yusuke1997/dblp-id-title huggingface dataset:
Structural Semantic Models for Automatic Analysis of Urban Areas
Applying Data Mining Techniques to Wafer Manufacturing
Contrastive Hierarchical Clustering
Robot Localization and Navigation Through Predictive Processing Using LiDAR
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets Using Deep Learning
Omiotis: A Thesaurus-Based Measure of Text Relatedness
A Meta-Learning Approach to One-Step Active-Learning
A Framework for Parallelizing Hierarchical Clustering Methods
Data Structures for Minimization of Total Within-Group Distance for Spatio-temporal Clustering
PICT: Precision-enhanced Road Intersection Recognition Using Cycling Trajectories
Data Integration for the Development of a Seismic Loss Prediction Model for Residential Buildings in New Zealand
Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I
Schema Mining: Finding Structural Regularity among Semistructured Data
Powershap: A Power-Full Shapley Feature Selection Method
Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction
Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback
Smurf-Based Anti-money Laundering in Time-Evolving Transaction Networks
Reducing Data Stream Sliding Windows by Cyclic Tree-Like Histograms
Scalable Backdoor Detection in Neural Networks
Continuous Upper Confidence Trees with Polynomial Exploration - Consistency
Walking Noise: On Layer-Specific Robustness of Neural Architectures Against Noisy Computations and Associated Characteristic Learning Dynamics
Constraint Selection for Semi-supervised Topological Clustering
APRIL: Active Preference Learning-Based Reinforcement Learning
COCOA: Compressed Continuity Analysis for Temporal Databases
Discriminative Interpolation for Classification of Functional Data
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Reinforcement Learning for Multi-Agent Stochastic Resource Collection
Ontology-Enabled Access Control and Privacy Recommendations
Human-Technology Relations in a Machine Learning Based Commuter App
WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care
Logic-Based Incremental Process Mining
Sentence Filtering for Information Extraction in Genomics, a Classification Problem
Temporal and Frequential Metric Learning for Time Series kNN Classification
Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-task and Inductive Transfer Learning
A Camera-Based System to Detect Driver Hands on the Steering Wheel in Semi-autonomous Vehicles
On-Site Gamma-Hadron Separation with Deep Learning on FPGAs
MMCNN: A Multi-branch Multi-scale Convolutional Neural Network for Motor Imagery Classification
AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling
Measuring the Stability of Feature Selection
Multi-Arm Active Transfer Learning for Telugu Sentiment Analysis
Analyzing Forward Robustness of Feedforward Deep Neural Networks with LeakyReLU Activation Function Through Symbolic Propagation
Tetrahedron: Barycentric Measure Visualizer
Bundle Recommendation with Item-Level Causation-Enhanced Multi-view Learning
Stream-Based Electricity Load Forecast
A Practical Deep Online Ranking System in E-commerce Recommendation
Improving Locality Sensitive Hashing Based Similarity Search and Estimation for Kernels
Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control
A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
Hidden Conditional Ordinal Random Fields for Sequence Classification
From the Data Mine to the Knowledge Mill: Applying the Principles of Lexical Analysis to the Data Mining and Knowledge Discovery Process
Inter-domain Multi-relational Link Prediction
An Experimental Investigation into the Evaluation of Explainability Methods for Computer Vision
Learning Bidirectional Similarity for Collaborative Filtering
Binary Domain Generalization for Sparsifying Binary Neural Networks
Providing Advice to Website Designers Towards Effective Websites Re-Organization
Towards Description of Block Model on Graph
Frequent Episode Mining Over the Latest Window Using Approximate Support Counting
Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain, September 13, 2021
Towards Better Evaluation of Multi-target Regression Models
Which Minimizer Does My Neural Network Converge To?
Selection of Numerical Weather Forecast Features for PV Power Predictions with Random Forests
Efficient Shared Near Neighbours Clustering of Large Metric Data Sets
Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions
A Network Architecture for Multi-Multi-Instance Learning
Physics Knowledge Discovery via Neural Differential Equation Embedding
The ACRE Crop-Weed Dataset for Benchmarking Weed Detection Models on Maize and Beans Fields
PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball Using Tracking Data
Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access
A Tree-Based Approach to Clustering XML Documents by Structure
Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias
Parallel Spectral Clustering
Scalable Moment-Based Inference for Latent Dirichlet Allocation
Coupling User Preference with External Rewards to Enable Driver-centered and Resource-aware EV Charging Recommendation
Ex-ThaiHate: A Generative Multi-task Framework for Sentiment and Emotion Aware Hate Speech Detection with Explanation in Thai
An Analysis of Interactions within and between Extreme Right Communities in Social Media
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training
Heuristic Measures of Interestingness
On Suppressing Range of Adaptive Stepsizes of Adam to Improve Generalisation Performance
Algorithm Selection via Meta-learning and Sample-based Active Testing
Online Bagging for Recommendation with Incremental Matrix Factorization
Discovery of Decision Rules from Databases: An Evolutionary Approach
Predicting Hourly Energy Consumption. Can Regression Modeling Improve on an Autoregressive Baseline?
