yusuke1997/dblp-id-title huggingface dataset:
Metric Learning: A Support Vector Approach
Latent Dirichlet Bayesian Co-Clustering
Detecting Driving Awareness
Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems
Enhancing Adversarial Training via Reweighting Optimization Trajectory
Bridged Refinement for Transfer Learning
Numbers in Multi-relational Data Mining
COVID Edge-Net: Automated COVID-19 Lung Lesion Edge Detection in Chest CT Images
Demand Forecasting in the Presence of Privileged Information
Data Streams and Data Synopses for Massive Data Sets
ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction
Parallel Multicut Segmentation via Dual Decomposition
Synchronization Based Outlier Detection
Distributed Algorithms to Find Similar Time Series
On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining
TF Boosted Trees: A Scalable TensorFlow Based Framework for Gradient Boosting
Score-Based Bayesian Skill Learning
ONE-M: Modeling the Co-evolution of Opinions and Network Connections
A New and Versatile Method for Association Generation
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining
Real-World Learning with Markov Logic Networks
Adequate Condensed Representations of Patterns
Parameter Estimation and Pattern Validation in Flock Mining
Towards Robot Skill Learning: From Simple Skills to Table Tennis
Using Part-Based Representations for Explainable Deep Reinforcement Learning
Hyperbolic Deep Keyphrase Generation
Techniques to Achieve Anonymization of Health Data: When are They Sufficient to Be Considered as Legally Complaint?
Quantifying Explanations of Neural Networks in E-Commerce Based on LRP
From Lab to Factory: Pitfalls and Guidelines for Self-/Unsupervised Defect Detection on Low-Quality Industrial Images
A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning
Cluster Algorithm for Social Choice
Shot Analysis in Different Levels of German Football Using Expected Goals
Conditional Ranking on Relational Data
Collaborative Tag Recommendation System based on Logistic Regression
Semi-Supervised Boosting for Multi-Class Classification
A Network Perspective on Stratification of Multi-Label Data
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II
Learning from Positive and Unlabeled Data under the Selected At Random Assumption
Link++: Adaptive Linking of Multiple Transportation Networks
SpectralLeader: Online Spectral Learning for Single Topic Models
Probabilistic Programming in Anglican
Context-Aware Predictions on Business Processes: An Ensemble-Based Solution
Learning Efficiently in Semantic Based Regularization
Data Science and Machine Learning at Scale
Matrix Completion Under Interval Uncertainty: Highlights
MASTFM: Meta-learning and Data Augmentation to Stress Test Forecasting Models
On Objective Measures of Rule Surprisingness
Using Inductive Logic Programming for Predicting Protein-Protein Interactions from Multiple Genomic Data
GRAM-SMOT: Top-N Personalized Bundle Recommendation via Graph Attention Mechanism and Submodular Optimization
Constructing Neural Forms for Hard-Constraint PINNs with Complex Dirichlet Boundaries
Country-Scale Exploratory Analysis of Call Detail Records Through the Lens of Data Grid Models
Nonparametric Bayesian Clustering Ensembles
Discovery of Surprising Exception Rules Based on Intensity of Implication
An Efficient Approach to Discovering Sequential Patterns in Large Databases
Active Supervised Domain Adaptation
Learning TSK Fuzzy Rules from Data Streams
Sequence-Graph Fusion Neural Network for User Mobile App Behavior Prediction
Learning Model Agnostic Explanations via Constraint Programming
Submodular Meta Data Compiling for Meta Optimization
Induction of Fuzzy Characteristic Rules
Text Mining at the Term Level
Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active Inference
Predictive Performance of Weghted Relative Accuracy
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroups
Incorporating Dependencies in Spectral Kernels for Gaussian Processes
Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification
Mining Big Data Streams with Apache SAMOA
Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part IV
Using Transduction and Multi-view Learning to Answer Emails
A Temporal Fusion Transformer for Long-Term Explainable Prediction of Emergency Department Overcrowding
Using Loglinear Clustering for Subcategorization Identification
Fast and Provably Effective Multi-view Classification with Landmark-Based SVM
Algorithmic Tools for Understanding the Motif Structure of Networks
Feature Selection for Transfer Learning
Many-to-Many Graph Matching: A Continuous Relaxation Approach
CasSampling: Exploring Efficient Cascade Graph Learning for Popularity Prediction
Automated ESG Report Analysis by Joint Entity and Relation Extraction
"Let's Eat Grandma": Does Punctuation Matter in Sentence Representation?
