yusuke1997/dblp-id-title huggingface dataset:
An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning
An Empirical Evaluation of Foundation Models for Multivariate Time Series Classification
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I
Towards Synergistic Human-AI Collaboration in Hybrid Decision-Making Systems
Towards Federated COVID-19 Vaccine Side Effect Prediction
Activity-Driven Influence Maximization in Social Networks
Personalized Thread Recommendation for MOOC Discussion Forums
Target-Aware Molecular Graph Generation
Routine Inspection: A Playbook for Corner Kicks
Revisiting Conditional Functional Dependency Discovery: Splitting the "C" from the "FD"
A Bi-clustering Framework for Categorical Data
Interestingness Measures for Fuzzy Association Rules
Hierarchical, Parameter-Free Community Discovery
Interactive Toolbox for Two-Dimensional Gaussian Mixture Modeling
An Ensemble Learning Approach for the Kaggle Taxi Travel Time Prediction Challenge
ILPO-NET: Network for the Invariant Recognition of Arbitrary Volumetric Patterns in 3D
Finding Reliable Subgraphs from Large Probabilistic Graphs
Evaluation of Forecasting Methods for Very Small-Scale Networks
Progressive and Iterative Approaches for Time Series Averaging
A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation
Hierarchical Document Clustering Based on Tolerance Rough Set Model
Leveraging External Factors in Household-Level Electrical Consumption Forecasting Using Hypernetworks
Error-Bounded Approximations for Infinite-Horizon Discounted Decentralized POMDPs
KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces
How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice
Bayesian Inference for Least Squares Temporal Difference Regularization
Recognizing Cognitive Load by a Hybrid Spatio-Temporal Causal Model from Multivariate Physiological Data
A Genetic Algorithm for Text Classification Rule Induction
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning
Speeding up Hyper-parameter Optimization by Extrapolation of Learning Curves Using Previous Builds
Hi Model, generating "nice" instead of "good" is not as bad as generating "rice"! Towards Context and Semantic Infused Dialogue Generation Loss Function
Named Entity Recognition from Scratch on Social Media
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II
Discovery of Regulatory Connections in Microarray Data
Constraint-Based Mining of Episode Rules and Optimal Window Sizes
Mining Relational Databases
Centered Masking for Language-Image Pre-training
On Refining BERT Contextualized Embeddings using Semantic Lexicons
Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems
Temporal Maximum Margin Markov Network
GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs
Revisiting Cross-Modal Knowledge Distillation: A Disentanglement Approach for RGBD Semantic Segmentation
Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce
ECD: Efficient Contrastive Decoding with Probabilistic Hallucination Detection
Dimensionality-Induced Information Loss of Outliers in Deep Neural Networks
Reconnaissance for Reinforcement Learning with Safety Constraints
Efficient Construction of Comprehensible Hierarchical Clusterings
Deep Learning Based Urban Anomaly Prediction from Spatiotemporal Data
Networked Point Process Models Under the Lens of Scrutiny
adaQN: An Adaptive Quasi-Newton Algorithm for Training RNNs
SLISEMAP: Combining Supervised Dimensionality Reduction with Local Explanations
Periodic Intra-ensemble Knowledge Distillation for Reinforcement Learning
Learning Implicit Generative Models by Teaching Density Estimators
Scalable Metric Learning for Co-Embedding
Efficient Pruning Schemes for Distance-Based Outlier Detection
Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations
Policy Search for Path Integral Control
MCMC for Bayesian Estimation of Differential Privacy from Membership Inference Attacks
Dynamic Hierarchies in Temporal Directed Networks
Hierarchical Latent Tree Analysis for Topic Detection
Spectral Distribution Alignment for Enhanced Generalization in Regression
Using Grammatical Inference to Automate Information Extraction from the Web
Active Learning by Clustering for Drifted Data Stream Classification
Using Multiple RDF Knowledge Graphs for Enriching ChatGPT Responses
A Case Study in Sequential Pattern Mining for IT-Operational Risk
Feature-Based Classification of Electric Guitar Types
Interpretable Counterfactual Explanations Guided by Prototypes
Active Learning in Gaussian Process State Space Model
Achieving Flexible Local Differential Privacy in Federated Learning via Influence Functions
Visual OntoBridge: Semi-automatic Semantic Annotation Software
A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods
Who will Interact with Whom? A Case-Study in Second Life Using Online Social Network and Location-Based Social Network Features to Predict Interactions between Users
