yusuke1997/dblp-id-title huggingface dataset:
WHODID: Web-Based Interface for Human-Assisted Factory Operations in Fault Detection, Identification and Diagnosis
Multi-intent Driven Contrastive Sequential Recommendation
Reprogramming GANs via Input Noise Design
AMQAN: Adaptive Multi-Attention Question-Answer Networks for Answer Selection
Deviation-Based Marked Temporal Point Process for Marker Prediction
Clifford Embeddings - A Generalized Approach for Embedding in Normed Algebras
Interpretable Hybrid-Rule Temporal Point Processes
Data Mining in Stabilometry: Application to Patient Balance Study for Sports Talent Mapping
Ordinal Label Proportions
Forecasting of Smart Meter Time Series Based on Neural Networks
Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform
MCTN: A Multi-Channel Temporal Network for Wearable Fall Prediction
Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning
Variable-Agnostic Causal Exploration for Reinforcement Learning
Hyper-Parameter Optimization for Privacy-Preserving Record Linkage
Aggregation Algorithm vs. Average For Time Series Prediction
Personality-Based User Modeling for Music Recommender Systems
Leveraging Plasticity in Incremental Decision Trees
Process Mining on a Public Procurement Dataset: A Case Study
Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering
Efficient Temporal Kernels Between Feature Sets for Time Series Classification
Randomized Operating Point Selection in Adversarial Classification
The Anatomy of SnakeT: A Hierarchical Clustering Engine for Web-Page Snippets
A CNN-Based Local-Global Self-attention via Averaged Window Embeddings for Hierarchical ECG Analysis
Analyzing Passing Sequences for the Prediction of Goal-Scoring Opportunities
Explaining Predictions from a Neural Network Ensemble One at a Time
Leveraging Homophily Under Local Differential Privacy for Effective Graph Neural Networks
The Top-k Frequent Closed Itemset Mining Using Top-k SAT Problem
Open Question Answering with Weakly Supervised Embedding Models
Identifying the Original Contribution of a Document via Language Modeling
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II
Hierarchical Active Learning with Proportion Feedback on Regions
Enhanced De-Essing via Neural Networks
Oracle-SAGE: Planning Ahead in Graph-Based Deep Reinforcement Learning
ProbLog2: Probabilistic Logic Programming
Network-based Measures for Predicting the Outcomes of Football Games
Ranking Interesting Subspaces for Clustering High Dimensional Data
Generating Multi-type Temporal Sequences to Mitigate Class-Imbalanced Problem
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part II
A Kernel-Learning Approach to Semi-supervised Clustering with Relative Distance Comparisons
Improving Autoregressive NLP Tasks via Modular Linearized Attention
Helping Your Docker Images to Spread Based on Explainable Models
Continual Rare-Class Recognition with Emerging Novel Subclasses
SynODC: Utilizing the Syntactic Structure for Outlier Detection in Categorical Attributes
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing
MONIC and Followups on Modeling and Monitoring Cluster Transitions
A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning
FlowFrontNet: Improving Carbon Composite Manufacturing with CNNs
Quantifying Node-Based Core Resilience
Robust Regression via Model Based Methods
Who is at Risk? Analyzing the Risk of Radicalization Among Reddit Users
Learnable Masked Tokens for Improved Transferability of Self-supervised Vision Transformers
Ontology Alignment Based on Word Embedding and Random Forest Classification
Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering
Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics
Cascade RSVM in Peer-to-Peer Networks
Combining Gaussian Processes with Neural Networks for Active Learning in Optimization
Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction
Iterated Matrix Reordering
Subspace Clustering Based Analysis of Neural Networks
Detecting Events in Evolving Social Networks through Node Centrality Analysis
SBAD: Sequence Based Attack Detection via Sequence Comparison
On the Generalization of Neural Combinatorial Optimization Heuristics
Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy
Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs
Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs
Gradient Similarity Surgery in Multi-task Deep Learning
Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data
Celebrity Watch: Browsing News Content by Exploiting Social Intelligence
M-Flash: Fast Billion-Scale Graph Computation Using a Bimodal Block Processing Model
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors
A Benchmark to Evaluate LLMs' Proficiency on Italian Student Competencies
Zero-Shot Detection of LLM-Generated Code via Approximated Task Conditioning
Taxonomy Formation by Approximate Equivalence Relations, Revisited
Utility-Based Regression
Improving an Accuracy of ANN-Based Mesoscale-Microscale Coupling Model by Data Categorization: With Application to Wind Forecast for Offshore and Complex Terrain Onshore Wind Farms
Proceedings of the 1st Workshop on Linked Data for Knowledge Discovery co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Nancy, France, September 19th, 2014
Faithful Explanations for Graph Classification Using Logic
Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine
Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation
Bootstrapping Information Extraction from Semi-structured Web Pages
Towards Flexibility Detection in Device-Level Energy Consumption
Fast Variational Bayesian Linear State-Space Model
A Novel Incremental Covariance-Guided One-Class Support Vector Machine
Optimal String Mining Under Frequency Constraints
Fault Prognostics for the Predictive Maintenance of Wind Turbines: State of the Art
CardioWheel: ECG Biometrics on the Steering Wheel
Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-Regenerative Life Support System Telemetry
Effective Pruning Techniques for Mining Quasi-Cliques
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits
Context-Aware Location Prediction
FUSE: Multi-faceted Set Expansion by Coherent Clustering of Skip-Grams
Multiple-Aspect Analysis of Semantic Trajectories - First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings
Pool-Based Agnostic Experiment Design in Linear Regression
Fast Gradient Boosting Decision Trees with Bit-Level Data Structures
Learning When to Observe: A Frugal Reinforcement Learning Framework for a High-Cost World
The Next Frontier: AI We Can Really Trust
Efficient and Numerically Stable Sparse Learning
Adversarial Representation Learning with Closed-Form Solvers
Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance
FDTI: Fine-Grained Deep Traffic Inference with Roadnet-Enriched Graph
Graph Neural Networks for Jamming Source Localization
Evolutive Deep Models for Online Learning on Datastreams with no Storage
Adjustment Criteria for Recovering Causal Effects from Missing Data
Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply Chains
Machine Learning as Surrogate to Building Performance Simulation: A Building Design Optimization Application
HetCAN: A Heterogeneous Graph Cascade Attention Network with Dual-Level Awareness
A Propositional Approach to Textual Case Indexing
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction
Multitask Recalibrated Aggregation Network for Medical Code Prediction
ChordPrompt: Orchestrating Cross-Modal Prompt Synergy for Multi-domain Incremental Learning in CLIP
Context-Based Similarity Measures for Categorical Databases
Data Preprocessing and Dynamic Ensemble Selection for Imbalanced Data Stream Classification
Probabilistic Active Learning with Structure-Sensitive Kernels
A Route-Affecting Region Based Approach for Feature Extraction in Transportation Route Planning
InVis: A Tool for Interactive Visual Data Analysis
XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features
Privacy-Preserving Collaborative Filtering on Vertically Partitioned Data
Right on Time: Revising Time Series Models by Constraining Their Explanations
Data Streaming with Affinity Propagation
Integrating Pattern Mining in Relational Databases
When Humans and AI Collide
Balanced and Token-Efficient Summarization of User Reviews via Stratified Sampling and Large Language Models
Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering
The Pronciple of Transformation between Efficiency and Effectiveness: Towards a Fair Evaluation of the Cost-Effectiveness of KDD Techniques
Online Learning of Weighted Relational Rules for Complex Event Recognition
Trustworthy Hybrid Decision-Making
A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Discovering and Visualizing Tactics in a Table Tennis Game Based on Subgroup Discovery