Multi-relational Decision Tree Induction
AnswerArt - Contextualized Question Answering
Internet Document Filtering Using Fourier Domain Scoring
Consistency of Probabilistic Classifier Trees
Anomaly Detection: How to Artificially Increase Your F1-Score with a Biased Evaluation Protocol
Handling Delayed Feedback in Distributed Online Optimization: A Projection-Free Approach
Early Detection of Fake News with Multi-source Weak Social Supervision
Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases
Look before you leap: Some insights into learner evaluation with cross-validation
Big Data Analytics in the Social and Ubiquitous Context - 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers
Fair and Privacy-Preserving Synthetic Data Generation via Clustering-Based Variational Autoencoder and Adversarially Debiased Wasserstein Generative Adversarial Networks with Gradient Penalty
Embedding Monte Carlo Search of Features in Tree-Based Ensemble Methods
HAGAPS: Hierarchical Attentive Graph Neural Networks for Predicting Alternative Polyadenylation Site Quantification
RulEth: Genetic Programming-Driven Derivation of Security Rules for Automotive Ethernet
Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology
Variance-Based Defense Against Blended Backdoor Attacks
New Frontiers in Mining Complex Patterns - Second International Workshop, NFMCP 2013, Held in Conjunction with ECML-PKDD 2013, Prague, Czech Republic, September 27, 2013, Revised Selected Papers
Localized Random Shapelets
NWP Ensembles for Wind Energy Uncertainty Estimates
Learning with Random Learning Rates
ST-DenNetFus: A New Deep Learning Approach for Network Demand Prediction
Enriching Category Representations with LLMs Towards Robust Zero-Shot OOD Detection
Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions
Mitigating Discrimination in Insurance with Wasserstein Barycenters
Gaphyl: A Genetic Algorithms Approach to Cladistics
Comparison of Three Objective Functions for Conceptual Clustering
Duplicate Multi-modal Entities Detection with Graph Contrastive Self-training Network
Informativeness-Based Active Learning for Entity Resolution
Spatial-Temporal PDE Networks for Traffic Flow Forecasting
Exploratory Analysis of Text Collections Through Visualization and Hybrid Biclustering
Incremental Sensor Placement Optimization on Water Network
A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds
Data Mining in the Telecommunications Industry (Abstract)
Data Decomposition Based Learning for Load Time-Series Forecasting
A Graphical Model for Content Based Image Suggestion and Feature Selection
Approximate Consistency: Towards Foundations of Approximate Kernel Selection
Closed Sets for Labeled Data
Discovering Inter-Dimensional Rules in Dynamic Graphs
Effective Blending of Two and Three-way Interactions for Modeling Multi-relational Data
Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017
Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting
Minimal Shrinkage for Noisy Data Recovery Using Schatten-p Norm Objective
Machine Learning with Symbolic Methods and Knowledge Graphs co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Virtual, September 17, 2021
MatrixCalculus.org - Computing Derivatives of Matrix and Tensor Expressions
Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining
Learning from Stochastic Teacher Representations Using Student-Guided Knowledge Distillation
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IV
6VecLM: Language Modeling in Vector Space for IPv6 Target Generation
Do Protein Transformers Have Biological Intelligence?
Boosting Protein Language Models with Negative Sample Mining
Learning with Randomized Majority Votes
Kernel Polytope Faces Pursuit
Towards Interactive Feature Selection with Human-in-the-loop
A Dynamic Ensemble and Replaying Model for Online Marine Sensor Data Prediction
How Useful Is Graph Pooling for Node-Level Tasks?