PolyAnalyst Data Analysis Technique and Its Specialization for Processing Data Organized as a Set of Attribute Values
Deep Networks Based Approach for Automatic Counting Panicles on UAV Captured Paddy RGB Imagery
Disagreement Evaluation of Solutions for Math Word Problem
Mining Periodic Patterns with a MDL Criterion
Efficient Classification from Multiple Heterogeneous Databases
Concurrent Bandits and Cognitive Radio Networks
Fault Forecasting Using Data-Driven Modeling: A Case Study for Metro do Porto Data Set
Ordinal Quantification Through Regularization
Exceptional Gestalt Mining: Combining Magic Cards to Make Complex Coalitions Thrive
DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data
Socially Fair Center-Based and Linear Subspace Clustering
Federated Learning with Flexible Architectures
Legend-Informed Symbol Recognition in Engineering Diagrams with Self-supervised Learning
CQNet: A Clustering-Based Quadruplet Network for Decentralized Application Classification via Encrypted Traffic
Embedding with Autoencoder Regularization
Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs
Computational Model for Urban Growth Using Socioeconomic Latent Parameters
Orthogonal Mixture of Hidden Markov Models
Looking Beyond the Past: Analyzing the Intrinsic Playing Style of Soccer Teams
SampleFix: Learning to Generate Functionally Diverse Fixes
Kernel Sequential Monte Carlo
Asymmetric Graph-Based Deep Reinforcement Learning for Portfolio Optimization
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks
OCADaMi: One-Class Anomaly Detection and Data Mining Toolbox
SustainaML: Enhancing Transparency, Control, and Green Sustainability in AutoML
Comparison of Machine Learning Methods for Predicting the Recovery Time of Professional Football Players After an Undiagnosed Injury
Tri-Band Assessment of Multi-Spectral Satellite Data for Flood Detection
Classification Factored Gated Restricted Boltzmann Machine
Segmentation of VHR EO Images using Unsupervised Learning
Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources
Sparse Kernel SVMs via Cutting-Plane Training
Socioscope: Spatio-temporal Signal Recovery from Social Media
On Meta Levels of an Organized Society of KDD Agents
WebDR: A Web Workbench for Data Reduction
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings
Clustering Transactional Data
LA - A Clustering Algorithm with an Automated Selection of Attributes, wich is Invariant to Functional Transformations of Coordinates
Ridge Regression, Hubness, and Zero-Shot Learning
A QUBO Framework for Team Formation
AIMED-RL: Exploring Adversarial Malware Examples with Reinforcement Learning
Preserving Real-World Robustness of Neural Networks Under Sparsity Constraints
How CNNs and ViTs Perceive Similarities Between Categories
REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training
Data Mining for the Web
Trustworthy AI Development in Education
Generalising Random Forest Parameter Optimisation to Include Stability and Cost
TOAS Intelligence Mining; Analysis of Natural Language Processing and Computational Linguistics
ReDeLEx: A Framework for Relational Deep Learning Exploration
Adaptive Bases for Reinforcement Learning
IKNN: Informative K-Nearest Neighbor Pattern Classification
Towards Behaviometric Security Systems: Learning to Identify a Typist
Efficient Mining of Top Correlated Patterns Based on Null-Invariant Measures
Towards Unifying Feature Interaction Models for Click-Through Rate Prediction
PowerScope: Early Event Detection and Identification in Electric Power Systems
Bi-directional Contrastive Distillation for Multi-behavior Recommendation
Information Interaction Profile of Choice Adoption
Smooth InfoMax - Towards Easier Post-Hoc Interpretability
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic Analysis
Anomaly Detection via Few-Shot Learning on Normality
Neutralized Empirical Risk Minimization with Generalization Neutrality Bound
Offline Reinforcement Learning with On-Policy Q-Function Regularization
A Machine Learning Approach to Study Expressive Performance Deviations in Classical Guitar
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge
multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification
Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting
Knowledge Discovery from Software Engineering Data: Rough Set Analysis and Its Interaction with Goal-Oriented Measurement
Learning Bi-clustered Vector Autoregressive Models
Unveiling Latent States Behind Social Indicators
Evaluation Measures for Multi-class Subgroup Discovery
Social-Affiliation Networks: Patterns and the SOAR Model
LCDB 1.0: An Extensive Learning Curves Database for Classification Tasks
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space
Covariate-Correlated Lasso for Feature Selection
Topological Insights into Sparse Neural Networks
How Much Does Stock Prediction Improve with Sentiment Analysis?
Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation
Intent Enhanced Self-supervised Hypergraph Learning for Session-Based Recommendation
Holistic Assessment of Structure Discovery Capabilities of Clustering Algorithms
Landscape Analysis of Stochastic Policy Gradient Methods
When a Tweet Finds its Place: Fine-Grained Tweet Geolocalisation
Learning of Simple Conceptual Graphs from Positive and Negative Examples
Image Access and Data Mining: An Approach
Collective Principal Component Analysis from Distributed, Heterogeneous Data
Convolutional Neural Network for Automatic MeSH Indexing
One Graph Is Worth a Thousand Logs: Uncovering Hidden Structures in Massive System Event Logs
Single-Path NAS: Designing Hardware-Efficient ConvNets in Less Than 4 Hours
SEA: Graph Shell Attention in Graph Neural Networks
Visualizing Multi-document Semantics via Open Domain Information Extraction
Hierarchical Graph Contrastive Learning for Review-Enhanced Recommendation
A Divise Initialisation Method for Clustering Algorithms
Fairness-Aware Graph Representation Learning with Limited Demographic Information
DegUIL: Degree-Aware Graph Neural Networks for Long-Tailed User Identity Linkage
On the Potentials of Input Repetition in CNN Networks for Reducing Multiplications
Proceedings of the 2nd International Workshop on Dynamic Networks and Knowledge Discovery, DyNaK 2014, co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Nancy, France, September 15, 2014
Balios - The Engine for Bayesian Logic Programs
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces
Temporal Heterogeneous Interaction Graph Embedding for Next-Item Recommendation
LYRICS: A General Interface Layer to Integrate Logic Inference and Deep Learning
Seasonal Average Temperature Forecast with the AutoGluonTS Modern AutoML Tool
What to Do with Your Sentiments in Finance
A Scalable Model for Frequency Distribution of Low Occurrence Multi-words Towards Handling Very Large Spectrum of Text Corpora Sizes
Extraction of Experts' Decision Process from Clinical Databases Using Rough Set Model
Leveraging Low Rank Filters for Efficient and Knowledge-Preserving Lifelong Learning
Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem
Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency
Explainable Process Monitoring Based on Class Activation Map: Garbage In, Garbage Out
Learning Throttle Valve Control Using Policy Search
Robust Gaussian Process Regression with Huber Likelihood and Projection Pursuit
Transferring Clinical Prediction Models Across Hospitals and Electronic Health Record Systems
Bayesian Optimization with Missing Inputs
Conference Mining via Generalized Topic Modeling
Parameter-Free Hierarchical Co-clustering by n-Ary Splits
Circle Attention: Forecasting Network Traffic by Learning Interpretable Spatial Relationships from Intersecting Circles
Summarizing Labeled Multi-graphs
Transformer-Based Contrastive Multi-view Clustering via Ensembles
BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answering
Deep Learning for Real-Time Neural Decoding of Grasp
Learning Decision Trees for Unbalanced Data
On the Adaptability of Attention-Based Interpretability in Different Transformer Architectures for Multi-class Classification Tasks
Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective
Distribution Matching for Graph Quantification Under Structural Covariate Shift
Urban Climate Data Sensing, Warehousing, and Analysis: A Case Study in the City of Abu Dhabi, United Arab Emirates
Image Anomaly Detection with Generative Adversarial Networks
Towards Fairness Through Time
Beyond Bag-of-Concepts: Vectors of Locally Aggregated Concepts
Classification in Geographical Information Systems
A Fast Algorithm to Find Overlapping Communities in Networks
Non-parametric Online AUC Maximization
Analysis of Vocational Education and Training and the Labour Market in Catalonia. A Data-Driven Approach
Learning Aligned-Spatial Graph Convolutional Networks for Graph Classification
On Decision Boundaries of Naïve Bayes in Continuous Domains
Supply Framework of Physical Machine Demand in Elastic Computing Service
Gaussian Logic for Predictive Classification
