yusuke1997/dblp-id-title huggingface dataset:
Unsupervised and Active Learning Using Maximin-Based Anomaly Detection
Convex Factorization Machines
Diffusion Model with Selective Attention for Temporal Knowledge Graph Reasoning
Topic Learning from Few Examples
Multi-target Regression via Random Linear Target Combinations
Online Adaptive Multivariate Time Series Forecasting
Hate Speech Detection in Clubhouse
A Comparison of Batch and Incremental Supervised Learning Algorithms
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI
RoADS: A Road Pavement Monitoring System for Anomaly Detection Using Smart Phones
A Source Separation Approach to Temporal Graph Modelling for Computer Networks
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting
Finding Coherent Node Groups in Directed Graphs
Cost Sensitive Time-Series Classification
Categorizing Online Harassment on Twitter
Predictive Efficacy of a New Association Football League Format in Polish Ekstraklasa
Framework to Evaluate Deep Learning Algorithms for Edge Inference and Training
End-to-End Learning for Prediction and Optimization with Gradient Boosting
Migrating Models: A Decentralized View on Federated Learning
Active Learning with Evolving Streaming Data
Taxonomy-Driven Lumping for Sequence Mining
Graph Regularized Transductive Classification on Heterogeneous Information Networks
Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms co-located with the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases, AutoML@PKDD/ECML 2017, Skopje, Macedonia, September 22, 2017
Evasion Attacks against Machine Learning at Test Time
Adaptive Boosting for Transfer Learning Using Dynamic Updates
Forest-Based Point Process for Event Prediction from Electronic Health Records
Kanopy: Analysing the Semantic Network around Document Topics
Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization
Solar Energy Forecasting and Optimization System for Efficient Renewable Energy Integration
Precise Weather Parameter Predictions for Target Regions via Neural Networks
Wages of Wins: Could an Amateur Make Money from Match Outcome Predictions?
GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs
Hough Transform as a Tool for the Classification of Vehicle Speed Changes in On-Road Audio Recordings
TempoBiGen: A Curated Generative Model for Healthcare Mobility Logs with Visit Duration
#MeTooMaastricht: Building a Chatbot to Assist Survivors of Sexual Harassment
Sparse Kernel-SARSA(λ) with an Eligibility Trace
Enhancing HVAC Control Efficiency: A Hybrid Approach Using Imitation and Reinforcement Learning
Fast Near Neighbor Search in High-Dimensional Binary Data
Indexed Bit Map (IBM) for Mining Frequent Sequences
Fast Outlier Detection in High Dimensional Spaces
Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures
Relational Differential Prediction
Online Regression with Controlled Label Noise Rate
SPOT: A Framework for Selection of Prototypes Using Optimal Transport
Automation of Leasing Vehicle Return Assessment Using Deep Learning Models
Finding Spatial Clusters
Top-N Recommendation via Joint Cross-Domain User Clustering and Similarity Learning
Peak-Jumping Frequent Itemset Mining Algorithms
Selecting Information Diffusion Models over Social Networks for Behavioral Analysis
Fast Extraction of Locally Optimal Patterns Based on Consistent Pattern Function Variations
Topy: Real-Time Story Tracking via Social Tags
Automated Data Transformation with Inductive Programming and Dynamic Background Knowledge
Practical Open-Loop Optimistic Planning
Mining Frequent Connected Subgraphs Reducing the Number of Candidates
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes
Scaling Multi-label Conformal Prediction with Label Interactions for a Large Number of Labels
Boosting Long-Tail Data Classification with Sparse Prototypical Networks
Recognition of Agents Based on Observation of Their Sequential Behavior
Efficient Score-Based Learning of Equivalence Classes of Bayesian Networks
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them
Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation
Principles of Data Mining and Knowledge Discovery, 4th European Conference, PKDD 2000, Lyon, France, September 13-16, 2000, Proceedings
Sub-sampling for Multi-armed Bandits
Two Step graph-based semi-supervised Learning for Online Auction Fraud Detection
Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression
Machine Learning Challenges for Single Cell Data
Familiar Feelings: Listener-Rated Familiarity in Music Emotion Recognition
Federated Learning with Neural Graphical Models
ConGCN: Factorized Graph Convolutional Networks for Consensus Recommendation
Analyzing Word Frequencies in Large Text Corpora Using Inter-arrival Times and Bootstrapping
FedRNL: Federated Rationalization with Soft Parameter Sharing
Time Aspect in Making an Actionable Prediction of a Conversation Breakdown
When is Undersampling Effective in Unbalanced Classification Tasks?