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II
Machine Learning Approaches for Metagenomics
k -Version-Space Multi-class Classification Based on k -Consistency Tests
Pleiades: Subspace Clustering and Evaluation
Using Wikipedia for Cross-Language Named Entity Recognition
Scalable Adversarial Online Continual Learning
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VII
Future Designer - Generative AI Meets Interior Design
Midpoint Regularization: From High Uncertainty Training Labels to Conservative Classification Decisions
Improving Time-Series Rule Matching Performance for Detecting Energy Consumption Patterns
Learning to Perceive Two-Dimensional Displays Using Probabilistic Grammars
The Quest of Finding the Antidote to Sparse Double Descent
Mining Sequences of Temporal Intervals
Correlation Analysis for Determining the Potential of Home Energy Management Systems in Germany
Automated Financial Analysis Using GPT-4
Autonomous Visualization
Image Representation, Annotation and Retrieval with Predictive Clustering Trees
RE-GrievanceAssist: Enhancing Customer Experience Through ML-Powered Complaint Management
ML Training on a Tiny Microcontroller for a Self-adaptive Neural Network-Based DC Motor Speed Controller
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling
HIClass: Hyper-interactive Text Classification by Interactive Supervision of Document and Term Labels
Leveraging Automated Mixed-Low-Precision Quantization for Tiny Edge Microcontrollers
Distributed Generative Modelling with Sub-linear Communication Overhead
Hyper-parameter Optimization for Latent Spaces
Efficient Analysis of Transactional Data Using Graph Convolutional Networks
Reliable Classifications with Guaranteed Confidence Using the Dempster-Shafer Theory of Evidence
Warped Matrix Factorisation for Multi-view Data Integration
Kernel-Based Inductive Transfer
Smart Cities: How Data Mining and Optimization Can Shape Future Cities
Building Appliances Energy Performance Assessment
A Weighting Scheme for Tag Recommendation in Social Bookmarking Systems
MHDNE: Network Embedding Based on Multivariate Hawkes Process
Interpretable Models via Pairwise Permutations Algorithm
Graph-Based Discrete Differential Geometry for Critical Instance Filtering
Non-redundant Subgroup Discovery in Large and Complex Data
Flexible Recurrent Neural Networks
Zero-Shot Scene Graph Relation Prediction Through Commonsense Knowledge Integration
De Novo Molecular Design Enabled by Direct Preference Optimization and Curriculum Learning
Federated Frank-Wolfe Algorithm
Tractable Semi-supervised Learning of Complex Structured Prediction Models
On the Equivalence between Deep NADE and Generative Stochastic Networks
Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2013 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2013), Prague, Czech Republic, September 27th, 2013
Topics in Financial Filings and Bankruptcy Prediction with Distributed Representations of Textual Data
Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups
Undersampled Majority Class Ensemble for highly imbalanced binary classification
From Graphs to DAGs: A Low-Complexity Model and a Scalable Algorithm
Personalized Tag Recommendation for Images Using Deep Transfer Learning
Sparse Information Filter for Fast Gaussian Process Regression
MUMBO: MUlti-task Max-Value Bayesian Optimization
Towards Data Mining Without Information on Knowledge Structure
Solving Structured Sparsity Regularization with Proximal Methods
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I
Alignment-Based Topic Extraction Using Word Embedding
A Comparative Analysis of Temporal Long Text Similarity: Application to Financial Documents
On the Challenges and Practices of Reinforcement Learning from Real Human Feedback
Block CUR: Decomposing Matrices Using Groups of Columns
Rumour Detection via Zero-Shot Cross-Lingual Transfer Learning
Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlation
Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources
The Research on Vulnerability Analysis in OpenADR for Smart Grid
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
Accelerating RNN-Based Speech Enhancement on a Multi-core MCU with Mixed FP16-INT8 Post-training Quantization
Enhance Temporal Knowledge Graph Completion via Time-Aware Attention Graph Convolutional Network
Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks
Pointer-Guided Pre-training: Infusing Large Language Models with Paragraph-Level Contextual Awareness
Social Media as a Source of Sensing to Study City Dynamics and Urban Social Behavior: Approaches, Models, and Opportunities
Iterative Representation Learning for Entity Alignment Leveraging Textual Information
Mixed Integer Linear Programming for Optimizing a Hopfield Network
A Bayesian Markov Model for Station-Level Origin-Destination Matrix Reconstruction
Collaborative Learning Based Effective Malware Detection System
Geodesic Analysis on the Gaussian RKHS Hypersphere
Temporal PageRank
Characterizing Soccer Players' Playing Style from Match Event Streams
Collaborative Expert Recommendation for Community-Based Question Answering
Streaming Decision Trees for Lifelong Learning
Modeling the Temporal Nature of Human Behavior for Demographics Prediction
Exploring Word-Sememe Graph-Centric Chinese Antonym Detection
On the Distributional Convergence of Temporal Difference Learning
Intelligently Detecting Information Online-Weaponisation Trends (IDIOT)
Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model
A probabilistic approach for financial IoT data
Pre-trained Language Model for Biomedical Question Answering
OMBA: User-Guided Product Representations for Online Market Basket Analysis
Finding Interesting Pass Patterns from Soccer Game Records
A Unified Framework for Assessing Energy Efficiency of Machine Learning
Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part II