A Passage Retrieval Transformer-Based Re-Ranking Model for Truthful Consumer Health Search
Closed Non-derivable Itemsets
Classification of Dementia Types from Cognitive Profiles Data
Automating Layout Synthesis with Constructive Preference Elicitation
Reducing the Planning Horizon Through Reinforcement Learning
Memory-Enhanced Emotional Support Conversations with Motivation-Driven Strategy Inference
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks
Learning Łukasiewicz Logic Fragments by Quadratic Programming
On Improving Accuracy in Federated Learning Using GANs-Based Pre-training and Ensemble Learning
Peer and Authority Pressure in Information-Propagation Models
The Bitvector Machine: A Fast and Robust Machine Learning Algorithm for Non-linear Problems
The Role of Homophily and Popularity in Informed Decentralized Search
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense
Boosting Credit Risk Data Quality Using Machine Learning and eXplainable AI Techniques
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets
Penalized FTRL with Time-Varying Constraints
Improving Diversity in Black-Box Few-Shot Knowledge Distillation
ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models
Machine Learning for Crowdsourced Spatial Data
Learning to Solve Minimum Cost Multicuts Efficiently Using Edge-Weighted Graph Convolutional Neural Networks
Transferring Instances for Model-Based Reinforcement Learning
BioSegment: Active Learning segmentation for 3D electron microscopy imaging
Robust Domain Adaptation: Representations, Weights and Inductive Bias
Data Analytics for Renewable Energy Integration - Third ECML PKDD Workshop, DARE 2015, Porto, Portugal, September 11, 2015. Revised Selected Papers
Structurally Regularized Non-negative Tensor Factorization for Spatio-Temporal Pattern Discoveries
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies
Robust Anomaly Detection in Images Using Adversarial Autoencoders
Media Bias in German News Articles: A Combined Approach
Mining Medication-Effect Relations from Twitter Data Using Pre-trained Transformer Language Model
Real-Time Fine-Grained Freeway Traffic State Estimation Under Sparse Observation
Bootstrap Latents of Nodes and Neighbors for Graph Self-supervised Learning
Dynamic Ensemble Selection with Probabilistic Classifier Chains
Machine Learning Methods for Music Discovery and Recommendation
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
Explaining Fatigue in Runners Using Time Series Analysis on Wearable Sensor Data
Marvolo: Programmatic Data Augmentation for Deep Malware Detection
Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series
A Comparative Study on Machine Learning Algorithms for Assessing Energy Efficiency of Buildings
Getting Your Package to the Right Place: Supervised Machine Learning for Geolocation
Conversational XAI: Formalizing Its Basic Design Principles
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part I
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone
An Algorithm for Transfer Learning in a Heterogeneous Environment
Stable and Accurate Feature Selection
Active Learning for Data Streams Under Concept Drift and Concept Evolution
Local Interpretability of Random Forests for Multi-target Regression
Classes of Four-Fold Table Quantifiers
Explaining Text Clustering Results Using Semantic Structures
On the Noise Robustness of Analog Complex-Valued Neural Networks
Efficient Weight Learning for Markov Logic Networks
Information Marginalization on Subgraphs
Mining Human Mobility Data to Discover Locations and Habits
Context Abstraction to Improve Decentralized Machine Learning in Structured Sensing Environments
Feature Enhanced Capsule Networks for Robust Automatic Essay Scoring
Information Extraction From the GDELT Database to Analyse EU Sovereign Bond Markets
Structured Output Learning with Candidate Labels for Local Parts
Orthant Based Proximal Stochastic Gradient Method for ℓ 1 -Regularized Optimization
Accelerating Model Selection with Safe Screening for L 1-Regularized L 2-SVM
Principles of Data Mining and Knowledge Discovery, 6th European Conference, PKDD 2002, Helsinki, Finland, August 19-23, 2002, Proceedings
Message Scheduling Methods for Belief Propagation
Including Multi-feature Interactions and Redundancy for Feature Ranking in Mixed Datasets
