yusuke1997/dblp-id-title huggingface dataset:
Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization
STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process
On the Transferability of Neural Models of Morphological Analogies
Learning Data Set Similarities for Hyperparameter Optimization Initializations
Relation of Activity and Confidence When Training Deep Neural Networks
PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning
Interactive Visual Data Exploration with Subjective Feedback
Evaluating Negation with Multi-way Joins Accelerates Class Expression Learning
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes
Embodiment Adaptation from Interactive Trajectory Preferences
Graph Neural Networks for Automatic Addition of Optimizing Components in Printed Circuit Board Schematics
Linear Bandits in Unknown Environments
Detection of ADHD Based on Eye Movements During Natural Viewing
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model
Simultaneous Linear Connectivity of Neural Networks Modulo Permutation
Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks
Mining Rules of Multi-level Diagnostic Procedure from Databases
Structuring Domain-Specific Text Archives by Deriving a Probabilistic XML DTD
Detecting Public Influence on News Using Topic-Aware Dynamic Granger Test
A Bayesian Convolutional Neural Network for Robust Galaxy Ellipticity Regression
End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification
Understanding Adversarial Space Through the Lens of Attribution
A Systematic Approach for Tracking the Evolution of XAI as a Field of Research
Synthetic Oversampling of Multi-label Data Based on Local Label Distribution
Counterfactual Explanations for Recommendation Bias
SAViR-T: Spatially Attentive Visual Reasoning with Transformers
Self-supervised Graph Learning with Segmented Graph Channels
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
Text-Guided Dual Interaction for Multimodal Relation Extraction in Social Media
Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization
Deep Imbalanced Time-Series Forecasting via Local Discrepancy Density
Maintenance of Discovered Knowledge
Temporally Evolving Community Detection and Prediction in Content-Centric Networks
Non-stationary Environment Compensation Using Sequential EM Algorithm for Robust Speech Recognition
Text Mining from Migration Narratives
BellatrExplorer: An Interactive Random Forest Local Explainability Dashboard
Graph-Based Transduction with Confidence
Enhancing Siamese Neural Networks Through Expert Knowledge for Predictive Maintenance
Link Prediction in Multi-modal Social Networks
MetaREVEAL: RL-based Meta-learning from Learning Curves
An Empirical Comparison of Exact Nearest Neighbour Algorithms
Prequential AUC for Classifier Evaluation and Drift Detection in Evolving Data Streams
FinCPRG: A Bidirectional Generation Pipeline for Hierarchical Queries and Rich Relevance in Financial Chinese Passage Retrieval
Open Set Domain Adaptation Using Optimal Transport
A Differentially Private Kernel Two-Sample Test
Similarity Search for Multi-dimensional NMR-Spectra of Natural Products
A Two-Step Approach for the Prediction of Mood Levels Based on Diary Data
Efficient Sample Reuse in EM-Based Policy Search
A Merge Sort Based Ranking System for the Evaluation of Large Language Models
Linear Contextual Bandits with Hybrid Payoff: Revisited
On-Line Adaptive Filtering of Web Pages
Asking Generalized Queries to Ambiguous Oracle
Athlete Monitoring in Professional Road Cycling Using Similarity Search on Time Series Data
Fault Tolerant Regression for Sensor Data
Deriving Class Association Rules Based on Levelwise Subspace Clustering
Explainable Anomaly Detection System for Categorical Sensor Data in Internet of Things
Determination of Screening Descriptors for Chemical Reaction Databases
Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams
Long-Term Fairness in Ride-Hailing Platform
Identification of ECG Arrhythmias Using Phase Space Reconstruction
Learning Data Representations with Joint Diffusion Models
Individual Fairness with Group Awareness Under Uncertainty
DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis
Linear State-Space Model with Time-Varying Dynamics