Extracting Trajectories through an Efficient and Unifying Spatio-temporal Pattern Mining System
Using Stochastic Methods to Setup High Precision Experiments
Surprising Patterns for the Call Duration Distribution of Mobile Phone Users
Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule
A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases
Understanding Rumen Methanogen Interactions in Sheep Using Machine Learning
Big Data Financial Sentiment Analysis in the European Bond Markets
Be Certain of How-to before Mining Uncertain Data
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
Mining Audio Data for Multiple Instrument Recognition in Classical Music
K-Subspace Clustering
Routine Bandits: Minimizing Regret on Recurring Problems
CityFlowER: An Efficient and Realistic Traffic Simulator with Embedded Machine Learning Models
Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization
Representative Association Rules and Minimum Condition Maximum Consequence Association Rules
Model Monitoring and Dynamic Model Selection in Travel Time-Series Forecasting
Unsupervised Surrogate Anomaly Detection
Scalable and Interpretable One-Class SVMs with Deep Learning and Random Fourier Features
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IX
How to Pre-train Your Model? Comparison of Different Pre-training Models for Biomedical Question Answering
Exploring Cell-Based Neural Architectures for Embedded Systems
Clustering underlying stock trends via non-negative matrix factorization
Modeling Relations and Their Mentions without Labeled Text
FedCluLearn: Federated Continual Learning Using Stream Micro-cluster Indexing Scheme
Assessing Different Feature Selection Methods Applied to a Bulk RNA Sequencing Dataset with Regard to Biomedical Relevance
Collaborative Value Function Estimation Under Model Mismatch: A Federated Temporal Difference Analysis
Principles of Data Mining and Knowledge Discovery, Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999, Proceedings
The Future of CiteSeer: CiteSeer x
Trust Hole Identification in Signed Networks
Efficient Graph Kernels by Randomization
Multi-domain Active Learning for Semi-supervised Anomaly Detection
Adaptive Skip-Train Structured Regression for Temporal Networks
Infinitely Many-Armed Bandits with Unknown Value Distribution
Wasserstein t-SNE
Efficiently Mining Approximate Models of Associations in Evolving Databases
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
Mining Queries
Hybrid Cost-Sensitive Decision Tree
Exploration of Document Collections with Self-Organizing Maps: A Novel Approach to Similarity Representation
Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018), Dublin, Ireland, September 10th, 2018
Encoding Hierarchical Classification Codes for Privacy-Preserving Record Linkage Using Bloom Filters
FASOLE: Fast Algorithm for Structured Output LEarning
A Crystal Knowledge-Enhanced Pre-training Framework for Crystal Property Estimation
Unsupervised Learning of Joint Embeddings for Node Representation and Community Detection
Recognizing Reliability of Discovered Knowledge
A Relaxation-Based Approach for Mining Diverse Closed Patterns
Fourier-Information Duality in the Identity Management Problem
TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory
Sentimentor: Sentiment Analysis of Twitter Data
Meta-Learning for Black-Box Optimization
FuseRank (Demo): Filtered Vector Search in Multimodal Structured Data
A Framework for Deep Quantification Learning
A General Machine Learning Framework for Survival Analysis
Sensor-Based Performance Monitoring in Track Cycling
Confusable Learning for Large-Class Few-Shot Classification
Hierarchical Interaction Summarization and Contrastive Prompting for Explainable Recommendations