Privacy-Preserving Record Linkage to Identify Fragmented Electronic Medical Records in the All of Us Research Program
Disjoint-Support Factors and Seasonality Estimation in E-Commerce
Backdoor Attacks with Input-Unique Triggers in NLP
Pattern Extraction for Time Series Classification
Interactively Exploring Supply and Demand in the UK Independent Music Scene
A Density-Biased Sampling Technique to Improve Cluster Representativeness
CC-MR - Finding Connected Components in Huge Graphs with MapReduce
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework
Neural Cross-Domain Collaborative Filtering with Shared Entities
Extending Attribute-Oriented Induction as a Key-Preserving Data Mining Method
A Lossless Data Reduction for Mining Constrained Patterns in n-ary Relations
Expert Constrained Clustering: A Symbolic Approach
Fast Nearest Neighbor Search on Large Time-Evolving Graphs
Ising Bandits with Side Information
Rethinking Graph Domain Adaptation: A Spectral Contrastive Perspective
Time Warp Invariant Dictionary Learning for Time Series Clustering: Application to Music Data Stream Analysis
Time Series Clustering for Enhanced Dynamic Allocation in A/B Testing
An Analysis of Tensor Models for Learning on Structured Data
Optimal Online Learning Procedures for Model-Free Policy Evaluation
DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups
Spatial Contrastive Learning for Few-Shot Classification
The Blind Leading the Blind: Network-Based Location Estimation Under Uncertainty
MitM Attack Detection in BLE Networks Using Reconstruction and Classification Machine Learning Techniques
RADAR: Recurrent Autoencoder Based Detector for Adversarial Examples on Temporal EHR
An Exploratory Analysis of Multiple Multivariate Time Series
Privacy-Oriented Data Mining by Proof Checking
Automatic Grading of Student Code with Similarity Measurement
Learning Graphical Factor Models with Riemannian Optimization
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation
Host Based Intrusion Detection System with Combined CNN/RNN Model
Forecasting the FIFA World Cup - Combining Result- and goal-based Team Ability Parameters
Text Classification Using Association Rules, Dependency Pruning and Hyperonymization
Event Recognition Strategies applied in the Mercurio Project
Behavior of k-NN as an Instance-Based Explanation Method
Learning to Describe Player Form in the MLB
Ranking Cryptocurrencies by Brand Importance: A Social Media Analysis in ENEAGRID
Automatic Pass Annotation from Soccer Video Streams Based on Object Detection and LSTM
General Algorithms for Mining Closed Flexible Patterns under Various Equivalence Relations
Generating Actionable Knowledge by Expert-Guided Subgroup Discovery
Using Temporal Language Models for Document Dating
Improving Unsupervised Domain Adaptation with Representative Selection Techniques
ActiveVisium: Leveraging Active Learning to Enhance Manual Pathologist Annotation in 10x Visium Spatial Transcriptomics Experiments
Quantifying Quality of Actions Using Wearable Sensor
Relational Classification for Personalized Tag Recommendation
Decentralizing Multi-agent Reinforcement Learning with Temporal Causal Information
Multiple-Source Adaptation Using Variational Rényi Bound Optimization
node2bits: Compact Time- and Attribute-Aware Node Representations for User Stitching
Machine Learning for Data Streams with CapyMOA
Detecting Drift in Healthcare AI Models Based on Data Availability
Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver
Applying Electromagnetic Field Theory Concepts to Clustering with Constraints
The Metric is the Message: Benchmarking Challenges for Neural Symbolic Regression
A Tutorial Introduction to High Performance Data Mining (Abstract)
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 2022), Grenoble, France, September 18-22, 2022
Improving Ambulance Dispatching with Machine Learning and Simulation
Modeling Evolving User Behavior via Sequential Clustering
Prediction with Model-Based Neutrality
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains
Density-Based Subspace Clustering in Heterogeneous Networks
Evaluating the Impact of Friends in Predicting User's Availability in Online Social Networks
