yusuke1997/dblp-id-title huggingface dataset:
A Kernel Based Method for Discovering Market Segments in Beef Meat
IICE: Web Tool for Automatic Identification of Chemical Entities and Interactions
Automatic Construction and Refinement of a Class Hierarchy over Multi-valued Data
Relative Comparison Kernel Learning with Auxiliary Kernels
Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems
Longitudinal Surveys Are Texts: LLM-Enhanced Analysis of School Attendance in New Zealand
IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages
Monitoring Physical Activity and Mental Stress Using Wrist-Worn Device and a Smartphone
Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting
Italian Debate on Measles Vaccination: How Twitter Data Highlight Communities and Polarity
Ethical and Technological AI Risks Classification: A Human Vs Machine Approach
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
Target-Adaptive Structure-Semantic Consistency for Unsupervised Graph Domain Adaptation
Go Green: A Decision-Tree Framework to Select Optimal Box-Sizes for Product Shipments
A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis
Using a Hash-Based Method for Apriori-Based Graph Mining
WildInsight: a Chatbot for Wildlife Conservation Research
Non-dissipative Propagation by Randomized Anti-symmetric Deep Graph Networks
Language Support for Temporal Data Mining
SLSGD: Secure and Efficient Distributed On-device Machine Learning
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
A Recommendation System for CAD Assembly Modeling Based on Graph Neural Networks
Implication-Based Fuzzy Association Rules
Declarative Modeling for Machine Learning and Data Mining
How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning
Learning from Our Movements - The Mobility Data Analytics Era
ASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis
Online Binary Incomplete Multi-view Clustering
GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-Based Social Networks
Primula-3for Probabilistic Modeling and Reasoning on Graph Data
Automated Quality Assurance for Hand-Held Tools via Embedded Classification and AutoML
MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds
A Principle of Least Action for the Training of Neural Networks
Hardware Acceleration of Machine Learning Beyond Linear Algebra
Logical Calculi for Knowledge Discovery in Databases
ScienScan - An Efficient Visualization and Browsing Tool for Academic Search
Joint Learning for Cyclone Track Nowcasting
Is There a Best Quality Metric for Graph Clusters?
Contextual Itemset Mining in DBpedia
What Drives Online Popularity: Author, Content or Sharers? Estimating Spread Dynamics with Bayesian Mixture Hawkes
TagMiner: A Semisupervised Associative POS Tagger Effective for Resource Poor Languages
Feature Selection by Transfer Learning with Linear Regularized Models
Document Classification Through Interactive Supervision of Document and Term Labels
Instructional Video Summarization Using Attentive Knowledge Grounding
Ageing-Based Multinomial Naive Bayes Classifiers Over Opinionated Data Streams
Physical Performance Optimization in Football
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017
Information-Bottleneck Approach to Salient Region Discovery
Scalable Interactive Data Visualization
Discretization and Grouping: Preprocessing Steps for Data Mining
Evaluation of the Limit of Detection in Network Dataset Quality Assessment with PerQoDA
Ranked Rules and Data Visualization
Diversity Regularized Ensemble Pruning
Interactive Anomaly Detection Based on Clustering and Online Mirror Descent
Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization
Detection of Harassment on Twitter with Deep Learning Techniques
Linear Discriminant Dimensionality Reduction
A Heterogeneous Propagation Graph Model for Rumor Detection Under the Relationship Among Multiple Propagation Subtrees
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees
Adaptive Knowledge Distillation for Classification of Hand Images Using Explainable Vision Transformers
Spoofing Transaction Detection with Group Perceptual Enhanced Graph Neural Network
Knowledge Integration in Deep Clustering
Ensemble Methods for Stock Market Prediction
Interactive Time Series Clustering with COBRASTS
Session Target Pair: User Intent Perceiving Networks for Session-Based Recommendation
On the Stratification of Multi-label Data
Movement Behaviour Recognition for Water Activities
Attentive Multi-Layer Perceptron for Non-autoregressive Generation
ProxyLLM : LLM-Driven Framework for Customer Support Through Text-Style Transfer
Tractable Models for Information Diffusion in Social Networks
A Framework for Data Mining Pattern Management
The Growing Semantic Web
Backdoor Attacks on Graph Classification via Data Augmentation and Dynamic Poisoning
Co-attention and Contrastive Learning Driven Knowledge Tracing
Phenotype Inference from Text and Genomic Data
Generalized Modularity for Community Detection