Efficient Privacy-Preserving Truth Discovery and Copy Detection in Crowdsourcing
Ensembles of Balanced Nested Dichotomies for Multi-class Problems
Concept Neurons - Handling Drift Issues for Real-Time Industrial Data Mining
Using Belief Networks and Fisher Kernels for Structured Document Classification
Very Fast Streaming Submodular Function Maximization
Memory-Enhanced Invariant Prompt Learning for Urban Flow Prediction Under Distribution Shifts
Automatic Detection and Recognition of Individuals in Patterned Species
The Matrix Generalized Inverse Gaussian Distribution: Properties and Applications
A Framework for Deep Constrained Clustering - Algorithms and Advances
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 V
Designing a Method to Identify Explainability Requirements in Cancer Research
Rate-Constrained Ranking and the Rate-Weighted AUC
SigBERT: Combining Narrative Medical Reports and Rough Path Signature Theory for Survival Prediction in Oncology
A Topological Approach for Detecting Twitter Communities with Common Interests
Safe Policy Improvement with Soft Baseline Bootstrapping
Session-Based Recommendation Along with the Session Style of Explanation
Fair Associative Co-clustering
AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental Learning
Zero-cost Transition to Multi-document Processing in Summarization with Multi-Channel Attention
QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees
Induction of Concepts in Web Ontologies through Terminological Decision Trees
BASS: A Bootstrapping Approach for Aligning Heterogenous Social Networks
Incorporating Privileged Information to Unsupervised Anomaly Detection
Cycling Network Projects: A Decision-Making Aid Approach
Challenges of Stream Learning for Predictive Maintenance in the Railway Sector
Joint Prediction of Topics in a URL Hierarchy
Strategic Patterns Discovery in RTS-games for E-Sport with Sequential Pattern Mining
Survival Factorization on Diffusion Networks
3D Detection of ALMA Sources Through Deep Learning
An Application of Association Rules Discovery to Geographic Information Systems
Privacy Preserving Synthetic Data Release Using Deep Learning
Predicting Partial Orders: Ranking with Abstention
Explaining Uncertainty in AI for Clinical Decision Support Systems
Interestingness is Not a Dichotomy: Introducing Softness in Constrained Pattern Mining
Make a Long Image Short: Adaptive Token Length for Vision Transformers
Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA)
TopicExplorer: Exploring Document Collections with Topic Models
Non-exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks
LtrGCN: Large-Scale Graph Convolutional Networks-Based Learning to Rank for Web Search
Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety
X-SDR: An Extensible Experimentation Suite for Dimensionality Reduction
Fast Training of Support Vector Machines for Survival Analysis
Contextual Hypernetwork for Adaptive Prediction of Laser-Induced Colors on Quasi-random Plasmonic Metasurfaces
Immediate Split Trees: Immediate Encoding of Floating Point Split Values in Random Forests
Ensembles on Random Patches
Optimal Thresholding of Classifiers to Maximize F1 Measure
Dynamic Ensemble Re-Construction for Better Ranking
Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets
Graph-Margin Based Multi-label Feature Selection
Are SHAP Values Biased Towards High-Entropy Features?
ShareBoost: Boosting for Multi-view Learning with Performance Guarantees
Semi-supervised Multivariate Sequential Pattern Mining
Comprehensive Transformer-Based Model Architecture for Real-World Storm Prediction
A Reinforcement Learning Algorithm for Fair Electoral Redistricting in Parliamentary Systems
Transformers: "The End of History" for Natural Language Processing?