Learning Detector of Malicious Network Traffic from Weak Labels
CAM-Based Methods Can See Through Walls
Cold-Start Recommendation for On-Demand Cinemas
A Heuristic Approach for Sensitive Pattern Hiding with Improved Data Quality
Unveiling the Hidden: Movie Genre and User Bias in Spoiler Detection
Efficient Confident Search in Large Review Corpora
Machine Learning as an Objective Approach to Understanding Music
Feature Selection for Value Function Approximation Using Bayesian Model Selection
TopoAttn-Nets: Topological Attention in Graph Representation Learning
Classifier Chains for Multi-label Classification
Enhancing Shortest-Path Graph Kernels via Graph Augmentation
Towards a Collaborative Platform for Advanced Meta-Learning in Healthcare Predictive Analytics
Finding the Optimal Network Depth in Classification Tasks
Collaborative Filtering on Data Streams
Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation
Node Representation Learning for Directed Graphs
Sublinear Algorithms for Penalized Logistic Regression in Massive Datasets
Optimal Teaching Curricula with Compositional Simplicity Priors
Consistency of Losses for Learning from Weak Labels
Circle Graphs: New Visualization Tools for Text-Mining
DetoxAI: A Python Toolkit for Debiasing Deep Learning Models in Computer Vision
Disagreement Options: Task Adaptation Through Temporally Extended Actions
Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges
Drilling a Large Corpus of Document Images of Geological Information Extraction
Propositionalisation and Aggregates
Preliminary Experimental Analysis of Reservoir Computing Approach for Balance Assessment
A Comparative Study of Community Detection Techniques for Large Evolving Graphs
Is Attention Interpretation? A Quantitative Assessment on Sets
A Latent Space Analysis of Editor Lifecycles in Wikipedia
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV
Toward a Fair Review-Management System
Data Mining for Robust Business Intelligence Solutions
Domain Adaptation with Regularized Optimal Transport
Feature Extraction from Sensor Data Streams for Real-Time Human Behaviour Recognition
Sobolev Training with Approximated Derivatives for Black-Box Function Regression with Neural Networks
Non-redundant Spectral Dimensionality Reduction
Classification of Anti-learnable Biological and Synthetic Data
Fine-Grained Explanations Using Markov Logic
On Optimizing Operational Efficiency in Storage Systems via Deep Reinforcement Learning
Equipment Health Indicator Learning Using Deep Reinforcement Learning
VulEXplaineR: XAI for Vulnerability Detection on Assembly Code
Multi-Objective Group Discovery on the Social Web
Automatic Design of Neuromarkers for OCD Characterization
A Deep Multi-task Approach for Residual Value Forecasting
Unsupervised Human Pose Estimation on Depth Images
Preference Mining: A Novel Approach on Mining User Preferences for Personalized Applications
Long-Term Learning for Web Search Engines
Sparsifying Instance Segmentation Models for Efficient Vision-Based Industrial Recycling
Unsupervised Anomaly Detection for Communication Networks: An Autoencoder Approach
Exponential Convergence of Gradient Methods in Concave Network Zero-Sum Games
Ensembling Shift Detectors: An Extensive Empirical Evaluation
Phenotype Prediction with Semi-supervised Classification Trees
Extracting Semantic Networks from Text Via Relational Clustering
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach
Producing Accurate Interpretable Clusters from High-Dimensional Data
Encouraging Sparsity in Neural Topic Modeling with Non-Mean-Field Inference
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions
A Cooperative Game Theoretic Approach to Prototype Selection
Measuring Football Players' On-the-ball Contributions from Passes during Games
Discovering Association Rules in Large, Dense Databases
Large Margin Learning of Bayesian Classifiers Based on Gaussian Mixture Models
Continuously Deep Recurrent Neural Networks
A Machine Learning Approach for Road Cycling Race Performance Prediction
Multi-channel Convolutional Neural Networks for Handling Multi-dimensional Semantic Trajectories and Predicting Future Semantic Locations
An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning
Accurate WiFi-Based Indoor Positioning with Continuous Location Sampling
The Local Convexification Method and Its Application to Learning Weakly Convex Boolean Functions
