yusuke1997/dblp-id-title huggingface dataset:
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Bayesian Multi-view Tensor Factorization
Talk is Cheap, Energy is Not: Towards a Green, Context-Aware Metrics Framework for Automatic Speech Recognition
Comparing Probabilistic Models for Melodic Sequences
An Algorithm for Multi-relational Discovery of Subgroups
Consolidation and Transmission of Multiple xAPI Data Sources from Virtual Learning Environments to Different Learning Record Stores
Denoising Diffusion Implicit Models for Laser-Plasma Accelerator Simulation Trained With Physical Constraint Loss
LitCQD: Multi-hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
FG 2 AN: Fairness-Aware Graph Generative Adversarial Networks
Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms
Filtered States: Active Inference, Social Media and Mental Health
Code Summarization with Project-Specific Features
Text Categorisation Using Document Profiling
Maintaining Sliding-Window Neighborhood Profiles in Interaction Networks
Mitigating Algorithmic Bias with Limited Annotations
C 3 DE: Causal-Aware Collaborative Neural Controlled Differential Equation for Long-Term Urban Crowd Flow Prediction
Hypergraph Learning with Hyperedge Expansion
Anomaly Detection with Score Functions Based on the Reconstruction Error of the Kernel PCA
Winning the DARPA Grand Challenge
Knowledge Intensive Learning: Combining Qualitative Constraints with Causal Independence for Parameter Learning in Probabilistic Models
Anonymity can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-label Graphs
An Interactive Interface for Novel Class Discovery in Tabular Data
Multi-step Prediction of Financial Asset Return Volatility Using Parsimonious Autoregressive Sequential Model
Analyzing the Explanation and Interpretation Potential of Matrix Capsule Networks
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I
Incremental Exemplar Learning Schemes for Classification on Embedded Devices
TwitterCracy: Exploratory Monitoring of Twitter Streams for the 2016 U.S. Presidential Election Cycle
A Boosting Approach to Multiview Classification with Cooperation
Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L 2 , 1 Regularization
Text Categorization and Semantic Browsing with Self-Organizing Maps on Non-euclidean Spaces
Exploiting Multi-step Sample Trajectories for Approximate Value Iteration
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification
Unsupervised Diverse Colorization via Generative Adversarial Networks
Event Relevancy Pruning in Support of Energy-Efficient Sequential Pattern Mining
Feature Induction and Network Mining with Clustering Tree Ensembles
A Differential Privacy Workflow for Inference of Parameters in the Rasch Model
MepoGNN: Metapopulation Epidemic Forecasting with Graph Neural Networks
Learning Stochastic Dynamical Systems via Bridge Sampling
Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes
Predicting the Primary Medical Procedure Through Clustering of Patients' Diagnoses
New Features for Sentiment Analysis: Do Sentences Matter?
FedAR: Addressing Client Unavailability in Federated Learning with Local Update Approximation and Rectification
Bayesian Nonparametrics for Sparse Dynamic Networks
Pattern Structures and Concept Lattices for Data Mining and Knowledge Processing
Considering Unseen States as Impossible in Factored Reinforcement Learning
Bow Gesture Classification to Identify Three Different Expertise Levels: A Machine Learning Approach
Relevance Grounding for Planning in Relational Domains
Customized Conversational Recommender Systems
Swap Randomization of Bases of Sequences for Mining Satellite Image Times Series
Filtered Observations for Model-Based Multi-agent Reinforcement Learning
Spatial Community-Informed Evolving Graphs for Demand Prediction
Meta-learning System for Automated Clustering
Exploitation and Merge of Information Sources for Public Procurement Improvement
Time-Varying Gaussian Process Bandit Optimization with Experts: No-Regret in Logarithmically-Many Side Queries
k -Anonymous Patterns
Co-Regularised Support Vector Regression
Node Re-Ordering as a Means of Anomaly Detection in Time-Evolving Graphs
A 2-Step Methodology for XAI in Education
Ultra-low Power Machinery Fault Detection Using Deep Neural Networks
Resampling in an Indefinite Database to Approximate Functional Dependencies
Knowledge-Conscious Data Clustering
Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII
On Dynamic Feature Weighting for Feature Drifting Data Streams
Scalable Bayesian Matrix Factorization
Risk-Based Thresholding for Reliable Anomaly Detection in Concentrated Solar Power Plants
Training Restricted Boltzmann Machines with Overlapping Partitions
Discovery of Generalized Association Rules with Multiple Minimum Supports
Dep-L 0 : Improving L 0 -Based Network Sparsification via Dependency Modeling
Visual Analysis of a Research Group's Performance thanks to Linked Open Data
Detecting Anomalies with Autoencoders on Data Streams
DeMis: Data-Efficient Misinformation Detection Using Reinforcement Learning
Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits
L1-Depth Revisited: A Robust Angle-Based Outlier Factor in High-Dimensional Space
Algebraic Techniques for Analysis of Large Discrete-Valued Datasets
Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics
SkipCas: Information Diffusion Prediction Model Based on Skip-Gram
HCT: A Hierarchical Contrastive Learning Framework for Transferable Graph Anomaly Detection
Finding Incident-Related Social Media Messages for Emergency Awareness
Mining All Non-derivable Frequent Itemsets
An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering
Implicit Linking of Food Entities in Social Media
Boolean Reasoning Scheme with Some Applications in Data Mining
Adaptive Seasonal-Trend Decomposition for Streaming Time Series Data with Transitions and Fluctuations in Seasonality
Automatic Text Summarization Using Unsupervised and Semi-supervised Learning
Exploring Fringe Settings of SVMs for Classification
An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining
Predicting Chemical Carcinogenesis Using Structural Information Only
KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
Detecting and Predicting Evidences of Insider Trading in the Brazilian Market
Hermoupolis: A Trajectory Generator for Simulating Generalized Mobility Patterns
Model-Based Reinforcement Learning with Multi-task Offline Pretraining
Exploring Thematic Coherence in Fake News
TagRec: Automated Tagging of Questions with Hierarchical Learning Taxonomy
StinkyCheese: Chat-Based Model for Subscription Classification
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems
Improved MinMax Cut Graph Clustering with Nonnegative Relaxation
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part II
Fast Conditional Network Compression Using Bayesian HyperNetworks
Rank Aggregation for Non-stationary Data Streams
Fairness of ChatGPT and the Role of Explainable-Guided Prompts
Lagrangian Duality for Constrained Deep Learning
Learning a Fair Distance Function for Situation Testing
Hypothesis Transfer in Bandits by Weighted Models
Alternate Geometric and Semantic Denoising Diffusion for Protein Inverse Folding
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings
Adversarial Magnification to Deceive Deepfake Detection Through Super Resolution
Optimized Substructure Discovery for Semi-structured Data
Invariant Time-Series Classification
Modeling Dynamic Heterogeneous Network for Link Prediction Using Hierarchical Attention with Temporal RNN
Engine Misfire Detection with Pervasive Mobile Audio
Optimizing Delegation Between Human and AI Collaborative Agents
Cluster Aggregate Inequality and Multi-level Hierarchical Clustering
GANNSTER: Graph-Augmented Neural Network Spatio-Temporal Reasoner for Traffic Forecasting
On the Convergence of DEM's Linear Parameter Estimator
Loss Functions in Diffusion Models: A Comparative Study
Materialized Data Mining Views
Hypernetworks Build Implicit Neural Representations of Sounds
TS-MIoU: A Time Series Similarity Metric Without Mapping
Mining Positional Data Streams
Deep Query Ranking for Question Answering over Knowledge Bases
Principles of Data Mining and Knowledge Discovery, 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001, Proceedings
Incremental Nonlinear PCA for Classification
The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II
ClusTR: Exploring Multivariate Cluster Correlations and Topic Trends
Direct-Effect Risk Minimization for Domain Generalization
Noisy Matrix Completion Using Alternating Minimization
Characterization and Early Detection of Evergreen News Articles
Temporal Density Extrapolation
Structure Pattern Analysis and Cascade Prediction in Social Networks
Scalable Large Margin Gaussian Process Classification