FairFlow: An Automated Approach to Model-Based Counterfactual Data Augmentation for NLP
Multi-Task Learning with Group-Specific Feature Space Sharing
Improving Robustness and Flexibility of Concept Taxonomy Learning from Text
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning
The TwoKey Plot for Multiple Association Rules Control
Source Hypothesis Transfer for Zero-Shot Domain Adaptation
Classifier Evasion: Models and Open Problems
Estimating Precisions for Multiple Binary Classifiers Under Limited Samples
Model Reuse with Bike Rental Station Data
Learning to Aggregate Using Uninorms
Music Generation Using Bayesian Networks
An Empirical Study of Hyperparameter Importance Across Datasets
Cooperative Multi-agent Reinforcement Learning for Inventory Management
Fast and Exact Mining of Probabilistic Data Streams
A Unified Batch Selection Policy for Active Metric Learning
Behavioral Constraint Template-Based Sequence Classification
Classification with Sums of Separable Functions
Towards Precomputed 1D-Convolutional Layers for Embedded FPGAs
Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification
Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach
On the Null Distribution of the Precision and Recall Curve
Minimum Neighbor Distance Estimators of Intrinsic Dimension
Safe Exploration for Active Learning with Gaussian Processes
Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search
Certification of Model Robustness in Active Class Selection
Learning and Scaling Directed Networks via Graph Embedding
Spatial-Temporal Graph Sandwich Transformer for Traffic Flow Forecasting
Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data
Feature Extraction over Multiple Representations for Time Series Classification
Interactive Knowledge-Based Kernel PCA
Edit Constraints on Microaggregation and Additive Noise
Improving Micro-video Recommendation by Controlling Position Bias
Discovering Dynamic Communities in Interaction Networks
Generation of Rules from Incomplete Information Systems
Quantile Layers: Statistical Aggregation in Deep Neural Networks for Eye Movement Biometrics
Opinion Formation by Voter Model with Temporal Decay Dynamics
Handling KDD Process Changes by Incremental Replanning
Learning Binary Codes with Bagging PCA
A Mixed Information Source Approach for Biomedical Question Answering: MindLab at BioASQ 7B
Adaptive Model Rules from Data Streams
Quantum Machine Learning for Malware Classification
Maximum Margin Separations in Finite Closure Systems
Aggregating Independent and Dependent Models to Learn Multi-label Classifiers
Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification
Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising
Risk-Averse Matchings over Uncertain Graph Databases
Preserving Privacy in Data Mining via Importance Weighting
An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior
Effect of Metalearning on Feature Selection Employment
Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings
Speeding Up Recovery from Concept Drifts
Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization
Graph Rebasing and Joint Similarity Reconstruction for Cross-Modal Hash Retrieval
Neural Message Passing for Multi-label Classification
Learning Real-Time Automata from Multi-Attribute Event Logs
Multi-view Approach to Parkinson's Disease Quality of Life Data Analysis
Strength in Diversity: The Advance of Data Analysis
Max-Margin Weight Learning for Markov Logic Networks
A Blended Metric for Multi-label Optimisation and Evaluation
The KL-Divergence Between a Graph Model and its Fair I-Projection as a Fairness Regularizer
Multiple Manifolds Learning Framework Based on Hierarchical Mixture Density Model
Stable Vision Concept Transformers for Medical Diagnosis
LayeredLiNGAM: A Practical and Fast Method for Learning a Linear Non-gaussian Structural Equation Model
Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks
Lagrange Dual Decomposition for Finite Horizon Markov Decision Processes
Monitoring Emergency First Responders' Activities via Gradient Boosting and Inertial Sensor Data
Error Correcting Codes with Optimized Kullback-Leibler Distances for Text Categorization
Bi-matching Mechanism to Combat Long-tail Senses of Word Sense Disambiguation
Google Topics as a Way Out of the Cookie Dilemma?