A Family of Feed-Forward Models for Protein Sequence Classification
Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling
Finding Similar Movements in Positional Data Streams
DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors
How to Carve up the World: Learning and Collaboration for Structure Recommendation
Disentangled Representations for Continual Learning: Overcoming Forgetting and Facilitating Knowledge Transfer
Joint Multi-source Reduction
1st ECML/PKDD Workshop on Statistically Sound Data Mining, SSDM 2014, held at ECML/PKDD 2014, Nancy, France, September 15, 2014
Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2015, co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 11, 2015
GALG: Linking Addresses in Tracking Ecosystem Using Graph Autoencoder with Link Generation
Naive Bayes for Text Classification with Unbalanced Classes
KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework
Fine-Tune Smarter, Not Harder: Parameter-Efficient Fine-Tuning for Geospatial Foundation Models
Variational Bayes for Mixture Models with Censored Data
CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining
Attention, Filling in the Gaps for Generalization in Routing Problems
Transfer Learning in Credit Risk
Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency
ST-LoRA: Low-Rank Adaptation for Spatio-Temporal Forecasting
Advancing Solar Flare Prediction Using Deep Learning with Active Region Patches
L 1 -Regularized Neural Ranking for Risk Stratification and Its Application to Prediction of Time to Distant Metastasis in Luminal Node Negative Chemotherapy Naïve Breast Cancer Patients
Intent-Aware Audience Targeting for Ride-Hailing Service
Poisoning Attacks on Algorithmic Fairness
Knowledge Discovery from User Preferences in Conversational Recommendation
SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract)
Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections
Cut-Stitch: A Simple and Effective Data Augmentation Method for Industrial Inspection
Long-Tail Augmented Graph Contrastive Learning for Recommendation
Few-Shot Forecasting of Time-Series with Heterogeneous Channels
Anytime Subgroup Discovery in Numerical Domains with Guarantees
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines
Response-Guided Community Detection: Application to Climate Index Discovery
Let's Penetrate the Defense: A Machine Learning Model for Prediction and Valuation of Penetrative Passes
Learning to Detect Adverse Traffic Events from Noisily Labeled Data
AD-AUG: Adversarial Data Augmentation for Counterfactual Recommendation
Differentially Private Analysis of Outliers
Enabling ControlNet to follow Localized Descriptions Using Cross-Attention Control
Mining Actionable Partial Orders in Collections of Sequences
A Quantitative Comparison of the Subgraph Miners MoFa, gSpan, FFSM, and Gaston
Porting Decision Tree Algorithms to Multicore Using FastFlow
Leveraging Variational Autoencoders for Multiple Data Imputation
Aspect Mining with Rating Bias
Harnessing the Power of Prompt Experts: Efficient Knowledge Distillation for Enhanced Language Understanding
PrePeP: A Light-Weight, Extensible Tool for Predicting Frequent Hitters
Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series
Adaptive Two-View Online Learning for Math Topic Classification
Churn Prediction Using Dynamic RFM-Augmented Node2vec
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift
Towards Resource-Efficient Classifiers for Always-On Monitoring
Alternative Semantic Representations for Zero-Shot Human Action Recognition
Learning First-Order Definite Theories via Object-Based Queries
Attribute-Aware Sequential Recommendation Model for Used Car Auctions
Predicting Pass Receiver in Football Using Distance Based Features
Preface to the 1st ECML/PKDD workshop on Statistically Sound Data Mining
Selecting from Multiple Strategies Improves the Foreseeable Reasoning of Tool-Augmented Large Language Models
Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
Hetero-Labeled LDA: A Partially Supervised Topic Model with Heterogeneous Labels
DualMatch: Robust Semi-supervised Learning with Dual-Level Interaction
Inducing Cost-Sensitive Trees via Instance Weighting
Automated Construction and Analysis of Political Networks via Open Government and Media Sources
Interpretable Instance-Based Learning Through Pairwise Distance Trees
FastDEC: Clustering by Fast Dominance Estimation
Re-evaluating the Privacy Benefit of Federated Learning
Automating Common Data Science Matrix Transformations
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I
Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution
Addressing Limitations of TinyML Approaches for AI-Enabled Ambient Intelligence - Position Paper
Structured Regularizer for Neural Higher-Order Sequence Models