Two-Stage Temporal Knowledge Graph Completion Based on Reinforcement Learning
An Efficiently Computable Support Measure for Frequent Subgraph Pattern Mining
Feature Clustering for Extreme Events Analysis, with Application to Extreme Stream-Flow Data
Clustering Via Local Regression
A Scaled-Correlation Based Approach for Defining and Analyzing Functional Networks
Finding Community Topics and Membership in Graphs
Multiple Hypergraph Learning for Ephemeral Group Recommendation
Hierarchical Information-Guided Spatio-Temporal Mamba for Stock Time Series Forecasting
Privacy Preserving Blocking and Meta-Blocking
Enhancing Summarization with Text Classification via Topic Consistency
Transparency and Predicive Power: Explaining Complex Classification Models
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VI
Measuring Constraint-Set Utility for Partitional Clustering Algorithms
Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs
Unsupervised Signature Extraction from Forensic Logs
Multimodal Nonlinear Filtering Using Gauss-Hermite Quadrature
Contrastive Learning Enhanced Diffusion Model for Improving Tropical Cyclone Intensity Estimation with Test-Time Adaptation
Splitting Algorithms for Federated Learning
Introducing Pyra: A High-Level Linter for Data Science Software
Clustering Large, Multi-level Data Sets: An Apporach Based on Kohonen Self Organizing Maps
Federated Learning of Oligonucleotide Drug Molecule Thermodynamics with Differentially Private ADMM-Based SVM
Scoring and Classifying with Gated Auto-Encoders
Imitation Learning with Sinkhorn Distances
Privacy Preserving Client/Vertical-Servers Classification
FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios
Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection
Latent Structure Pattern Mining
Off-the-Grid: Fast and Effective Hyperparameter Search for Kernel Clustering
Fourier-Enhanced Adaptive Manifold Latent Feature Analysis for Spatiotemporal Signal Recovery
Scavenger - A Framework for Efficient Evaluation of Dynamic and Modular Algorithms
Adaptive Ensembles for Evolving Data Streams - Combining Block-Based and Online Solutions
Cost Sensitive Discretization of Numeric Attributes
Unsupervised Learning: Self-aggregation in Scaled Principal Component Space
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part III
SMACE: A New Method for the Interpretability of Composite Decision Systems
Sparse Horseshoe Estimation via Expectation-Maximisation
Hierarchical Sparse Dictionary Learning
Discovery of Approximate Medical Knowledge Based on Rough Set Model
Beyond Blocks: Hyperbolic Community Detection
Learning with L q<1 vs L 1 -Norm Regularisation with Exponentially Many Irrelevant Features
Location Prediction of Mobile Phone Users Using Apriori-Based Sequence Mining with Multiple Support Thresholds
Density-Aware Walks for Coordinated Campaign Detection
NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification
Sparse Transformer Hawkes Process for Long Event Sequences
A Unified Contrastive Loss for Self-training
Minimizing Grid Interaction of Solar Generation and DHW Loads in nZEBs Using Model-Free Reinforcement Learning
Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions
Predicting Negative Side Effects of Surgeries Through Clustering
Speeding Up Feature Subset Selection Through Mutual Information Relevance Filtering
An LLM-Based Decision Support System for Strategic Decision-Making
Towards Few-Shot Self-explaining Graph Neural Networks
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
Revisit Behavior in Social Media: The Phoenix-R Model and Discoveries
Solving Relational MDPs with Exogenous Events and Additive Rewards
Invertible Manifold Learning for Dimension Reduction
ClowdFlows: A Cloud Based Scientific Workflow Platform
Concept of a Rule-based Configurator for Auto-WEKA Using OpenML
A Connectionist Approach to Structural Simiarity Determination as a Basis of Clustering, Classification and Feature Detection
An Alternating Direction Method for Dual MAP LP Relaxation
Automated Search for Deep Neural Network Inference Partitioning on Embedded FPGA
Properties and Benefits of Calibrated Classifiers
TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement
Get a Human-In-The-Loop: Feature Engineering via Interactive Visualizations
An Experiment on Knowledge Discovery in Chemical Databases
Towards Association Rules with Hidden Variables
Model-Based Clustering with HDBSCAN