Change Detection in Multivariate Datastreams Controlling False Alarms
Meta-learning of Textual Representations
A Cluster-Level Semi-supervision Model for Interactive Clustering
Maps for Reasoning in Ultimate
TrafficFlowGAN: Physics-Informed Flow Based Generative Adversarial Network for Uncertainty Quantification
Online Learning in Adversarial Lipschitz Environments
Variants Analysis in Judicial Trials: Challenges and Initial Results
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I
Guiding Catalogue Enrichment with User Queries
Adverse Drug Reaction Mining in Pharmacovigilance Data Using Formal Concept Analysis
A Layered Dirichlet Process for Hierarchical Segmentation of Sequential Grouped Data
PICA: A Data-Driven Synthesis of Peer Instruction and Continuous Assessment
Clustering of exchange rates and their dynamics under different dependence measures
Probabilistic Wind Power Forecasting by Using Quantile Regression Analysis
Recurrent Greedy Parsing with Neural Networks
Frequent Generalized Subgraph Mining via Graph Edit Distances
Classifying Stem Cell Differentiation Images by Information Distance
Knowledge Discovery through Symbolic Regression with HeuristicLab
An Advert Creation System for 3D Product Placements
Predictive Distribution Matching SVM for Multi-domain Learning
Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda
Continuous Depth Recurrent Neural Differential Equations
Object Geolocation from Crowdsourced Street Level Imagery
MWPRanker: An Expression Similarity Based Math Word Problem Retriever
Measuring Unfairness Through Game-Theoretic Interpretability
Using Graph Neural Networks for the Detection and Explanation of Network Intrusions
HAGAN: Homophily-Aware Generative Adversarial Network for Graph Anomaly Detection
Identifying Influential Users by Their Postings in Social Networks
Experimental Design in Dynamical System Identification: A Bandit-Based Active Learning Approach
Charge Own Job: Saliency Map and Visual Word Encoder for Image-Level Semantic Segmentation
Low-Cost Optical Tracking of Soccer Players
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling
Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction
Correlation Clustering with Global Weight Bounds
ActivMetal: Algorithm Recommendation with Active Meta Learning
The Most Reliable Subgraph Problem
Probing Negative Sampling for Contrastive Learning to Learn Graph Representations
Using Barycenters as Aggregate Representations of Repetition-Based Time-Series Exercise Data
Offline Reinforcement Learning for Community-Acquired Pneumonia Management: A Feasibility Study
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers, Part I
LimGen: Probing the LLMs for Generating Suggestive Limitations of Research Papers
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification
MetaQuRe: Meta-learning from Model Quality and Resource Consumption
Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study
Time Series Classification in Dissimilarity Spaces
Scalable, High-Performance Data Mining with Parallel Processing
Speeding Up the Search for Optimal Partitions
Boosted Mean Shift Clustering
ViperCharts: Visual Performance Evaluation Platform
First-Order Bayes-Ball
Gradient Boosting Versus Mixed Integer Programming for Sparse Additive Modeling
Stance Classification of Tweets Using Skip Char Ngrams
Sentimental Analysis of COVID-19 Vaccine Tweets Using BERT+NBSVM
Generalised Linear Model for Football Matches Prediction
Semi-supervised Classification from Discriminative Random Walks
Adaptive Class Association Rule Mining for Human Activity Recognition
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation
Learning Complex Activity Preconditions in Process Mining
Bootstrap State Representation Using Style Transfer for Better Generalization in Deep Reinforcement Learning
Adversarial Imitation Learning with Controllable Rewards for Text Generation
Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss
Neural Control Variates for Monte Carlo Variance Reduction
Multidimensional Prediction Models When the Resolution Context Changes
Machine Learning for Robotics
Unsupervised Classification of Speaker Profiles as a Point Anomaly Detection Task
Online Structure Learning for Markov Logic Networks
Probability Estimation for Multi-class Classification Based on Label Ranking
