yusuke1997/dblp-id-title huggingface dataset:
Learning from Inconsistent and Unreliable Annotators by a Gaussian Mixture Model and Bayesian Information Criterion
Informed Priors for Knowledge Integration in Trajectory Prediction
Entropy and Margin Maximization for Structured Output Learning
Improving GP-UCB Algorithm by Harnessing Decomposed Feedback
Mining Business Relationships from Stocks and News
The Minimum Code Length for Clustering Using the Gray Code
PRoA: A Probabilistic Robustness Assessment Against Functional Perturbations
Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms
Time Series Forecasting with Gaussian Processes Needs Priors
Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks
Exploring Real Mobility Data with M-Atlas
Learning Tensor-Based Representations from Brain-Computer Interface Data for Cybersecurity
Proceedings of the ECML/PKDD Discovery Challenges co-located with European Conference on Machine Learning - Principle and Practice of Knowledge Discovery in Database (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017
Composite Denoising Autoencoders
Contextual Graph Representation Learning in Text Disambiguation
Embedding Knowledge Graphs Attentive to Positional and Centrality Qualities
Modeling and Detecting Urinary Anomalies in Seniors from Data Obtained by Unintrusive Sensors
NA-Aware Machine Reading Comprehension for Document-Level Relation Extraction
AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy
Spectral Features for Audio Based Vehicle Identification
OPTICS-OF: Identifying Local Outliers
Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II
Evolutionary Multi-objective Ensembles for Wind Power Prediction
A Scalable Approach for Unified Large Events Models in Soccer
Real-Part Quantum Support Vector Machines
Finding Similar Time Series
Using Genetic Algorithms to Evolve a Rule Hierarchy
Efficient Multisplitting on Numerical Data
Scalable Hyperparameter Optimization with Products of Gaussian Process Experts
Automatic Model Adaptation for Complex Structured Domains
A Mixed Similarity Measure in Near-Linear Computational Complexity for Distance-Based Methods
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 2020), Ghent, Belgium, September 14th, 2020
Huber-Norm Regularization for Linear Prediction Models
Time Series Machine Learning with Aeon: Classification and Regression
A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint
Author Name Disambiguation Using a New Categorical Distribution Similarity
Enhancing Energy-Efficiency by Solving the Throughput Bottleneck of LSTM Cells for Embedded FPGAs
Federated Learning Towards the Unknown: A Deep Dive Into Diabetic Retinopathy Prediction from Real-World EHR Structured Data on Unseen Diabetic Centers
Towards Predicting the Subscription Status of Twitch.tv Users - ECML-PKDD ChAT Discovery Challenge 2020
Monitoring Short Term Changes of Malaria Incidence in Uganda with Gaussian Processes
Prospective Data Model and Distributed Query Processing for Mobile Sensing Data Streams
Supervised Clustering for Subgroup Discovery: An Application to COVID-19 Symptomatology
Learning Unbiased Representations via Rényi Minimization
pysubgroup: Easy-to-Use Subgroup Discovery in Python
Policy Iteration Based on a Learned Transition Model
On Training Survival Models with Scoring Rules
Wave Top-k Random-d Family Search: How to Guide an Expert in a Structured Pattern Space
A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery
Feedback-Guided Attributed Graph Embedding for Relevant Video Recommendation
Application of Data-Mining and Knowledge Discovery in Automotive Data Engineering
A New Class of Intelligible Models for Tabular Learning
GLADformer: A Mixed Perspective for Graph-Level Anomaly Detection
Machine Learning Prediction of Photovoltaic Energy from Satellite Sources
H 2 -Nets: Hyper-hodge Convolutional Neural Networks for Time-Series Forecasting
Learning Compact Class Codes for Fast Inference in Large Multi Class Classification
Machine Learning for Targeted Assimilation of Satellite Data
Corpus-Based Neural Network Method for Explaining Unknown Words by WordNet Senses
Understanding Domain-Size Generalization in Markov Logic Networks
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes
Parameter Learning of Bayesian Network Classifiers Under Computational Constraints
Learning Beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling
A Stacked Bidirectional LSTM Model for Classifying Source Codes Built in MPLs
Efficient Discovery of Sets of Co-occurring Items in Event Sequences
A Joint Topic and Perspective Model for Ideological Discourse
Frequency-Based Separation of Climate Signals
Investigating the Dynamics of Cardio-Metabolic Comorbidities and Their Interactions in Ageing Adults Through Dynamic Bayesian Networks
Tree-Based OWL Class Expression Learner over Large Graphs
Kernels for Periodic Time Series Arising in Astronomy
A Selecting-the-Best Method for Budgeted Model Selection
Safe Screening Rules for Group SLOPE
SemanticTalk: Software for Visualizing Brainstorming Sessions and Thematic Concept Trails on Document Collections
Unsupervised Machine Learning Methods to Estimate a Health Indicator for Condition Monitoring Using Acoustic and Vibration Signals: A Comparison Based on a Toy Data Set from a Coffee Vending Machine
Recognition of Instrument Timbres in Real Polytimbral Audio Recordings
Striving for Simplicity in Deep Neural Models Trained for Malware Detection
SMOTEBoost: Improving Prediction of the Minority Class in Boosting
Feature-Robust Optimal Transport for High-Dimensional Data
Deep Learning, Grammar Transfer, and Transportation Theory
A Generative Bayesian Model for Item and User Recommendation in Social Rating Networks with Trust Relationships
Model Bridging: Connection Between Simulation Model and Neural Network
Neither in the Programs Nor in the Data: Mining the Hidden Financial Knowledge with Knowledge Graphs and Reasoning
Nowcasting with Numerous Candidate Predictors
Regularized Sparse Kernel Slow Feature Analysis
The Rapid Growth of Human-in-the-Loop Machine Learning
Graph Enhanced Memory Networks for Sentiment Analysis
Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I
Search Space Complexity of Iteration Domain Based Instruction Embedding for Deep Learning Accelerators
Improving Access to Science for Social Good
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification
Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains
Ordinal Versus Nominal Time Series Classification
Robust Representation for Domain Adaptation in Network Security
LATuner: An LLM-Enhanced Database Tuning System Based on Adaptive Surrogate Model
Explainable Long and Short-Term Pattern Detection in Projected Sequential Data
A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases
Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint
A Scalable AI Approach for Clinical Trial Cohort Optimization
Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns
Simple Graph Condensation
Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing, DMNLP 2015, co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 07, 2015
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms
Blankets All the Way up - the Economics of Active Inference
Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE
Semi-supervised Subspace Co-Projection for Multi-class Heterogeneous Domain Adaptation
Model Switching for Bayesian Classification Trees with Soft Splits
TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation
Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers
Handling Oversampling in Dynamic Networks Using Link Prediction
MultiLayerET: A Unified Representation of Entities and Topics Using Multilayer Graphs
Unsupervised Domain Adaptation with Joint Domain-Adversarial Reconstruction Networks
Disparity Between Batches as a Signal for Early Stopping
Fast Stepwise Regression on Linked Data
Resource-Aware Steel Production Through Data Mining
Empirical Evaluation of Feature Subset Selection Based on a Real-World Data Set
Predicting Player Trajectories in Shot Situations in Soccer
Community-Aware Graph Transformer: Preserving Community Semantics for Effective Global Aggregation
BK-ADAPT: Dynamic Background Knowledge for Automating Data Transformation
VOGUE: Answer Verbalization Through Multi-Task Learning
Leveraging Higher Order Dependencies between Features for Text Classification
Towards Data-Driven Volatility Modeling with Variational Autoencoders
Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies
ITCH: Information-Theoretic Cluster Hierarchies
Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth
Multiscale Comparison of Temporal Patternsin Time-Series Medical Databases
Explaining End-to-End ECG Automated Diagnosis Using Contextual Features
Hyperparameter Optimization with Factorized Multilayer Perceptrons