Variance Reduced Stochastic Proximal Algorithm for AUC Maximization
TreeDiffusion: Hierarchical Generative Clustering for Conditional Diffusion
VisualSynth: Democratizing Data Science in Spreadsheets
Optimal Client Recommendation for Market Makers in Illiquid Financial Products
Coarse-DTW for Sparse Time Series Alignment
Smoothing Categorical Data
Towards Open-World Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach
A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction
Learning in Probabilistic Graphs Exploiting Language-Constrained Patterns
Maximal Closed Set and Half-Space Separations in Finite Closure Systems
Recommending Related Products Using Graph Neural Networks in Directed Graphs
SINAS: Suspect Investigation Using Offenders' Activity Space
On the Complexity of All ε-Best Arms Identification
Object Mining: A Practical Application of Data Mining for the Construction and Maintenance of Software Components
Sequence Generation with Target Attention
Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning
Exact Hybrid Covariance Thresholding for Joint Graphical Lasso
Learning an Affine Transformation for Non-linear Dimensionality Reduction
Preference-Based Policy Learning
An OPTICS Clustering-Based Anomalous Data Filtering Algorithm for Condition Monitoring of Power Equipment
Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density
Framework for Exploring and Understanding Multivariate Correlations
PowerCast: Mining and Forecasting Power Grid Sequences
Assessing the Uncertainty of the Text Generating Process Using Topic Models
A Declarative Framework for Constrained Clustering
Robust Principal Component Analysis by Reverse Iterative Linear Programming
Group Anomaly Detection Using Deep Generative Models
Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning
Strategic and Crowd-Aware Itinerary Recommendation
On the Robustness of Global Feature Effect Explanations
A U-Shaped Hierarchical Recommender by Multi-resolution Collaborative Signal Modeling
On the Need of Class Ratio Insensitive Drift Tests for Data Streams
Learning Explainable Representations of Malware Behavior
Meta-QSAR: Learning How to Learn QSARs
Linguistic Analysis of Stack Overflow Data: Native English vs Non-native English Speakers
Probabilistic Circuits with Constraints via Convex Optimization
Using Signature Files for Querying Time-Series Data
Data-Efficient Interactive Multi-objective Optimization Using ParEGO
DeepSolar Tracker: Towards Unsupervised Assessment with Open-Source Data of the Accuracy of Deep Learning-Based Distributed PV Mapping
Efficient Multi-start Strategies for Local Search Algorithms
KAFÈ: Kernel Aggregation for FEderated
Mutual Information Measure for Image Segmentation Using Few Labels
Incremental Training of a Recurrent Neural Network Exploiting a Multi-scale Dynamic Memory
New Frontiers in Mining Complex Patterns - Third International Workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers
Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery
Decision Tree Toolkit: A Component-Based Library of Decision Tree Algorithms
Mining Chess Playing as a Complex Process
Collaborative Interest-Aware Graph Learning for Group Identification
CircuitVQA: A Visual Question Answering Dataset for Electrical Circuit Images
NE-WNA: A Novel Network Embedding Framework Without Neighborhood Aggregation
Foveated Neural Computation
Inductive Generalized Zero-Shot Learning with Adversarial Relation Network
MultiNets: Web-Based Multilayer Network Visualization
Multi-task Learning for Features Extraction in Financial Annual Reports
Dyad Ranking Using A Bilinear Plackett-Luce Model
Monotone Sampling of Networks
The Role of Hierarchies in Exploratory Data Mining
Generating Social Network Features for Link-Based Classification
Mirror Descent for Metric Learning: A Unified Approach
MEGA: Multi-encoder GNN Architecture for Stronger Task Collaboration and Generalization
C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization
Inductive Logic Programming in Clementine
MFDG: A Multi-Factor Dialogue Graph Model for Dialogue Intent Classification
RAPID: Real-time Analytics Platform for Interactive Data Mining
An Auto-stopped Hierarchical Clustering Algorithm for Analyzing 3D Model Database
Real: A Representative Error-Driven Approach for Active Learning
PLSI: The True Fisher Kernel and beyond
Mr-SBC: A Multi-relational Naïve Bayes Classifier
A Bayesian Classifier for Learning from Tensorial Data
Mining Graph Evolution Rules
Automated Detection of Epidemics from the Usage Logs of a Physicians' Reference Database