When Size Matters: Markov Blanket with Limited Bit Depth Conditional Mutual Information
Some Enhencements of Decision Tree Bagging
How Your Supporters and Opponents Define Your Interestingness
Lifelong Learning with Gaussian Processes
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance
Improving Classification with Pairwise Constraints: A Margin-Based Approach
Predicting the Outcome of ODI Cricket Matches: A Team Composition Based Approach
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), Grenoble, France, September 23, 2022
Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics
Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-view Deep Learning
RTG: A Recursive Realistic Graph Generator Using Random Typing
Proceedings of the 1st Workshop on Dynamic Networks and Knowledge Discovery, Barcelona, Spain, September 24, 2010
Anomaly Detection in Temporal Graph Data: An Iterative Tensor Decomposition and Masking Approach
Formation and Temporal Evolution of Social Groups During Coffee Breaks
Univariate Skeleton Prediction in Multivariate Systems Using Transformers
Estimating the Impact of Coupon Non-usage
Counterfactual Robustness: A Framework to Analyze the Robustness of Causal Generative Models Across Interventions
ReliefF for Hierarchical Multi-label Classification
Learning Distinct Features Helps, Provably
Co-clustering for Differentially Private Synthetic Data Generation
Supervised Contrastive Learning for Few-Shot Action Classification
Locally Linear Landmarks for Large-Scale Manifold Learning
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient
Clustering River Basins Using Time-Series Data Mining on Hydroelectric Energy Generation
Data Analysis in the Life Sciences - Sparking Ideas -
Evaluating Distance Measures for Image Time Series Clustering in Land Use and Cover Monitoring
Diffusion-Based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation
Boosting Generalized Few-Shot Learning by Scattering Intra-class Distribution
Automatic Detection of Non-Biological Artifacts in ECGs Acquired During Cardiac Computed Tomography
TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models
Example-dependent Basis Vector Selection for Kernel-Based Classifiers
Manifold Mixing for Stacked Regularization
On Discovering the Correlated Relationship between Static and Dynamic Data in Clinical Gait Analysis
Interactive Anonymization for Privacy aware Machine Learning
Privacy Preserving Semi-supervised Learning for Labeled Graphs
Approximation Error of Sobolev Regular Functions with Tanh Neural Networks: Theoretical Impact on PINNs
On the Effectiveness of Non-negative Matrix Factorization for Text Open-Set Recognition
TCuPGAN: A Novel Framework Developed for Optimizing Human-Machine Interactions in Citizen Science
Discovering Behavioural Patterns in Knowledge-Intensive Collaborative Processes
Batch Reinforcement Learning from Crowds
A Generalization of Forward-Backward Algorithm
Enhanced Web Page Content Visualization with Firefox
DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems
UCB-Driven Utility Function Search for Multi-objective Reinforcement Learning
Attack Transferability Characterization for Adversarially Robust Multi-label Classification
Mining Paraphrases from Self-anchored Web Sentence Fragments
Fast Algorithms for Mining Emerging Patterns
How to Measure Uncertainty in Uncertainty Sampling for Active Learning
Advancing Graph Counterfactual Fairness Through Fair Representation Learning
Learning from Partially Annotated Sequences
Bloomy Decision Tree for Multi-objective Classification
BMaD - A Boolean Matrix Decomposition Framework
HierCost: Improving Large Scale Hierarchical Classification with Cost Sensitive Learning
A Recurrent Neural Network Survival Model: Predicting Web User Return Time
A Skeleton-Based Approach to Learning Bayesian Networks from Data
CESI: Sparse Input Spatial Interpolation for Heterogeneous and Noisy Hybrid Wireless Sensor Networks
Recent Advances in Kernel-Based Graph Classification
Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification
Action-Rules: How to Increase Profit of a Company
Content-Based Filtering in On-Line Social Networks
Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions
A Hybrid Approach to Feature Selection
PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-regression AdvGAN
First International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@PKDD/ECML 2017, 22 September 2017, Skopje, Macedonia
Attention-Based Method for Categorizing Different Types of Online Harassment Language
Consequence-Aware Sequential Counterfactual Generation
Knowledge Discovery in Medical Multi-databases: A Rough Set Approach
ISOLLE: Locally Linear Embedding with Geodesic Distance
Estimating the Maximal Speed of Soccer Players on Scale
Towards Comparable Knowledge Distillation in Semantic Image Segmentation
Matrix Factorization as Search
Simulated Iterative Classification A New Learning Procedure for Graph Labeling
Evidential Nearest Neighbours in Active Learning
Data-Agnostic Pivotal Instances Selection for Decision-Making Models
Robust Dictionary Learning on the Hilbert Sphere in Kernel Feature Space
Noise Reduction in Distant Supervision for Relation Extraction Using Probabilistic Soft Logic
Towards More Reliable Transfer Learning
Users Behavioural Inference with Markovian Decision Process and Active Learning
Explaining Soccer Match Outcomes with Goal Scoring Opportunities Predictive Analytics
ECML PKDD 2018 Workshops - Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings
SEDiL: Software for Edit Distance Learning
Learning to Tag from Open Vocabulary Labels
Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories
OptiSim: A Hardware-Aware Optimization Space Exploration Tool for CNN Architectures
Effects of Boundary Conditions in Fully Convolutional Networks for Learning Spatio-Temporal Dynamics
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses