yusuke1997/dblp-id-title huggingface dataset:
PuzzleShuffle: Undesirable Feature Learning for Semantic Shift Detection
Exploring Chance in NCAA Basketball
Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints
Discovery of Characteristic subgraph Patterns Using Relative Indexing and the Cascade Model
Supporting Case Acquisition and Labelling in the Cotext of Web Mining
Finding High-Value Training Data Subset Through Differentiable Convex Programming
Algorithms for Optimizing the Ratio of Monotone k-Submodular Functions
Stacked-MLkNN: A stacking based improvement to Multi-Label k-Nearest Neighbours
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration for Exosuit Personalization
Insight4News: Connecting News to Relevant Social Conversations
GraphWeave : Interpretable and Robust Graph Generation via Random Walk Trajectories
Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks
Leveraging Free Labels to Power up Heterophilic Graph Learning in Weakly-Supervised Settings: An Empirical Study
MIL: Automatic Metaphor Identification by Statistical Learning
RBNets: A Reinforcement Learning Approach for Learning Bayesian Network Structure
Leiden-Fusion Partitioning Method for Effective Distributed Training of Graph Embeddings
The Interpretable Representation of Football Player Roles Based on Passing/Receiving Patterns
Trees and Induction Graphs for Multivariate Response
Valve Health Identification Using Sensors and Machine Learning Methods
GBRF: A Novel Framework for Encoding User-Preferences in Imbalanced Data Distributions via Genetic Optimization
A New Algorithm for Faster Mining of Generalized Association Rules
Identifying Avatar Aliases in StarCraft 2
Characterization of Novel HIV Drug Resistance Mutations Using Clustering, Multidimensional Scaling and SVM-Based Feature Ranking
Wikipedia Vandal Early Detection: From User Behavior to User Embedding
Concurrent Inference of Topic Models and Distributed Vector Representations
Exploring Dynamic Embeddedness: a Network Analysis of the Global Pharmaceutical Industry 1991-2012
Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space
Digging into Acceptor Splice Site Prediction: An Iterative Feature Selection Approach
Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification
Inductive Unsupervised Domain Adaptation for Few-Shot Classification via Clustering
InterDiff: Synthesizing Financial Time Series with Inter-Stock Correlations via Classifier-Free Guided Diffusion
Demand-Driven Tag Recommendation
Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery
Escaping Saddle Points of Empirical Risk Privately and Scalably via DP-Trust Region Method
Sentiment Informed Cyberbullying Detection in Social Media
More General and Effective Model Compression via an Additive Combination of Compressions
BestTime: Finding Representatives in Time Series Datasets
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 III
Effectively Grouping Trajectory Streams
Graph Homomorphism Features: Why Not Sample?
Football Pass Prediction Using Player Locations
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part IV
Learning Optimal Linear Precoding for Cell-Free Massive MIMO with GNN
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines
A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching
VAMBC: A Variational Approach for Mobility Behavior Clustering
Breaking Free: Decoupling Forced Systems with Laplace Neural Networks
Differentially Private Hypothesis Transfer Learning
Sparsity in Deep Neural Networks - An Empirical Investigation with TensorQuant
Differentially Private Learning from Label Proportions
An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making
Explainable Artificial Intelligence in Medical Diagnostics: Insights into Alzheimer's Disease
Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure
VIAL-AD: Visual Interactive Labelling for Anomaly Detection - An Approach and Open Research Questions
Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data
Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation
Semi-supervised Siamese Networks for Change Recognition with VHR Imagery
Semi-Supervised Consensus Clustering for ECG Pathology Classification
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III
A Study of Synthetic Oversampling for Twitter Imbalanced Sentiment Analysis
FCNN: Fourier Convolutional Neural Networks
Continual Model-Based Reinforcement Learning for Data Efficient Wireless Network Optimisation
Topic Sentiment Joint Model with Word Embeddings
Does Training Affect Match Performance? A Study Using Data Mining And Tracking Devices
Iterative Corpus Refinement for Materials Property Prediction Based on Scientific Texts
Multilevel Conditional Fuzzy C-Means Clustering of XML Documents
Ideas Worth Spreading: A Free Energy Proposal for Cumulative Cultural Dynamics
Error Prediction with Partial Feedback
Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks
Desiderata for Explainable AI in Statistical Production Systems of the European Central Bank
AUDIO: An Integrity Audi ting Framework of O utlier-Mining-as-a-Service Systems
Boot-Strapping Language Identifiers for Short Colloquial Postings
An Application of Data Mining to the Problem of the University Students' Dropout Using Markov Chains
Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks
Video-DPRP: A Differentially Private Approach for Visual Privacy-Preserving Video Human Activity Recognition
Uncertainty Awareness for Predicting Noisy Stock Price Movements
Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning
Conic Multi-task Classification
h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience
Data Mining at a Major Bank: Lessons from a Large Marketing Application
Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models
Distributional Correlation-Aware Knowledge Distillation for Stock Trading Volume Prediction
Towards Computation of Novel Ideas from Corpora of Scientific Text
Motion Segmentation by Model-Based Clustering of Incomplete Trajectories
Distribution Rules with Numeric Attributes of Interest
Generating Robust Counterfactual Explanations
Constrained Optimization to Improve Critical Rare Classes Performance Within the Top-Ranking Part
RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings
Learning to Have Fun
Statistical sigma-Partition Clustering over Data Streams
Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics
Deep Sketched Output Kernel Regression for Structured Prediction
Discovering Topically- and Temporally-Coherent Events in Interaction Networks
Bagging and Boosting with Dynamic Integration of Classifiers
SAGS-DynamicBio: Integrating Semantic-Aware and Graph Structure-Aware Embedding for Dynamic Biological Data with Knowledge Graphs
Mining Model Trees from Spatial Data
Calibrating the Mean-Reversion Parameter in the Hull-White Model Using Neural Networks
Decision Making in American Football: Evidence from 7 Years of NFL Data
Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme
Brexit or Bremain? Evidence from bubble analysis
Learning Structures in Earth Observation Data with Gaussian Processes
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages
Discovering Proper Neighbors to Improve Session-Based Recommendation
Interpretable Low-rank Document Representations with Label-dependent Sparsity Patterns
Higher Order Fused Regularization for Supervised Learning with Grouped Parameters
TAMOR: Tier-Aware Multi-objective Recommendation for Ant Fortune Financial Marketing
GraphJCL: A Dual-Perspective Graph-Based Framework for Urban Region Representation via Joint Contrastive Learning
Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms
Fast and Parallelizable Ranking with Outliers from Pairwise Comparisons
Efficient Hyperdimensional Computing
Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams
PDF-VQA: A New Dataset for Real-World VQA on PDF Documents
Towards Landscape Analysis in Adaptive Learning of Surrogate Models
Extracting Multilingual Relations with Joint Learning of Language Models
Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries
Analyzing Research Trends in Inorganic Materials Literature Using NLP
Overcoming the Limitations of Localization Uncertainty: Efficient and Exact Non-linear Post-processing and Calibration
Extension to C-means Algorithm for the Use of Similarity Functions
EvolvingClusters: Online Discovery of Group Patterns in Enriched Maritime Data
Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent
Learning Preferences with Hidden Common Cause Relations
Boosted Bellman Residual Minimization Handling Expert Demonstrations
Weka4WS: A WSRF-Enabled Weka Toolkit for Distributed Data Mining on Grids
CatchCore: Catching Hierarchical Dense Subtensor
Semi-supervised Co-teaching for Monitoring Motor States of Parkinson's Disease Patients
Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses
Decomposition of Aggregate Electricity Demand into the Seasonal-Thermal Components for Demand-Side Management Applications in "Smart Grids"
Hyperparameter Search Space Pruning - A New Component for Sequential Model-Based Hyperparameter Optimization
SPEEDING Up the Metabolism in E-commerce by Reinforcement Mechanism DESIGN
Differentially Private Federated Combinatorial Bandits with Constraints
Lightweight Temporal Self-attention for Classifying Satellite Images Time Series
Skeletal Cores and Graph Resilience
Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles
Neural Networks with Feature Attribution and Contrastive Explanations
Learning Geometric Representations of Objects via Interaction
Feature Weighting Strategies in Sentiment Analysis
Hierarchical Fine-Grained Visual Classification Leveraging Consistent Hierarchical Knowledge
Segment-Removal Based Stuttered Speech Remediation
Infinite Mixtures of Markov Chains
Crowdsourcing Evaluation of Saliency-Based XAI Methods
On Trustworthy Rule-Based Models and Explanations
Social Data Mining and Seasonal Influenza Forecasts: The FluOutlook Platform
Fast and Adaptive Questionnaires for Voting Advice Applications
The SPMF Open-Source Data Mining Library Version 2
Computing Association Rules Using Partial Totals
Enabling Machine Learning on the Edge Using SRAM Conserving Efficient Neural Networks Execution Approach
Prediction of Global Navigation Satellite System Positioning Errors with Guarantees
Privacy-Preserving Machine Learning in Life Insurance Risk Prediction
Reduced-Rank Local Distance Metric Learning
A Novel Web Text Mining Method Using the Discrete Cosine Transform
PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach
Persistent Roles in Online Social Networks
Statistically significant subgraphs for genome-wide association study
Mining Complex Event Patterns in Computer Networks
Explainable Abusive Language Classification Leveraging User and Network Data
Interpretation Attacks and Defenses on Predictive Models Using Electronic Health Records
Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks
Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs
Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation
AeroINR: Meta-learning for Efficient Generation of Aerodynamic Geometries
Association Rule Selection in a Data Mining Environment
Safe Exploration Method for Reinforcement Learning Under Existence of Disturbance
VC-Dimension Based Generalization Bounds for Relational Learning
Dynamic Thresholding for Accurate Crack Segmentation Using Multi-objective Optimization
Deep Adaptive Multi-intention Inverse Reinforcement Learning
A Deep Dynamic Latent Block Model for the Co-Clustering of Zero-Inflated Data Matrices
Rule-Based Active Sampling for Learning to Rank
Deep Gaussian Processes Using Expectation Propagation and Monte Carlo Methods
Exploring the Training Robustness of Distributional Reinforcement Learning Against Noisy State Observations
Learning Discriminative Sufficient Statistics Score Space for Classification
A Framework for Data Mining in Wind Power Time Series
Deep Generative Multi-view Learning
Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding
Knowledge Discovery on Blockchains: Challenges and Opportunities for Distributed Event Detection Under Constraints
Difference-Based Estimates for Generalization-Aware Subgroup Discovery
A Novel Framework for Locating Software Faults Using Latent Divergences
Performance Analysis of Data Mining Techniques for Improving the Accuracy of Wind Power Forecast Combination
Typology of Mixed-Membership Models: Towards a Design Method
Discovering Discriminative Nodes for Classification with Deep Graph Convolutional Methods
Auxiliary Guided Autoregressive Variational Autoencoders
Multiplex Community Detection for Resilient Electrical Segmentation Enabling Management of an Increasingly Complex Power Grid
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part III
Intelligent Urban Data Monitoring for Smart Cities
Non-Linear Gradient Boosting for Class-Imbalance Learning
Learning Multi-granularity Dynamic Network Representations for Social Recommendation
REBAGG: REsampled BAGGing for Imbalanced Regression
Automatic Hidden Web Database Classification
Keynote: Neurosymbolic AI: An Overview
Why Does Subsequence Time-Series Clustering Produce Sine Waves?
Mining Billion-Node Graphs: Patterns, Generators and Tools
Improving the Discovery of Association Rules with Intensity of Implication
Prototype-Guided Counterfactual Explanations via Variational Auto-encoder for Recommendation
ExAnte: Anticipated Data Reduction in Constrained Pattern Mining
Bi-directional Representation Learning for Multi-label Classification
Robust Selection Stability Estimation in Correlated Spaces
Simulation-Based Inference for Exoplanet Atmospheric Retrieval: Insights from Winning the Ariel Data Challenge 2023 Using Normalizing Flows
Time Based Tag Recommendation Using Direct and Extended Users Sets
Rate-Oriented Point-Wise Confidence Bounds for ROC Curves
Understanding and Improving Laplacian Positional Encodings for Temporal GNNs
Creating and Characterising Electricity Load Profiles of Residential Buildings
Transform Learning Based Function Approximation for Regression and Forecasting
Domain Adaptation with Maximum Margin Criterion with Application to Network Traffic Classification
Mining History of Changes to Web Access Patterns
Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams
Discovering and Visualizing Attribute Associations Using Bayesian Networks and Their Use in KDD
An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis
Ranking Researchers Through Collaboration Pattern Analysis
Inclusively: An AI-Based Assistant for Inclusive Writing
Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
Multi-stakeholder News Recommendation Using Hypergraph Learning
Team voyTECH: User Activity Modeling with Boosting Trees
A Statistical Approach to Speaker Identification in Forensic Phonetics
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space
Designing Search Space for Unbounded Bayesian Optimization via Transfer Learning
Multi-Plant Photovoltaic Energy Forecasting Challenge: Second Place Solution
Evaluation of Group Fairness Measures in Student Performance Prediction Problems
Data Transformation and Rough Sets
Manufacturing Dispatching Using Reinforcement and Transfer Learning
AST: Support for Algorithm Selection with a CBR Approach
Symbolic Distance Measurements Based on Characteristic Subspaces
Active Learning for LSTM-autoencoder-based Anomaly Detection in Electrocardiogram Readings
Approximating the Graph Edit Distance with Compact Neighborhood Representations
Basket Booster for Prototype-based Contrastive Learning in Next Basket Recommendation
Proactive Detection of Model Degradation in Financial Fraud Prediction with Delayed Labels
Molecular Graph Representation Learning via Structural Similarity Information
Imitative Learning for Online Planning in Microgrids
LinNet: Probabilistic Lineup Evaluation Through Network Embedding
Focused Multi-task Learning Using Gaussian Processes
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach
Scalable Nonnegative Matrix Factorization with Block-wise Updates
The Effects of Randomness on the Stability of Node Embeddings
Probabilistic Inference of Twitter Users' Age Based on What They Follow
On Detecting Clustered Anomalies Using SCiForest
Enhancing Fairness, Justice and Accuracy of Hybrid Human-AI Decisions by Shifting Epistemological Stances
Deep Metric Learning with Data Summarization
From Explainable AI to Human-Centered AI
Proactive Fiber Break Detection Based on Quaternion Time Series and Automatic Variable Selection from Relational Data
Algorithms for the Construction of Concept Lattices and Their Diagram Graphs
Neural Networks Comprising Sequentially Semiseparable Matrices with One Dimensional State Variable are Universal Approximators
Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting
Spectral Learning of Sequence Taggers over Continuous Sequences
Analyzing an Email Collection Using Formal Concept Analysis
CARIS: Cache Affinity-Aware Reinforced Intelligent Strategy
TDCM: Transport Destination Calibrating Based on Multi-task Learning
Koopman Spectral Kernels for Comparing Complex Dynamics: Application to Multiagent Sport Plays
Lifelong Hierarchical Topic Modeling via Nonparametric Word Embedding Clustering
A Comparison Between Block CEM and Two-Way CEM Algorithms to Cluster a Contingency Table
Abductive Plan Recognition by Extending Bayesian Logic Programs
Towards Addressing Noise and Static Variations of Analog Computations Using Efficient Retraining
New Regularized Algorithms for Transductive Learning
Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control Optimization
Bayesian Nonparametric Inverse Reinforcement Learning
Learning from Labeled and Unlabeled Documents: A Comparative Study on Semi-Supervised Text Classification
Discriminative Factor Alignment across Heterogeneous Feature Space
A Multi-criteria System for Recommending Taxi Routes with an Advance Reservation
Neural Networks in an Adversarial Setting and Ill-Conditioned Weight Space
Inductive Document Representation Learning for Short Text Clustering
Size Matters: Finding the Most Informative Set of Window Lengths
RumorMixer: Exploring Echo Chamber Effect and Platform Heterogeneity for Rumor Detection
Graphical Multi-way Models
Dropout Regularization in Extended Generalized Linear Models Based on Double Exponential Families
Rule Discovery and Probabilistic Modeling for Onomastic Data
Bayesian Matrix Co-Factorization: Variational Algorithm and Cramér-Rao Bound
LKT-FM: A Novel Rating Pattern Transfer Model for Improving Non-overlapping Cross-Domain Collaborative Filtering
Pivot-Based Distributed K-Nearest Neighbor Mining
Neural Networks Design: Rough Set Approach to Continuous Data
Deep Active Learning for Detection of Mercury's Bow Shock and Magnetopause Crossings
Missing but Not Missed: On Learnability Under Imputation
An Information Retrieval System for CBRNe Incidents
Text Mining for Finding Functional Community of Related Genes Using TCM Knowledge
Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014
Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows
Functional Bid Landscape Forecasting for Display Advertising
Forecasting of Product Quality Through Anomaly Detection
LDRNet: Enabling Real-Time Document Localization on Mobile Devices
Quality Scheme Assessment in the Clustering Process
Joint Learning of Entity Semantics and Relation Pattern for Relation Extraction
Partial Label Learning via Subspace Representation and Global Disambiguation
CycleFootprint: A Fully Automated Method for Extracting Operation Cycles from Historical Raw Data of Multiple Sensors
Temporal Exceptional Model Mining Using Dynamic Bayesian Networks
ShiftTree: An Interpretable Model-Based Approach for Time Series Classification
VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics
Sequence Labelling SVMs Trained in One Pass
Ballpark Learning: Estimating Labels from Rough Group Comparisons
Gradient Boosting Models for Photovoltaic Power Estimation Under Partial Shading Conditions
Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks
The AI Act is Coming: Are E-Health Manufacturers Ready?
Feature-Based Gait Pattern Classification for a Robotic Walking Frame
Trajectory Data Pattern Mining
Continual Neural Computation
Bidirectional Semi-supervised Learning with Graphs
DiffVersify: a Scalable Approach to Differentiable Pattern Mining with Coverage Regularization
TOPTMH: Topology Predictor for Transmembrane alpha-Helices
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part II
How Long Will She Call Me? Distribution, Social Theory and Duration Prediction
SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation
PSSDL: Probabilistic Semi-supervised Dictionary Learning
A Semi-supervised and Online Learning Approach for Non-Intrusive Load Monitoring
Integrating Constraint Programming and Itemset Mining
Breaking Through the Syntax Barrier: Searching with Entities and Relations
NSEEN: Neural Semantic Embedding for Entity Normalization
Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining
Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals
Discovering Wiring Patterns Influencing Neural Network Performance
Fairness-Aware Classifier with Prejudice Remover Regularizer
A Spectral Learning Algorithm for Finite State Transducers
Transductive Learning for Text Classification Using Explicit Knowledge Models
Hierarchical Design Space Exploration for Distributed CNN Inference at the Edge
Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications
ARKTiS - A Fast Tag Recommender System Based On Heuristics
Text Mining for Open Domain Semi-Supervised Semantic Role Labeling
Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@ECML/PKDD 2018, Dublin, Ireland, September 10, 2018
Dynamic Interpretability for Model Comparison via Decision Rules
Knowledge Transfer for Multi-labeler Active Learning
Controlling Imbalanced Error in Deep Learning with the Log Bilinear Loss
LinC: Explaining Time Series Clusterings with User-Provided Constraints
Smart Cities with Deep Edges
Stop the Clock: Are Timeout Effects Real?
Watch, Listen & Learn: Co-training on Captioned Images and Videos