PTMSearch: A Greedy Tree Traversal Algorithm for Finding Protein Post-Translational Modifications in Tandem Mass Spectra
Online Anomaly Explanation: A Case Study on Predictive Maintenance
Clustering by Intent: A Semi-Supervised Method to Discover Relevant Clusters Incrementally
Post-hoc Counterfactual Generation with Supervised Autoencoder
Classifier-Free Graph Diffusion for Molecular Property Targeting
Can Twitter Help to Predict Outcome of 2019 Indian General Election: A Deep Learning Based Study
Deep Reinforcement Learning for Large-Scale Epidemic Control
The Effects of Reluctant and Fallible Users in Interactive Online Machine Learning
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks
Linking IT Product Records
Harnessing Mixed Features for Imbalance Data Oversampling: Application to Bank Customers Scoring
Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference
RangeGrad: Explaining Neural Networks by Measuring Uncertainty Through Bound Propagation
Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning
Learning Hierarchical Planning-Based Policies from Offline Data
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part X
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Diffusion Classifier Guidance for Non-robust Classifiers
Novel Node Category Detection Under Subpopulation Shift
Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations
On the Stability of Feature Selection in the Presence of Feature Correlations
MPG: An Efficient Multi-scale Point-Based GNN for Non-uniform Meshes
Lightweight Collaborative Filtering Method for Binary-Encoded Data
Why Fair Automated Hiring Systems Breach EU Non-discrimination Law
Continuous Similarity Computation over Streaming Graphs
Learning Parameters in Entity Relationship Graphs from Ranking Preferences
Robust Burned Area Delineation Through Multitask Learning
Advanced Strategic Improvement with Decision Interactions
Actively Transfer Domain Knowledge
Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning
Shallow Self-learning for Reject Inference in Credit Scoring
Using Machine Learning Methods and Linguistic Features in Single-Document Extractive Summarization
Extended Functional Dependencies as a Basis for Linguistic Summaries
Bayesian Nonlinear Support Vector Machines for Big Data
RAID: Root Cause Anomaly Identification and Diagnosis
PBE: Driver Behavior Assessment Beyond Trajectory Profiling
Results of the Seventh Edition of the BioASQ Challenge
Word Sense Disambiguation for Exploiting Hierarchical Thesauri in Text Classification
Rethinking the Misalignment Problem in Dense Object Detection
Distributed Multi-task Learning for Sensor Network
Adaptive Supervised Learning for Financial Markets Volatility Targeting Models
Comparison of Tree-Based Methods for Multi-target Regression on Data Streams
KnowNow: A Serendipity-Based Educational Tool for Learning Time-Linked Knowledge
Leveraging Multi-target Regression for Predicting the Next Parallel Activities in Event Logs
A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
Shapley-Based Feature Selection for Online Algorithm Selection
Contribution of Boosting in Wrapper Models
Latent Factors Meet Homophily in Diffusion Modelling
Data is Moody: Discovering Data Modification Rules from Process Event Logs
Data Analytics for Renewable Energy Integration - Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers
Progressive Decomposition-Enhanced Time-Varying Graph Neural Network for Traffic Forecasting
Effective Visualization of Information Diffusion Process over Complex Networks
Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework
A Left-to-Right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis
Uncovering Hidden Block Structure for Clustering
Automated Discovery of Trade-Off Between Utility, Privacy and Fairness in Machine Learning Models
Spectral Co-Clustering for Dynamic Bipartite Graphs
Towards Inclusive Fairness Evaluation via Eliciting Disagreement Feedback from Non-expert Stakeholders
A Mathematics Framework of Artificial Shifted Population Risk and Its Further Understanding Related to Consistency Regularization
F-3DNet: Leveraging Inner Order of Point Clouds for 3D Object Detection
Machine Learning for Intelligent Industrial Design
Taking over the Stock Market: Adversarial Perturbations Against Algorithmic Traders
Detecting Temporal Change in Event Sequences: An Application to Demographic Data