Approximate Explanations for Classification of Histopathology Patches
SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery
Self-supervised Multi-task Representation Learning for Sequential Medical Images
String Sanitization: A Combinatorial Approach
DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software Ecosystem
Prediction of Tiers in the Ranking of Ice Hockey Players
Nowcasting Unemployment Rates with Smartphone GPS Data
PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks
Metalearning for Multiple-Domain Transfer Learning
DeepPE: Emulating Parameterization in Numerical Weather Forecast Model Through Bidirectional Network
Modeling Multi-factor and Multi-faceted Preferences over Sequential Networks for Next Item Recommendation
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines
Boosting for Unsupervised Domain Adaptation
L 0 -ARM: Network Sparsification via Stochastic Binary Optimization
Pitch-Related Identification of Instruments in Classical Music Recordings
Design Space Exploration of Time, Energy, and Error Rate Trade-offs for CNNs Using Accuracy-Programmable Instruction Set Processors
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling
A Practical Application of Artificial Intelligence Techniques for Legal Context Analysis
A Simple Exponential Family Framework for Zero-Shot Learning
SNNAP: Solver-Based Nearest Neighbor for Algorithm Portfolios
Gauss Shift: Density Attractor Clustering Faster Than Mean Shift
Versatile Decision Trees for Learning Over Multiple Contexts
Vision Transformers for Burned Area Delineation
Subgroup Discovery with Proper Scoring Rules
Early Active Learning with Pairwise Constraint for Person Re-identification
Engaging Older Adults at Meal-Time Through AI-Empowered Socially Assistive Robots
Interactive Visualization for Predictive Modelling with Decision Tree Induction
Fast Burst Correlation of Financial Data
Exploring Multiple Communities with Kernel-Based Link Analysis
Short-Term Electricity Consumption Forecast Using Datasets of Various Granularities
A Correspondence Between Maximal Complete Bipartite Subgraphs and Closed Patterns
Sequential Data Classification in the Space of Liquid State Machines
Beyond Outlier Detection: LookOut for Pictorial Explanation
Leveraging Spatial Abstraction in Traffic Analysis and Forecasting with Visual Analytics
Machine Learning Guided Optimization for Demand Responsive Transport Systems
Generalized Matrix Factorizations as a Unifying Framework for Pattern Set Mining: Complexity Beyond Blocks
Discovery of Ambiguous Patterns in Sequences: Application to Bioinformatics
Frequency Enhanced Pre-training for Cross-City Few-shot Traffic Forecasting
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference
Variational Bayesian Mixture of Robust CCA Models
Network-Based Disease Candidate Gene Prioritization: Towards Global Diffusion in Heterogeneous Association Networks
Adaptive XML Tree Classification on Evolving Data Streams
Pattern Teams
Principles of Data Mining and Knowledge Discovery, First European Symposium, PKDD '97, Trondheim, Norway, June 24-27, 1997, Proceedings
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks
GrINd: Grid Interpolation Network for Scattered Observations
SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training
How Early Can We Detect? Detecting Misinformation on Social Media Using User Profiling and Network Characteristics
Multiview Semi-supervised Learning for Ranking Multilingual Documents
Sentiment Classification with Supervised Sequence Embedding
Poisson Graphical Granger Causality by Minimum Message Length
Web-Induced Heterogeneous Transfer Learning with Sample Selection
Spectral Ranking with Covariates
Using the Web to Reduce Data Sparseness in Pattern-Based Information Extraction
Using Neural Network to Extract Knowledge from Database
Calibrate to Interpret
FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness
Semigeometric Tiling of Event Sequences
On Finer Control of Information Flow in LSTMs
Efficient Adaptive Spatial-Temporal Attention Network for Traffic Flow Forecasting
The Price of Labelling: A Two-Phase Federated Self-learning Approach
Estimating Dynamic Graphical Models from Multivariate Time-series Data
Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II
Financial Fraud Detection with Improved Neural Arithmetic Logic Units
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent
I See Dead People: Gray-Box Adversarial Attack on Image-to-Text Models
Sensorimotor Visual Perception on Embodied System Using Free Energy Principle