Learning and Inference in Probabilistic Classifier Chains with Beam Search
Tackling Oversmoothing in GNN via Graph Sparsification
Learning Dynamic Bayesian Belief Networks Using Conditional Phase-Type Distributions
ParCube: Sparse Parallelizable Tensor Decompositions
An Engineered Empirical Bernstein Bound
Optimizing Waste Collection: A Data Mining Approach
Directed Graph Learning via High-Order Co-linkage Analysis
Self-balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-kernel Estimation
Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL
LayerGLAT: A Flexible Non-autoregressive Transformer for Single-Pass and Multi-pass Prediction
Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes
Dynamics Adaptive Safe Reinforcement Learning with a Misspecified Simulator
Discovering Unbounded Episodes in Sequential Data
Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs
Lorentz-Invariant Augmentation for High-Energy Physics Deep Learning Models
DCID: Deep Canonical Information Decomposition
Tag Recommendations in Folksonomies
Enhancing Sharpness-Aware Minimization by Learning Perturbation Radius
Grouped Discrete Representation for Object-Centric Learning
Truly Unordered Probabilistic Rule Sets for Multi-class Classification
Mining Edge-Weighted Call Graphs to Localise Software Bugs
Balancing Speed and Accuracy in Neural-Enhanced Phonetic Name Matching
DyHGCN: A Dynamic Heterogeneous Graph Convolutional Network to Learn Users' Dynamic Preferences for Information Diffusion Prediction
A Sliding Window Filter for Time Series Streams
Permutation Testing Improves Bayesian Network Learning
Pattern-Based Anomaly Detection in Mixed-Type Time Series
Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases
User-Guided Clustering in Heterogeneous Information Networks via Motif-Based Comprehensive Transcription
Temporal Machine Learning for Switching Control
Tracing Videos to Their Social Network with Robust DCT Analysis
Polyp Detection in Endoscopic Video Using SVMs
Exploring and Exploiting Data-Free Model Stealing
Recommending Courses in MOOCs for Jobs: An Auto Weak Supervision Approach
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part I
Natively Interpretable t-SNE
New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, - Würzburg, Germany, September 16, 2019, Revised Selected Papers
Improve Default Prediction in Highly Unbalanced Context
Summarising Data by Clustering Items
Partial Device Fingerprints
Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space
Label Sanitization Against Label Flipping Poisoning Attacks
INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data
Hierarchical Structure-Aware Graph Prompting for Drug-Drug Interaction Prediction
Uncovering Fraud in Direct Marketing Data with a Fraud Auditing Case Builder
Towards a Predictive Patent Analytics and Evaluation Platform
Unsupervised Feature Selection via Unified Trace Ratio Formulation and K-means Clustering (TRACK)
EDN: A Novel Edge-Dependent Noise Model for Graph Data
Model Fusion via Neuron Transplantation
Finding Hierarchies of Subspace Clusters
PromptDSI: Prompt-Based Rehearsal-Free Continual Learning for Document Retrieval
A Churn Prediction Dataset from the Telecom Sector: A New Benchmark for Uplift Modeling
Combination of One-Class Support Vector Machines for Classification with Reject Option
Semi-supervised and Active Learning in Video Scene Classification from Statistical Features
An Adaptive Nearest Neighbor Classification Algorithm for Data Streams
Learning Policies for Battery Usage Optimization in Electric Vehicles
Flexible Sliding Windows for Kernel Regression Based Bus Arrival Time Prediction
InfoClus: Informative Clustering of High-Dimensional Data Embeddings
Graph-Revised Convolutional Network
Tackling Noise in Active Semi-supervised Clustering
Computational Drug Repositioning by Ranking and Integrating Multiple Data Sources
Learning Stochastic Models for Basketball Substitutions from Play-by-Play Data
Towards Expected Counter - Using Comprehensible Features to Predict Counterattacks
FireAnt: Claim-Based Medical Misinformation Detection and Monitoring
Model Reuse with Subgroup Discovery