learn Good xG Models
New Closed-Form Bounds on the Partition Function
Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models
Graph-Based Approaches to Clustering Network-Constrained Trajectory Data
Statistical Model for Rough Set Approach to Multicriteria Classification
Scaling up Dynamic Time Warping to Massive Dataset
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II
Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy?
Privacy Preserving Protocols for Eigenvector Computation
AMST: Alternating Multimodal Skip Training
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part III
Intrusion Detection Using Ensemble Models
On Neural Forecasting and News Emotions: The Case of the Spanish Stock Market
Domain Adaption in One-Shot Learning
Preventing Over-Fitting of Cross-Validation with Kernel Stability
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VII
Contextual Language Models for Knowledge Graph Completion
Mining Keystroke Timing Pattern for User Authentication
Learning Distributed Representations of Users for Source Detection in Online Social Networks
A Taxonomy of Interactive Online Machine Learning Strategies
Proactive Transfer Learning for Heterogeneous Feature and Label Spaces
The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization
A Brand Scoring System for Cryptocurrencies Based on Social Media Data
Graph-Based Motion Planning Networks
On the Correspondence between Classes of Implicational and Equivalence Quantifiers
Sampling-Based Data Mining Algorithms: Modern Techniques and Case Studies
Adaptive Learning Rate and Momentum for Training Deep Neural Networks
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II
Multi-graph Clustering Based on Interior-Node Topology with Applications to Brain Networks
Distributed Adaptive Optimization with Divisible Communication
Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining
Exploring Gender Bias in Misclassification with Clustering and Local Explanations
Multi-Subspace Representation and Discovery
MetaData Retrieval: A Software Prototype for the Annotation of Maps with Social Metadata
Unsupervised Sentence Embedding Using Document Structure-Based Context
P2NIA: Privacy-Preserving Non-iterative Auditing
Towards Discovery of Information Granules
Learning Recommendations in Social Media Systems by Weighting Multiple Relations
A Distributed Framework for Large-Scale Time-Dependent Graph Analysis
Association Mining in Large Databases: A Re-examination of Its Measures
Minimum-Size Bases of Association Rules
Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms
Recognizing User's Activity and Transport Mode Detection: Maintaining Low-Power Consumption
A General Measure of Rule Interestingness
A Reduction of Label Ranking to Multiclass Classification
Quantifying Energy Demand in Mountainous Areas
MANTRA: Temporal Betweenness Centrality Approximation Through Sampling
A Few Good Sentences: Content Selection for Abstractive Text Summarization
Confirmation Rule Sets
An Advert Creation System for Next-Gen Publicity
Generalizing Patterns for Cross-Domain Analogy
Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII
Quantized Gromov-Wasserstein
OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces
A Framework for Pattern Mining and Anomaly Detection in Multi-dimensional Time Series and Event Logs
Using Condensed Representations for Interactive Association Rule Mining
Feature Extraction from Mass Spectra for Classification of Pathological States
Measuring Vertex Centrality in Co-occurrence Graphs for Online Social Tag Recommendation
A Live Comparison of Methods for Personalized Article Recommendation at Forbes.com
LSTM Encoder-Predictor for Short-Term Train Load Forecasting
Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning
Multi-agent Imitation Learning with Copulas
Gx2Mol: De Novo Generation of Hit-Like Molecules from Gene Expression Profiles
Selecting Collaborative Filtering Algorithms Using Metalearning
TAMIS: Tailored Membership Inference Attacks on Synthetic Data
Learning Cheap and Novel Flight Itineraries
Visual Exploration of Genomic Data
Deep Ordinal Reinforcement Learning
Interactive Interpretation of Hierarchical Clustering
Attributed Graph Kernels Using the Jensen-Tsallis q-Differences
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation
Fast Feature Selection Using Partial Correlation for Multi-vaslued Attributes
CentroidNet: A Deep Neural Network for Joint Object Localization and Counting
A Model-Agnostic Approach to Quantifying the Informativeness of Explanation Methods for Time Series Classification
Evolutionary Dynamics of Regret Minimization
Mixtures of Large Margin Nearest Neighbor Classifiers
Layered TPOT: Speeding up Tree-based Pipeline Optimization
Integrating Learning and Reasoning with Deep Logic Models
Activation Anomaly Analysis
A Self-training Approach to Cost Sensitive Uncertainty Sampling
Node Classification in Temporal Graphs Through Stochastic Sparsification and Temporal Structural Convolution
Discovering and Tracking Organizational Structures in Event Logs
Concept Drift Detection Using Ensemble of Integrally Private Models
New Frontiers in Mining Complex Patterns - 5th International Workshop, NFMCP 2016, Held in Conjunction with ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016, Revised Selected Papers
Contextualized Graph Embeddings for Adverse Drug Event Detection
Analysis of Large Multi-modal Social Networks: Patterns and a Generator
Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling
Mining Conjunctive Sequential Patterns
Modelling Solar PV Adoption in Irish Dairy Farms Using Agent-Based Modelling
BDUOL: Double Updating Online Learning on a Fixed Budget
SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs
Information Extraction in Structured Documents Using Tree Automata Induction
How Much Linguistics Do We Need in order to Understand Online Opinions?