Efficient Distributed Decision Trees for Robust Regression
Argument Visualization and Narrative Approaches for Collaborative Spatial Decision Making and Knowledge Construction: A Case Study for an Offshore Wind Farm Project
Proceedings of MACLEAN: MAChine Learning for EArth ObservatioN Workshop co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2019), Würzburg, Germany, September 20, 2019
Boosting Nearest Neighbors for the Efficient Estimation of Posteriors
A Framework for Building pro-bono Data for Good Projects
Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering
Fast Approximate Text Document Clustering Using Compressive Sampling
Knowledge Distillation for Job Title Prediction and Project Recommendation in Open Source Communities
Deterministic Feature Selection for Regularized Least Squares Classification
Transductive Fire-Affected Area Segmentation Using False-Color Composite Data
Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability
Prediction of Happy Endings in German Novels
Preprocessing of Missing Values Using Robust Association Rules
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V
LLM Support for Real-Time Technical Assistance
Observational Logic Integrates Data Mining Based on Statistics and Neural Networks
Go with the Flow: Leveraging Physics-Informed Gradients to Solve Real-World Problems in Water Distribution Systems
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part V
Adaptive Certified Training: Towards Better Accuracy-Robustness Tradeoffs
RDF Knowledge Base Summarization by Inducing First-Order Horn Rules
Sampling Strategies for Representative Time Series in Load Flow Calculations
Privacy Risk for Individual Basket Patterns
"I Forgot About You": Exploring Multi-Label Unlearning (MLU) for Responsible Facial Recognition Systems
iDVS: An Interactive Multi-document Visual Summarization System
Annotated Suffix Tree Similarity Measure for Text Summarization
Application of Inductive Logic Programming to Structure-Based Drug Design
AB-STE: Adaptive Blended Gradient Estimation for Efficient Binarized Networks
Bi-tuning: Efficient Transfer from Pre-trained Models
Learning with Mixture Models: Concepts and Applications
Effect of Superpixel Aggregation on Explanations in LIME - A Case Study with Biological Data
Discovering Descriptive Tile Trees - By Mining Optimal Geometric Subtiles
Discovering Overlapping Communities of Named Entities
Simple, Scalable, and Stable Variational Deep Clustering
Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient Statistics
Mining Dense Subgraphs with Similar Edges
Shared Structure Learning for Multiple Tasks with Multiple Views
\mathtt OSLα : Online Structure Learning Using Background Knowledge Axiomatization
Formal Theory of Fun and Creativity
The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning
An Improved Multi-task Learning Approach with Applications in Medical Diagnosis
MinUS: Mining User Similarity with Trajectory Patterns
Finding Hidden Factors UsingIndependent Component Analysis
The ABC of Data: A Classifying Framework for Data Readiness
Knowledge-Powered Deep Learning for Word Embedding
Monitoring Short Term Changes of Infectious Diseases in Uganda with Gaussian Processes
Approximation of Frequency Queris by Means of Free-Sets
Within-Network Classification Using Local Structure Similarity
Compact Coding for Hyperplane Classifiers in Heterogeneous Environment
OMEGA: An Order-Preserving SubMatrix Mining, Indexing and Search Tool
A Context-Aware Approach to Detect Abnormal Human Behaviors
How Different is Stereotypical Bias Across Languages?
Linearly Constrained Weights: Reducing Activation Shift for Faster Training of Neural Networks
Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition
Multi-task Learning for User Engagement and Adoption in Live Video Streaming Events
A Crossroads for Hybrid Human-Machine Decision-Making
Refined Algorithms for Infinitely Many-Armed Bandits with Deterministic Rewards
Decomposable Families of Itemsets
Exploring the Generalizability of Transfer Learning for Camera Trap Animal Image Classification
On the Discovery of Weak Periodicities in Large Time Series
BatMan-CLR: Making Few-Shots Meta-learners Resilient Against Label Noise
Model Selection in Reinforcement Learning with General Function Approximations
Click-Aware Structure Transfer with Sample Weight Assignment for Post-Click Conversion Rate Estimation
Locating Faults in Photovoltaic Systems Data
Graph Diffusion Wasserstein Distances
Sequential Pattern Mining on Multimedia Data
Conditional Neural Relational Inference for Interacting Systems