The Simpler The Better: An Entropy-Based Importance Metric to Reduce Neural Networks' Depth
Efficient and Less Centralized Federated Learning
Automated Discovery of Polynomials by Inductive Genetic Programming
Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers
A Workflow for Generating Patient Counterfactuals in Lung Transplant Recipients
Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model
Right to Information Query Modelling via Graded Response Model
Finding Association Rules That Trade Support Optimally against Confidence
ALADIN: A New Approach for Drug-Target Interaction Prediction
Deconstructing Kernel Machines
Unsupervised Trajectory Sampling
Joint User Modeling Across Aligned Heterogeneous Sites Using Neural Networks
Football Player's Performance and Market Value
An l1 Regularization Framework for Optimal Rule Combination
Fairness is in the Details : Face Dataset Auditing
Key Point Selection and Clustering of Swimmer Coordination Through Sparse Fisher-EM
Semi-supervised Discriminant Analysis Via CCCP
Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test
SEEDOT: Tool for Enhancing Sentiment Lexicon with Machine Learning
Event-Based Predictive Maintenance on Top of Sensor Data in a Real Industry 4.0 Case Study
AEMLO: AutoEncoder-Guided Multi-label Oversampling
Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformers
Network Regression with Predictive Clustering Trees
Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks
Algorithms and Challenges on the GeoWeb
Spatio-Temporal Tensor Sketching via Adaptive Sampling
On Learning from Taxi GPS Traces (Preamble)
Robust Training of Graph Convolutional Networks via Latent Perturbation
Self-improvement for Computerized Adaptive Testing
Learning to Detect Online Harassment on Twitter with the Transformer
Rules, Subgroups and Redescriptions as Features in Classification Tasks
Evidence of Temporal Artifacts in Social Networks
What Can Hawk-Eye Data Reveal about Serve Performance in Tennis?
A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules
Reinforcement Learning through Global Stochastic Search in N-MDPs
Imbalanced Data Stream Classification Using Hybrid Data Preprocessing
Learnable Diffusion for Wavelets in Scattering Networks: Towards both Interpretability and Performance in Graph Representation Learning
Consistent and Tractable Algorithm for Markov Network Learning
Generalizing Reward Modeling for Out-of-Distribution Preference Learning
Nearest Neighbour Classification with Monotonicity Constraints
PerTurbo: A New Classification Algorithm Based on the Spectrum Perturbations of the Laplace-Beltrami Operator
Discovering Evolution Chains in Dynamic Networks
Resource-Constrained On-Device Learning by Dynamic Averaging
Multi-objective Optimization for Power Load Recommendation Considering User's Comfort
SOREX : Subspace Outlier Ranking Exploration Toolkit
Tag Sources for Recommendation in Collaborative Tagging Systems
Matching the Expert's Knowledge via a Counterfactual-Based Feature Importance Measure
ViBERTgrid BiLSTM-CRF: Multimodal Key Information Extraction from Unstructured Financial Documents
Large-Scale Multi-label Text Classification - Revisiting Neural Networks
Conditional Log-linear Models for Mobile Application Usage Prediction
Fairbeat: Assessing and Mitigating Bias with the Composite Balance Score
Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification
Intelligent Interaction with the Real World
Efficient Bi-objective Team Formation in Social Networks
Domain Adaptation of Conditional Probability Models Via Feature Subsetting
SALER: A Data Science Solution to Detect and Prevent Corruption in Public Administration
Dependency Detection in MobiMine and Random Matrices
Cost-Aware Early Classification of Time Series
Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part I
Hybrid Technique for Artificial Neural Network Architecture and Weight Optimization
TIDS: A Thermal Imaging Dataset for Subclinical Mastitis in Dairy Sheep
Thresholding of Semantic Similarity Networks Using a Spectral Graph-Based Technique
Monitoring the Business Cycle with Fine-Grained, Aspect-Based Sentiment Extraction from News
A Fast Method of Statistical Assessment for Combinatorial Hypotheses Based on Frequent Itemset Enumeration
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting
Fair Kernel Learning
Compositional Models for Reinforcement Learning
Learning Semantically Coherent Rules