Proceedings of the Workshop on Machine Learning and Data Mining for Sports Analytics 2016 co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, MLSA@PKDD/ECML 2016, Riva del Garda, Italy, September 19, 2016
Dynamic Joint Variational Graph Autoencoders
Watch-It-Next: A Contextual TV Recommendation System
Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part III
Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), Porto, Portugal, September 7-11, 2015
A Workflow for Creating Multimodal Machine Learning Models for Metastasis Predictions in Melanoma Patients
Web Usage Mining: How to Efficiently Manage New Transactions and New Clients
A Relational Data Mining Tool Based On Genetic Programming
Online Structural Graph Clustering Using Frequent Subgraph Mining
Continual Learning with Knowledge Transfer for Sentiment Classification
Sets of Robust Rules, and How to Find Them
LimeOut: An Ensemble Approach to Improve Process Fairness
Disentanglement and Local Directions of Variance
Testing for Self-excitation in Financial Events: A Bayesian Approach
Time and Again: - Time Series Mining via Recurrence Quantification Analysis
PU GNN: Chargeback Fraud Detection in P2E MMORPGs via Graph Attention Networks with Imbalanced PU Labels
KDTA: Automated Knowledge-Driven Text Annotation
Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data
Linking Event Mentions From Cricket Match Reports to Commentaries
GAMA: A General Automated Machine Learning Assistant
k -Anonymous Decision Tree Induction
ETT-CKGE: Efficient Task-Driven Tokens for Continual Knowledge Graph Embedding
Dropout's Dream Land: Generalization from Learned Simulators to Reality
Multi-interest Extraction Joint with Contrastive Learning for News Recommendation
Queryable and Interpretable PU Learning Through Probabilistic Circuits
Is This Bug Severe? A Text-Cum-Graph Based Model for Bug Severity Prediction
Detecting Stable Communities in Link Streams at Multiple Temporal Scales
Transforming PageRank into an Infinite-Depth Graph Neural Network
Deep Modular Multimodal Fusion on Multiple Sensors for Volcano Activity Recognition
Classifying Traces of Event Logs on the Basis of Security Risks
BoostEMM - Transparent Boosting using Exceptional Model Mining
The Search for Equations - Learning to Identify Similarities Between Mathematical Expressions
Automatic Classification of Strike Techniques Using Limb Trajectory Data
Speeding Up Logistic Model Tree Induction
Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation
Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification
On Discriminative Parameter Learning of Bayesian Network Classifiers
On Modeling Labor Markets for Fine-Grained Insights
Improving Human Activity Classification through Online Semi-Supervised Learning
On Inferring a Meaningful Similarity Metric for Customer Behaviour
Online Failure Prevention from Connected Heating Systems
Advocating for Multiple Defense Strategies Against Adversarial Examples
Automating Geospatial Vision Tasks with a Large Language Model Agent
The ChatGPT and Education Tweets Dataset
Adacket: ADAptive Convolutional KErnel Transform for Multivariate Time Series Classification
Improving Discriminator Guidance in Diffusion Models
Machine Learning Techniques for Supporting Renewable Energy Generation and Integration: A Survey
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
ECML PKDD 2018 Workshops - MIDAS 2018 and PAP 2018, Dublin, Ireland, September 10-14, 2018, Proceedings
Next Day Fire Prediction via Semantic Segmentation
Plant Disease Detection Using Deep Learning: A Proof of Concept on Pear Leaf Disease Detection
Finding Trees from Unordered 0-1 Data
A Community-Based Platform for Machine Learning Experimentation
Knowledge-Driven Active Learning
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes
Analyzing and Grounding Social Interaction in Online and Offline Networks
One-Class Quantification
Difference Target Propagation
Self-Similar Layered Hidden Markov Models
A Fast Effective Multi-Channeled Tag Recommender
Multi-view Self-supervised Heterogeneous Graph Embedding
Comparative Experiments for Multilingual Sentiment Analysis Using Machine Translation
Fault Detection in Wastewater Treatment Plants: Application of Autoencoders Models with Streaming Data
Differentiable Feature Selection, A Reparameterization Approach
Finding Local Groupings of Time Series
Identifying Over-represented Temporal Processes in Complex Networks
Causal Clustering for 2-Factor Measurement Models
MotiPlus and MotiSet: Discovering the Best Set of Motiflets in Time Series
Classification Cascades of Overlapping Feature Ensembles for Energy Time Series Data
Feature-Enhanced Probabilistic Models for Diffusion Network Inference
Self Hyper-parameter Tuning for Stream Classification Algorithms
Discovering Groups of Signals in In-Vehicle Network Traces for Redundancy Detection and Functional Grouping
Improving Meta-learning for Few-Shot Text Classification via Label Propagation
Gait-Based Biometrics System
Visual Mining of Spatial Time Series Data
Contrastive Representation Through Angle and Distance Based Loss for Partial Label Learning