Discriminative Experimental Design
Who Is Going to Get Hurt? Predicting Injuries in Professional Soccer
STARSS: A Spatio-Temporal Action Rating System for Soccer
Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction
Understanding the User: Personomy Translation for Tag Recommendation
Non-IID Distributed Learning with Optimal Mixture Weights
TIGTEC: Token Importance Guided TExt Counterfactuals
Deep Convolutional Gaussian Processes
Measuring Domain Portability and Error Propagation in Biomedical QA
A Novel Framework for Online Sales Burst Prediction
Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information
Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE
Online Partial Label Learning
Khiops CoViz: A Tool for Visual Exploratory Analysis of k-Coclustering Results
Viability of Future Actions: Robust Safety in Reinforcement Learning via Entropy Regularization
Differentially Private Projected Histograms: Construction and Use for Prediction
State Representation Learning for Goal-Conditioned Reinforcement Learning
Multi-view Generative Adversarial Networks
NDSE: Instance Generation for Classification by Given Meta-Feature Description
A Study on Imbalanced Data Streams
Unsupervised Riemannian Clustering of Probability Density Functions
Evaluating Vision Transformer Models for Visual Quality Control in Industrial Manufacturing
Clustering Distributed Homogeneous Datasets
Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation
Modeling Winner-Take-All Competition in Sparse Binary Projections
Trust Assessment on Streaming Data: A Real Time Predictive Approach
Structured Prediction of Sequences and Trees Using Infinite Contexts
Detecting Evasion Attacks in Deployed Tree Ensembles
Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective Inference
Industrializing Data Mining, Challenges and Perspectives
Association Rules for Expressing Gradual Dependencies
Efficient Rank-one Residue Approximation Method for Graph Regularized Non-negative Matrix Factorization
Enhancing Dynamic Control of Inertial District Energy Networks Through a Physics-Informed State-Space Model
Different Aggregation Strategies for Generically Contextualized Sentiment Lexicons
Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold
Finding Dense Subgraphs in Relational Graphs
Share Based Measures for Itemsets
UNCC Biomedical Semantic Question Answering Systems. BioASQ: Task-7B, Phase-B
Methods for Automatic Machine-Learning Workflow Analysis
Pharos: Query-Driven Schema Inference for the Semantic Web
Structured Apprenticeship Learning
Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm
Heterogeneity Breaks the Game: Evaluating Cooperation-Competition with Multisets of Agents
Minimal k -Free Representations of Frequent Sets
Adaptively Learning to Recognize Symbols in Handwritten Early Music
Sample and Expand: Discovering Low-Rank Submatrices With Quality Guarantees
Quantifying Robustness to Adversarial Word Substitutions
Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images
Stealing Data from Active Party in Vertical Split Learning
Measuring Stakeholders' Perceptions of Cybersecurity for Renewable Energy Systems
A Generic and Model-Agnostic Exemplar Synthetization Framework for Explainable AI
Exploratory Analysis of Biochemical Processes Using Hybrid Modeling Methods
ProcK: Machine Learning for Knowledge-Intensive Processes
Viral Marketing for Product Cross-Sell through Social Networks
Supporting Information Spread in a Social Internetworking Scenario
EM-SEC: Efficient Multi-head Set-Valued Evidential Classification
Weight-Rounding Error in Deep Neural Networks
The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks
Automatic Categorization of Human-Coded and Evolved CoreWar Warriors
U-statistics on network-structured data with kernels of degree larger than one
Assessing Privacy Risk in Retail Data
Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions
Proceedings of ECML-PKDD 2020 ChAT Discovery Challenge on Chat Analytics for Twitch co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020 (ECML-PKDD 2020), Ghent, Belgium (virtual due to Covid-19 pandemic), September 18, 2020
Calibrating User Response Predictions in Online Advertising
A Scalable Solution for the Extended Multi-channel Facility Location Problem
Fairness in Multi-Task Learning via Wasserstein Barycenters
Cross-Domain Recommendation via Cluster-Level Latent Factor Model
Modeling Short-Term Energy Load with Continuous Conditional Random Fields
Revealing Similar Semantics Inside CNNs: An Interpretable Concept-Based Comparison of Feature Spaces
An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations
ConCAD: Contrastive Learning-Based Cross Attention for Sleep Apnea Detection
Vector Field Learning via Spectral Filtering
Efficient Processing of Ranked Queries with Sweeping Selection
On Feature Selection, Bias-Variance, and Bagging
How to Measure Energy Consumption in Machine Learning Algorithms
SALAS: Supervised Aspect Learning Improves Abstractive Multi-document Summarization Through Aspect Information Loss
FB2vec: A Novel Representation Learning Model for Forwarding Behaviors on Online Social Networks
Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB
Assessing the Multi-labelness of Multi-label Data
The ESPRIT Project CreditMine and Its Relevance for the Internet Market
Semi-supervised Semantic Visualization for Networked Documents
Pitch Proposal: Recommenders with a Mission - Assessing Diversity in News Recommendations
CET: A Tool for Creative Exploration of Graphs
Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations
Follow Your Path: A Progressive Method for Knowledge Distillation
Using Reinforcement Learning to Conceal Honeypot Functionality
Exploiting Temporal Convolution for Activity Prediction in Process Analytics
Reparameterized Sampling for Generative Adversarial Networks
Estimating Treatment Effects Under Heterogeneous Interference
Local Lanczos Spectral Approximation for Community Detection
DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery
Modeling Sequential Preferences with Dynamic User and Context Factors
Privacy in Web Search Query Log Mining
Improving Tiled Evolutionary Adversarial Attack
A Shapley Value Approach for Influence Attribution
Enriching Visual with Verbal Explanations for Relational Concepts - Combining LIME with Aleph
Meta-HRNet: A High Resolution Network for Coarse-to-Fine Few-Shot Classification
Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem
Simple and Effective Graph Autoencoders with One-Hop Linear Models
Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs
SS-HIDA: Semi-Supervised Heterogeneous Image Domain Adaptation
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings
A New Framework for Classifying Probability Density Functions
On the Non-associativity of Analog Computations
SVEBI: Towards the Interpretation and Explanation of Spiking Neural Networks
Bitpaths: Compressing Datasets Without Decreasing Predictive Performance
SMOGN: a Pre-processing Approach for Imbalanced Regression
Privately Computing a Distributed k-nn Classifier
A Baseline Generative Probabilistic Model for Weakly Supervised Learning
Fast Proximal Gradient Methods with Node Pruning for Tree-Structured Sparse Regularization
SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization
Bagging for Biclustering: Application to Microarray Data
A Unifying View of Multiple Kernel Learning
Tree 2 - Decision Trees for Tree Structured Data
TRUMIT: A Tool to Support Large-Scale Mining of Text Association Rules
The Discrete Basis Problem
Enhancing Robustness of Graph Convolutional Networks via Dropping Graph Connections
Learning from Crowds via Joint Probabilistic Matrix Factorization and Clustering in Latent Space
K-Clique-Graphs for Dense Subgraph Discovery
A Unified Spectral Rotation Framework Using a Fused Similarity Graph
Constructing (Almost) Phylogenetic Trees from Developmental Sequences Data
Exploiting History Data for Nonstationary Multi-armed Bandit
Attentive Multi-task Deep Reinforcement Learning
Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices
TransT: Type-Based Multiple Embedding Representations for Knowledge Graph Completion
Parallel Knowledge Discovery Using Domain Generalization Graphs
XferNAS: Transfer Neural Architecture Search
Visual Terrain Analysis of High-Dimensional Datasets
curr2vib: Modality Embedding Translation for Broken-Rotor Bar Detection
Overcoming Fragmentation in Decision Trees Through Attribute Value Grouping
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations
A Comparison of Progressive and Iterative Centroid Estimation Approaches Under Time Warp
Sign Constrained Rectifier Networks with Applications to Pattern Decompositions
Federated Time Series Generation on Feature and Temporally Misaligned Data