Feature Selection for Density Level-Sets
Counterfactual Explanations for Remote Sensing Time Series Data: An Application to Land Cover Classification
Spatio-Temporal Multi-graph Networks for Demand Forecasting in Online Marketplaces
A Left Realist Critique of the Political Value of Adopting Machine Learning Systems in Criminal Justice
Multi-Task Boosting by Exploiting Task Relationships
Interpreting Atypical Conditions in Systems with Deep Conditional Autoencoders: The Case of Electrical Consumption
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IX
Learning to Predict One or More Ranks in Ordinal Regression Tasks
Decompose, Then Reconstruct: A Framework of Network Structures for Click-Through Rate Prediction
Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance Company
Finding Outlying Items in Sets of Partial Rankings
Explaining an Image Classifier with a Generative Model Conditioned by Uncertainty
A Classification of Anomaly Explanation Methods
Certifiable Active Class Selection in Multi-Class Classification
Shallow Text Clustering Does Not Mean Weak Topics: How Topic Identification Can Leverage Bigram Features
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection
Self Hyper-parameter Tuning for Stream Recommendation Algorithms
Laplacian Spectrum Learning
Transfer Learning for Time Series Anomaly Detection
Hypotensive Episode Prediction in ICUs via Observation Window Splitting
Malware Detection by Analysing Encrypted Network Traffic with Neural Networks
Guess the Movie - Linking Facebook Pages to IMDb Movies
VHI: Valve Health Identification for the Maintenance of Subsea Industrial Equipment
Incremental Aspect Models for Mining Document Streams
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport
Introducing Total Harmonic Resistance for Graph Robustness Under Edge Deletions
Agents Teaching Agents in Reinforcement Learning (Nectar Abstract)
Rule Discovery in Large Time-Series Medical Databases
SNOUT: An Intelligent Assistant for Exploratory Data Anaylsis
Fast Estimation of the Pattern Frequency Spectrum
Random Matrices in Data Analysis
Discovering Image-Text Associations for Cross-Media Web Information Fusion
GNN Transformation Framework for Improving Efficiency and Scalability
Learning with Configurable Operators and RL-Based Heuristics
Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics
Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication
Efficient Decentralized Deep Learning by Dynamic Model Averaging
Parametric t-Distributed Stochastic Exemplar-Centered Embedding
Attribute Conjunction Learning with Recurrent Neural Network
Link Prediction via Higher-Order Motif Features
On Identifying Fast Road Races: Decomposing Race Conditions and Individual Performance Level
Monitoring Technoscientific Issues in the News
Multiple Instance Learning with Bag-Level Randomized Trees
Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System
Pruning Relations for Substructure Discovery of Multi-relational Databases
Do Street Fairs Boost Local Businesses? A Quasi-Experimental Analysis Using Social Network Data
Attributed Graph Clustering with Unimodal Normalized Cut
PROMO for Interpretable Personalized Social Emotion Mining
Supervised Graph Contrastive Learning for Few-Shot Node Classification
PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data
Learning Perceptual Position-Aware Shapelets for Time Series Classification
MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data
VIPER - Visual Pattern Explorer
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification
Compact Representation of a Multi-dimensional Combustion Manifold Using Deep Neural Networks
A Geometric Approach to Find Nondominated Policies to Imprecise Reward MDPs
Deep Model Compression via Two-Stage Deep Reinforcement Learning
The Vanishing Empirical Variance in Randomly Initialized Deep ReLU Networks
How Many Topics? Stability Analysis for Topic Models
Propositionalization Online
Efficient Name Disambiguation for Large-Scale Databases
G-GLformer: Transformer with GRU Embedding and Global-Local Attention for Multivariate Time Series Forecasting
Learning a Contextual and Topological Representation of Areas-of-Interest for On-Demand Delivery Application
Sample Noise Impact on Active Learning
Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods
Progressive Dual-Space Discovering of Unknowns for Source-Free Open-Set Domain Adaptation