k Is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities
AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models
Distributed Learning of Non-convex Linear Models with One Round of Communication
Rough Sets for Data Mining and Knowledge Discovery (Abstract)
Approximation Algorithms for Confidence Bands for Time Series
Reinforcement Learning for Segmented Manufacturing
Low-Regret Algorithms for Strategic Buyers with Unknown Valuations in Repeated Posted-Price Auctions
Predicting Exoplanetary Features with a Residual Model for Uniform and Gaussian Distributions
Predicting Future Classifiers for Evolving Non-linear Decision Boundaries
Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting
Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features
TopCat: Data Mining for Topic Identification in a Text Corpus
Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets
Gamma Process Poisson Factorization for Joint Modeling of Network and Documents
ELSIM: End-to-End Learning of Reusable Skills Through Intrinsic Motivation
Temporal Defenses for Robust Recommendations
Copy Mechanism and Tailored Training for Character-Based Data-to-Text Generation
Non-redundant Subgroup Discovery Using a Closure System
Analyzing and Correcting Biased Machine Learning-Based Tuning of Weight Shrinkage in Forecast Combination
Limitations of the Lipschitz Constant as a Defense Against Adversarial Examples
Interpetable Target-Feature Aggregation for Multi-task Learning Based on Bias-Variance Analysis
The Limit Order Book Recreation Model (LOBRM): An Extended Analysis
Group-Specific Training Data
ASAP: Automatic Semantics-Aware Analysis of Network Payloads
Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data
Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender
Random Forests with Random Projections of the Output Space for High Dimensional Multi-label Classification
Intelligent Monitoring of Transformer Insulation Using Convolutional Neural Networks
Representation, Exploration and Recommendation of Playlists
Frequency-Aware Truncated Methods for Sparse Online Learning
Con-S2V: A Generic Framework for Incorporating Extra-Sentential Context into Sen2Vec
Risk-Aware Reinforcement Learning for Multi-Period Portfolio Selection
Extending Support Vector Regression to Constraint Optimization: Application to the Reduction of Potentially Avoidable Hospitalizations
NKFAC: A Fast and Stable KFAC Optimizer for Deep Neural Networks
Proceedings of the 1st International Workshop on Sentiment Discovery from Affective Data, SDAD@ECML/PKDD 2012, Bristol, UK, September 28, 2012
ISETS: Incremental Shapelet Extraction from Time Series Stream
A Metric for Selection of the Most Promising Rules
ASK-the-Expert: Active Learning Based Knowledge Discovery Using the Expert
Combining Multiple Models with Meta Decision Trees
Temporal and spatial approaches for land cover classification
A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarity
A Projection-Based Framework for Classifier Performance Evaluation
DPS: Diverse Prototype Selection for Adaptive In-Context Learning
FALCUN: A Simple and Efficient Deep Active Learning Strategy
Link Prediction in Dynamic Networks Using Graphlet
Autonomous HVAC Control, A Reinforcement Learning Approach
Using Both Latent and Supervised Shared Topics for Multitask Learning
Fuzzy Clustering of Series Using Quantile Autocovariances
A Deep Dive into Multilingual Hate Speech Classification
Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization
Job Title Prediction as a Dual Task of Expertise Prediction in Open Source Software
Harnessing Error Patterns to Estimate Out-of-Distribution Performance
Quality-Preserving Extreme Image Compression: Using Interpretable Conditioning Inputs with Diffusion Models
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I
Trajectory Imputation in Multi-agent Sports with Derivative-Accumulating Self-ensemble
Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models
Capacity Control for Partially Ordered Feature Sets
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE
MMNet: Multi-granularity Multi-mode Network for Item-Level Share Rate Prediction
Banksformer: A Deep Generative Model for Synthetic Transaction Sequences
Soccer Team Vectors
Accurate Recasting of Parameter Estimation Algorithms Using Sufficient Statistics for Efficient Parallel Speed-Up: Demonstrated for Center-Based Data Clustering Algorithms
Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds
Future Augmentation with Self-distillation in Recommendation
Detecting Bicliques in GF[q]
Regression by Feature Projections
The Model of Most Informative Patterns and Its Application to Knowledge Extraction from Graph Databases
Stream-based Community Discovery via Relational Hypergraph Factorization on Evolving Networks
Hyperbolic Delaunay Geometric Alignment
Augmenting Semantic Representation of Depressive Language: From Forums to Microblogs
Adaptive Options for Decision Trees in Evolving Data Stream Classification
Compression Picks Item Sets That Matter
InCo: Intermediate Prototype Contrast for Unsupervised Domain Adaptation
Energy Consumption Forecasting Using a Stacked Nonparametric Bayesian Approach
Hierarchical Interaction Networks with Rethinking Mechanism for Document-Level Sentiment Analysis
Deep Eyedentification: Biometric Identification Using Micro-movements of the Eye
Superset Learning Based on Generalized Loss Minimization
Reward Shaping for User Satisfaction
Hierarchical Unimodal Bandits
Semi-automated Construction of Complex Knowledge Base Question Answering Dataset Using Large Language Model
Unsupervised Multi-source Domain Adaptation for Regression
Self-supervised Log Parsing
Multi-modal Terminology Management - Corpora, Data Models, and Implementations in TermStar
Process-Based Modeling and Design of Dynamical Systems
Maximum Entropy Linear Manifold for Learning Discriminative Low-Dimensional Representation
The Feature Importance Ranking Measure
Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets
Pedestrian Trajectory Prediction with Structured Memory Hierarchies
Distributed Learning of Neural Networks with One Round of Communication
Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains
Centroid-Based Document Classification: Analysis and Experimental Results
Incorporating Physics-Based Models into Data Driven Approaches for Air Leak Detection in City Buses
ApmNet: Toward Generalizable Visual Continuous Control with Pre-trained Image Models
The Difference and the Norm - Characterising Similarities and Differences Between Databases
Transactional Tree Mining
I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads
BiCAE - A Bimodal Convolutional Autoencoder for Seed Purity Testing
Inhomogeneous Parsimonious Markov Models
Generic Pattern Trees for Exhaustive Exceptional Model Mining
A Unified Approach to Active Dual Supervision for Labeling Features and Examples
Sentiment extraction from financial public disclosure documents
Density Estimators for Positive-Unlabeled Learning
Transformer Models for Question Answering at BioASQ 2019
Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection
Visualizing Class Probability Estimators
Advancing Multi-step Mathematical Reasoning in Large Language Models Through Multi-layered Self-reflection with Auto-prompting
Will My Question Be Answered? Predicting "Question Answerability" in Community Question-Answering Sites
Filling Gaps in Micro-meteorological Data
Generalized Entropy and Projection Clustering of Categorical Data
EMG Subspace Alignment and Visualization for Cross-Subject Hand Gesture Classification
Structure Determination and Estimation of Hierarchical Archimedean Copulas Based on Kendall Correlation Matrix
Interesting Fuzzy Association Rules in Quantitative Databases
Multi-view Semantic Learning for Data Representation
CNN-Transformer with Absolute Positional Encoding Optimized for Low-Dimensional Inputs: Applied to Estimate Sliding Drop Width
Geography of Differences between Two Classes of Data
Answering the Most Correlated N Association Rules Efficiently
Induction of Strong Feature Subsets
Efficient Training of Graph-Regularized Multitask SVMs
STaR: a Social Tag Recommender System
The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery
Detecting Autism by Analyzing a Simulated Social Interaction
Explaining Predictions by Characteristic Rules
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III
New Frontiers in Mining Complex Patterns - First International Workshop, NFMCP 2012, Held in Conjunction with ECML/PKDD 2012, Bristol, UK, September 24, 2012, Revised Selected Papers
FILTA: Better View Discovery from Collections of Clusterings via Filtering
A Scalable Distributed Stream Mining System for Highway Traffic Data
Weighted Symbols-Based Edit Distance for String-Structured Image Classification