Obfuscation of Sensitive Text in Audiovisual Content Using AI
Active Learning of Model Parameters for Influence Maximization
Redefining Fairness: A Multi-dimensional Perspective and Integrated Evaluation Framework
Exploring a Mixed Representation for Encoding Temporal Coherence
The Role of Transformer Architecture in the Logic-as-Loss Framework
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Paired-Consistency: An Example-Based Model-Agnostic Approach to Fairness Regularization in Machine Learning
Binary Decomposition Methods for Multipartite Ranking
Drift Detection Using Stream Volatility
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning
Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal Network
A Quantification of Cluster Novelty with an Application to Martian Topography
Factorized Structured Regression for Large-Scale Varying Coefficient Models
Knowledge Discovery in Spatial Data by Means of ILP
Unsupervised Profiling for Identifying Superimposed Fraud
Efficient Mining of Correlation Patterns in Spatial Point Data
A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments
CRISPert: A Transformer-Based Model for CRISPR-Cas Off-Target Prediction
Datum-Wise Classification: A Sequential Approach to Sparsity
Restricted Deep Belief Networks for Multi-view Learning
Gradient-Based Label Binning in Multi-label Classification
Active Stream Learning with an Oracle of Unknown Availability for Sentiment Prediction
Equivariant Representation Learning in the Presence of Stabilizers
Automatic Category Structure Generation and Categorization of Chinese Text Documents
Predicting Player Transfers in the Small World of Football
Realistic Synthetic Data for Testing Association Rule Mining Algorithms for Market Basket Databases
Sequential Patterns of POS Labels Help to Characterize Language Acquisition
STGEN: Deep Continuous-Time Spatiotemporal Graph Generation
Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs
Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well
Stats Aren't Everything: Learning Strengths and Weaknesses of Cricket Players
On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference
Hub Gene Selection Methods for the Reconstruction of Transcription Networks
EURO 2016 Predictions Using Team Rating Systems
The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC)
AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants
Efficient Bayesian Maximum Margin Multiple Kernel Learning
Learning and Interpreting Potentials for Classical Hamiltonian Systems
Multimodal Approach to Early Detection of Harmful Algal Blooms
Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results
Taming Large Rule Models in Rough Set Approaches
TinyMetaFed: Efficient Federated Meta-learning for TinyML
A Parameter-Free Bayesian Framework for Uplift Modeling Application on Telecom Data
Active Class Selection with Uncertain Class Proportions
Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks
Selected Approaches Ranking Contextual Term for the BioASQ Multi-label Classification (Task6a and 7a)
Distractor Generation for Multiple-Choice Questions with Predictive Prompting and Large Language Models
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation
CHADE: Metalearning with Classifier Chains for Dynamic Combination of Classifiers
Augmented Leverage Score Sampling with Bounds
Graph-Enhanced Multi-Activity Knowledge Tracing
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
A Nearly Unbiased Matrix Completion Approach
Collaborative Filtering Using Restoration Operators
Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers
Ranking Based Multitask Learning of Scoring Functions
Metric Learning for Categorical and Ambiguous Features: An Adversarial Method
A Prediction-Based Visual Approach for Cluster Exploration and Cluster Validation by HOV 3
Visualization Support to Interactive Cluster Analysis
Lit@EVE: Explainable Recommendation Based on Wikipedia Concept Vectors
Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
Fairness Analysis in Causal Models: An Application to Public Procurement
Taxonomic Prediction with Tree-Structured Covariances
Hash Function Learning via Codewords
Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphs
Analyzing Text and Social Network Data with Probabilistic Models
High-Probability Kernel Alignment Regret Bounds for Online Kernel Selection
EXTREMUM: A Web-Based Tool to Generate and Explore Counterfactual Explanations on Tabular and Time-Series Data
Spatial Transfer Learning for Estimating PM 2.5 in Data-Poor Regions
A Feature Selection Method for Multi-dimension Time-Series Data
Triangle Completion Time Prediction Using Time-Conserving Embedding
Molecular Fingerprints-Based Machine Learning for Metabolic Profiling
Graphical Model-Based Lasso for Weakly Dependent Time Series of Tensors