Knowledge Discovery from Client-Server Databases
Graph Mining for Object Tracking in Videos
Multi-class and Multi-task Strategies for Neural Directed Link Prediction
Quality Guarantees for Autoencoders via Unsupervised Adversarial Attacks
Maximum Consistency Preferential Random Walks
A Virtualized Video Surveillance System for Public Transportation
Conditional Forecasting of Water Level Time Series with RNNs
BuildingWord-Emotion Mapping Dictionary for Online News
Influence of Graph Construction on Semi-supervised Learning
Link Prediction via Matrix Factorization
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII
Multimodal Tweet Sentiment Classification Algorithm Based on Attention Mechanism
Explaining Deviating Subsets Through Explanation Networks
Two-Way Analysis of High-Dimensional Collinear Data
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection
MASCOTS: Model-Agnostic Symbolic COunterfactual Explanations for Time Series
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II
FFBDNet: Feature Fusion and Bipartite Decision Networks for Recommending Medication Combination
Multi-spectral Gradient Residual Network for Haze Removal in Multi-sensor Remote Sensing Imagery
α-Clusterable Sets
Large Margin Multiclass Gaussian Classification with Differential Privacy
Learning from Little: Comparison of Classifiers Given Little Training
Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound
On Classifying Drifting Concepts in P2P Networks
PathOracle: A Deep Learning Based Trip Planner for Daily Commuters
Mining in the Phrasal Frontier
District Heating Substation Behaviour Modelling for Annotating the Performance
Configuration of Industrial Automation Solutions Using Multi-relational Recommender Systems
The Future is Different: Predicting Reddits Popularity with Variational Dynamic Language Models
Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process
Querying Inductive Databases via Logic-Based User-Defined Aggregates
Learning Socially Optimal Information Systems from Egoistic Users
On Saliency Maps and Adversarial Robustness
Evaluation of Ensemble Methods in Imbalanced Regression Tasks
OTTHO: On the Tip of My THOught
Robust Classification of Information Networks by Consistent Graph Learning
Finding Interpretable Concept Spaces in Node Embeddings Using Knowledge Bases
Symbolic Regression via Control Variable Genetic Programming
Limitations of Using Constraint Set Utility in Semi-Supervised Clustering
AutoPart: Parameter-Free Graph Partitioning and Outlier Detection
Site-Independent Template-Block Detection
Bayesian Optimization Combined with Successive Halving for Neural Network Architecture Optimization
Anti Imitation-Based Policy Learning
A Collaborative Filtering Tag Recommendation System Based on Graph
WikiSent: Weakly Supervised Sentiment Analysis through Extractive Summarization with Wikipedia
Learning to Teach Fairness-Aware Deep Multi-task Learning
A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks
Semantically Corroborating Neural Attention for Biomedical Question Answering
Nonintrusive Load Monitoring Based on Deep Learning
Multi-label Image Classification with Multi-scale Global-Local Semantic Graph Network
Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization
Prior Knowledge in Economic Applications of Data Mining
Physically Invertible System Identification for Monitoring System Edges with Unobservability
Towards Deeper GCNs: Alleviating Over-Smoothing via Iterative Training and Fine-Tuning
Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance
Black-Box Optimizer with Stochastic Implicit Natural Gradient
Reject and Cascade Classifier with Subgroup Discovery for Interpretable Metagenomic Signatures
Fast Hoeffding Drift Detection Method for Evolving Data Streams
Visual Analytics Methodology for Scalable and Privacy-Respectful Discovery of Place Semantics from Episodic Mobility Data
StreamKrimp: Detecting Change in Data Streams
Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting
Applying Machine Learning to Risk Assessment in Software Projects
Gradient Boosting Machine and LSTM Network for Online Harassment Detection and Categorization in Social Media
Improving Resampling-based Ensemble in Churn Prediction
Linear Modeling of the Adversarial Noise Space
Pseudo-Random Number Generation Using Generative Adversarial Networks