A Hybrid Distance-Based Method and Support Vector Machines for Emotional Speech Detection
Trend Mining in Dynamic Attributed Graphs
CEM-Visualisation and Discovery in Email
RSSI-Based Supervised Learning for Uncooperative Direction-Finding
Interactive Learning from Multiple Noisy Labels
Exploratory Attributes Search for Time-Series Data: An Experimental System for Agricultural Application
Collective Information Extraction with Context-Specific Consistencies
Decoupling Sparsity and Smoothness in Dirichlet Belief Networks
Classification in Very High Dimensional Problems with Handfuls of Examples
IntentBreaker: Intent-Adaptive Jailbreak Attack on Large Language Models
Principled Interpolation in Normalizing Flows
Causal Explanation of Convolutional Neural Networks
Highly Dimensional Problems in Computational Advertising
When Efficient Model Averaging Out-Performs Boosting and Bagging
An Interactive Tool for Interpretability of Time Series Classification
Incremental Local Evolutionary Outlier Detection for Dynamic Social Networks
Improving Dissimilarity Functions with Domain Knowledge, Applications with IKBS System
Detecting Potential Subscribers on Twitch: A Text Mining Approach with XGBoost - Discovery Challenge ChAT: CoolStoryBob
Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs
Improving Maximum Margin Matrix Factorization
F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets
Mental State Classification Using EEG Signals: Ethics, Law and Challenges
Waypoint Generation in Row-Based Crops with Deep Learning and Contrastive Clustering
Factor Models for Tag Recommendation in BibSonomy
Metamorphic Malware Behavior Analysis Using Sequential Pattern Mining
Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer
Data Generation Process Modeling for Activity Recognition
Learning to Augment Graph Structure for both Homophily and Heterophily Graphs
Proceedings of the Workshop on Large-Scale Time Dependent Graphs (TD-LSG 2017) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017
GMMbuilder - User-Driven Discovery of Clustering Structure for Bioarchaeology
Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns
Principles of Data Mining and Knowledge Discovery, Second European Symposium, PKDD '98, Nantes, France, September 23-26, 1998, Proceedings
Forecasting and Visualization of Renewable Energy Technologies Using Keyword Taxonomies
Multimodal Deep Networks for Text and Image-Based Document Classification
POLAR: Attention-Based CNN for One-Shot Personalized Article Recommendation
Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach
Diversity-Based Generalization for Unsupervised Text Classification Under Domain Shift
Integrating Renewable Energy in Agriculture: A Deep Reinforcement Learning-Based Approach
Predicting Pass Receiver In Football Using Distance Based Features
Discovery of Common Subsequences in Cognitive Evoked Potentials
Transductive Minimax Probability Machine
EgoMap: Projective Mapping and Structured Egocentric Memory for Deep RL
Improvements in the Data Partitioning Approach for Frequent Itemsets Mining
Adaptive Multi-space Defense Framework Against Adversarial Attacks
Sparse Gaussian Processes for Multi-task Learning
Supervised Learning of Semantic Relatedness
From Disentangled Representation to Concept Ranking: Interpreting Deep Representations in Image Classification Tasks
A Classification Based Scoring Function for Continuous Time Bayesian Network Classifiers
Team-Imitate-Synchronize for Solving Dec-POMDPs
Improving the Performance of the RISE Algorithm
Graph Contrastive Representation Learning with Input-Aware and Cluster-Aware Regularization
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning
SimSky: An Accuracy-Aware Algorithm for Single-Source SimRank Search
A Probabilistic Ranking Approach for Tag Recommendation
Bandits for Sponsored Search Auctions Under Unknown Valuation Model: Case Study in E-Commerce Advertising
Hybrid Connection and Host Clustering for Community Detection in Spatial-Temporal Network Data
A Unified and Flexible Framework for Comparing Simple and Complex Patterns
Neuro-symbolic Artificial Intelligence for Patient Monitoring
AutoML for Predictive Maintenance: One Tool to RUL Them All
Experience STORIES: A Visual News Search and Summarization System
Protecting Sensitive Topics in Text Documents with PROTEXTOR
Rank Measures for Ordering
Exploiting Causal Knowledge During CATE Estimation Using Tree Based Metalearners