Mining with Cover and Extension Operators
Searching for Relational Patterns in Data
Solving Problems with Visual Analytics: Challenges and Applications
A Two-Step Learning Approach for Solving Full and Almost Full Cold Start Problems in Dyadic Prediction
Going Offline: An Evaluation of the Offline Phase in Stream Clustering
Attribute Discovery and Rough Sets
A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection Using Compounded Corruptions
Mitigating Data Scarcity in Polymer Property Prediction via Multi-task Auxiliary Learning
Temporal Graph Based Incident Analysis System for Internet of Things
Clustering Rankings in the Fourier Domain
A Complementarity-Enhanced Mixture of Human-AI Teams for Decision-Making
Cooperative Bayesian Optimization for Imperfect Agents
A Systematic Comparison of Feature-Rich Probabilistic Classifiers for NER Tasks
Privacy Amplification via Iteration for Shuffled and Online PNSGD
PrUE: Distilling Knowledge from Sparse Teacher Networks
Towards a General Model for Intrusion Detection: An Exploratory Study
Leveraging Student Profiles and the Mamba Framework to Enhance Knowledge Tracing
Deep Spatiotemporal Clustering: A Temporal Clustering Approach for Multi-dimensional Climate Data
Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings
Probabilistic Latent-Factor Database Models
Time to Learn: Temporal Accelerators as an Embedded Deep Neural Network Platform
σ-GPTs: A New Approach to Autoregressive Models
Modeling a Web Forum Ecosystem into an Enriched Social Graph
Variance-Aware Noisy Training: Hardening DNNs Against Unstable Analog Computations
Learning Fast and Slow: Towards Inclusive Federated Learning
Pre-training Contextual Location Embeddings in Personal Trajectories via Efficient Hierarchical Location Representations
Algorithmic Factors Influencing Bias in Machine Learning
Habitual and Reflective Control in Hierarchical Predictive Coding
Estimating the Electrical Power Output of Industrial Devices with End-to-End Time-Series Classification in the Presence of Label Noise
A Critical Analysis of Variants of the AUC
Improving Temporal Knowledge Graph Reasoning with Hierarchical Semantic-Aware Contrastive Learning
Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding
Dual Color-Image Discriminators Adversarial Networks for Generating Artificial-SAR Colorized Images from SENTINEL-1 Images
Boosting Object Representation Learning via Motion and Object Continuity
Evaluating Transfer Learning Methods on Real-World Data Streams: A Case Study in Financial Fraud Detection
Self-distilled Pruning of Deep Neural Networks
Interactive Medical Miner: Interactively Exploring Subpopulations in Epidemiological Datasets
Combining Tag Recommendations Based on User History
ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information
Pedestrian Quantity Estimation with Trajectory Patterns
Copula PC Algorithm for Causal Discovery from Mixed Data
Semi-supervised Gaussian Process Ordinal Regression
Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM Tree
Markov Blanket Discovery in Positive-Unlabelled and Semi-supervised Data
Practical Bayesian Inverse Reinforcement Learning for Robot Navigation
Social Influence Attentive Neural Network for Friend-Enhanced Recommendation
Shift Happens: Adjusting Classifiers
PipeQS: Pipeline-Based Adaptive Quantization and Staleness-Aware Distributed GNN Training System
A Comparison of Propositionalization Strategies for Creating Features from Linked Open Data
Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning
DANCer: Dynamic Attributed Network with Community Structure Generator
A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain
SpecGreedy: Unified Dense Subgraph Detection
Ordinal Regression for Difficulty Prediction of StepMania Levels
Searching for Better Randomized Response Schemes for Privacy-Preserving Data Mining
Inferring Tie Strength in Temporal Networks
A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series
Diversity-Aware k-median: Clustering with Fair Center Representation
Analysing Customer Churn in Insurance Data - A Case Study
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
Defense-VAE: A Fast and Accurate Defense Against Adversarial Attacks
From Abstract Items to Latent Spaces to Observed Data and Back: Compositional Variational Auto-Encoder
Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs
Parallel Structural Graph Clustering
Erratum: Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals
Effective Version Space Reduction for Convolutional Neural Networks
Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information
Self-disclosure on Twitter During the COVID-19 Pandemic: A Network Perspective
Evolution Analysis of Large Graphs with Gradoop
Imputation of Non-participated Race Results
Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices
Decision-Theoretic Sparsification for Gaussian Process Preference Learning
Distance Metric Learning Revisited
Bayesian Active Learning for Censored Regression
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network
ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining
Semi-supervised Multi-label Classification - A Simultaneous Large-Margin, Subspace Learning Approach
BusWTE: Realtime Bus Waiting Time Estimation of GPS Missing via Multi-task Learning
Cage: A Hybrid Framework for Closed-Domain Conversational Agents
Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery
Structure-Preserving Gaussian Process Dynamics
Scalable Gaussian Process Models for Solar Power Forecasting
Hyperbolic Contrastive Learning with Model-Augmentation for Knowledge-Aware Recommendation
Parameterizing Federated Continual Learning for Reproducible Research
InFeRno - An Intelligent Framework for Recognizing Pornographic Web Pages
Why Did My Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data
Mining Weighted Association Rules for Fuzzy Quantitative Items
Time Constrained DL8.5 Using Limited Discrepancy Search
A Comparison of Two Approaches to Classify with Guaranteed Performance
Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
vMF Loss: Exploring a Scattered Intra-class Hypersphere for Few-Shot Learning
Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures
Expectation Propagation for Rating Players in Sports Competitions
Causal Inference on Multivariate and Mixed-Type Data
T-REX: Table - Refute or Entail eXplainer
Visualization for Streaming Telecommunications Networks
Forecasting Irregularly Sampled Time Series with Transformer Encoders
Improving an Association Rule Based Classifier
Geometry Preserving Multi-task Metric Learning
Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept
From Personalized to Hierarchically Structured Classifiers for Retrieving Music by Mood
Measuring Immigrants Adoption of Natives Shopping Consumption with Machine Learning
Exploiting the Earth's Spherical Geometry to Geolocate Images
Orange: From Experimental Machine Learning to Interactive Data Mining
Massively Parallel Feature Selection: An Approach Based on Variance Preservation
Modular Debiasing of Latent User Representations in Prototype-Based Recommender Systems
Preference-Based Meta-Learning using Dyad Ranking: Recommending Algorithms in Cold-Start Situations
GraphSVX: Shapley Value Explanations for Graph Neural Networks
Vec2Node: Self-Training with Tensor Augmentation for Text Classification with Few Labels
On the Consistency of Information Filters for Lazy Learning Algorithms
Semantic Text Classification of Emergent Disease Reports
A Progressive Resampling Algorithm for Finding Very Sparse Investment Portfolios
Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 11th, 2015
Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights
On Subgroup Discovery in Numerical Domains
Knowledge Distillation with Distribution Mismatch
Support Approximations Using Bonferroni-Type Inequalities
Identifiability of Model Properties in Over-Parameterized Model Classes
Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions
Improving Emotion Detection with Sub-clip Boosting
6MapNet: Representing Soccer Players from Tracking Data by a Triplet Network
A Practical Evaluation of Active Learning Approaches for Object Detection
Inductive Link Prediction with Interactive Structure Learning on Attributed Graph
Optimized Federated Learning on Class-Biased Distributed Data Sources
Improving the Quality of Rule-Based GNN Explanations
Class-Conditional Label Noise in Astroparticle Physics
Low Visibility Forecasting Using Numerical Weather Prediction Data
AMIE: Automatic Monitoring of Indoor Exercises
Mining for Opinions Across Domains: A Cross-Language Study
The Haar Wavelet Transform in the Time Series Similarity Paradigm
A Multi-modal Metric Learning Framework for Time Series kNN Classification
Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis
Discovering Bayesian Market Views for Intelligent Asset Allocation
Lambert Matrix Factorization
Tensor Factorization for Multi-relational Learning
Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data
Learning to Calibrate and Rerank Multi-label Predictions
SDE-KG: A Stochastic Dynamic Environment for Knowledge Graphs
Ordinal Aligned Domain Generalization for Sensor-Based Time Series Regression
Relaxation Labeling for Selecting and Exploiting Efficiently Non-local Dependencies in Sequence Labeling
Generating Dynamic Higher-Order Markov Models in Web Usage Mining
New Frontiers in Mining Complex Patterns - 6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Revised Selected Papers
Improved Identification of Imbalanced Multiple Annotation Intent Labels with a Hybrid BLSTM and CNN Model and Hybrid Loss Function
ADR: An Adversarial Approach to Learn Decomposed Representations for Causal Inference
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I
Multi-view Spectral Clustering on Conflicting Views
Co-clustering for Fair Recommendation
Stochastic One-Sided Full-Information Bandit
Generalized Inverse Reinforcement Learning with Linearly Solvable MDP
Online Network Source Optimization with Graph-Kernel MAB
Predicting the Potential of Professional Soccer Players
Mining Positive and Negative Association Rules: An Approach for Confined Rules
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part III