Maximizing Time-Decaying Influence in Social Networks
Learning Optimal Decision Trees Under Memory Constraints
Detection of Interdependences in Attribute Selection
Propagation Structure-Semantic Transfer Learning for Robust Fake News Detection
A Classification Approach for Prediction of Target Events in Temporal Sequences
Physics-Informed Spatio-Temporal Model for Human Mobility Prediction
Companion Guided Soft Margin for Face Recognition
Flexible Shift-Invariant Locality and Globality Preserving Projections
IDEA: An Interactive Dialogue Translation Demo System Using Furhat Robots
Learning Overspecified Gaussian Mixtures Exponentially Fast with the EM Algorithm
Your Privacy, My Privacy? On Leakage Risk Assessment in Online Social Networks
Ensuring the Inclusive Use of NLP in the Global Response to COVID-19
Monitoring Patterns through an Integrated Management and Mining Tool
Identifying Features of Constructive Journalism in News Articles: An Explainable ML Approach
TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks
Eigenvector Sensitive Feature Selection for Spectral Clustering
Efficient Estimation of AUC in a Sliding Window
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III
A Multivariate and Multi-step Ahead Machine Learning Approach to Traditional and Cryptocurrencies Volatility Forecasting
Complex Localization in the Multiple Instance Learning Context
Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier
Practical Black Box Model Inversion Attacks Against Neural Nets
Asynchronous Distributed Incremental Computation on Evolving Graphs
Efficient Bayesian Updates for Deep Active Learning via Laplace Approximations
Multi-objective Particle Swarm Optimization for Feature Selection in Credit Scoring
Bayesian Active Clustering with Pairwise Constraints
State-Dependent Exploration for Policy Gradient Methods
Neural Models for Factual Inconsistency Classification with Explanations
I-GLIDE: Input Groups for Latent Health Indicators in Degradation Estimation
Uncertainty Quantification for Black-Box LLMs via Star Graphs Connectivity: Exploring Alternatives for Semantic Density
Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings
Basis of Fuzzy Knowledge Discovery System
Towards Few-Shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-Guided Neural Process Approach
Learning Neighborhoods for Metric Learning
Ubiquitous Social Media Analysis - Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers
HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses
Optimizing Neural Networks for Patent Classification
Graph Neural Network Leveraging Higher-Order Class Label Connectivity for Heterophilous Graphs
Generalized Online Sparse Gaussian Processes with Application to Persistent Mobile Robot Localization
Relaxed Transfer of Different Classes via Spectral Partition
Network Cooperation with Progressive Disambiguation for Partial Label Learning
Study on Meta-Learning Approach Application in Rank Aggregation Algorithm Selection
Interpretable Survival Gradient Boosting Models with Bagged Trees Base Learners
A Fast Method for Training Linear SVM in the Primal
Best Practices to Train Deep Models on Imbalanced Datasets - A Case Study on Animal Detection in Aerial Imagery
Detecting Swimmers in Unconstrained Videos with Few Training Data
Target to Source Coordinate-Wise Adaptation of Pre-trained Models
μYOLO: Towards Single-Shot Object Detection on Microcontrollers
Rough Dependencies as a Particular Case of Correlation: Application to the Calculation of Approximative Reducts
Applications of Machine Learning in Dota 2: Literature Review and Practical Knowledge Sharing
Synthetic Graph Generation from Finely-Tuned Temporal Constraints
k^2 k 2 -means for Fast and Accurate Large Scale Clustering
Query Log Mining for Inferring User Tasks and Needs
Statistics-Free Interpolation of Ocean Observations with Deep Spatio-Temporal Prior (short paper)
Mathematical Optimization of Design Parameters of Photovoltaic Module
ARTEMIS: Assessing the Similarity of Event-Interval Sequences
Representation Learning on Multi-layered Heterogeneous Network
A Semi-discriminative Approach for Sub-sentence Level Topic Classification on a Small Dataset
Better Features, Better Calibration: A Simple Fix for Overconfident Networks
Learning with Imbalanced Domains: Preface
Towards Explainable Meta-learning
Explainable Learning with Hierarchical Online Deterministic Annealing
Learning Submodular Functions
(Blue) Taxi Destination and Trip Time Prediction from Partial Trajectories
Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing, DMNLP 2016, co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2016, Riva del Garda, Italy, September 23, 2016
Optimizing Disjunctive Association Rules
Cybersecurity for Smart Cities: A Brief Review
Collective Traffic Forecasting
Integer Bayesian Network Classifiers
Nonparametric Bayesian Deep Visualization
A Dual-Channel Heterogeneous Hypergraph Convolutional Network for Dual-target Cross-domain Recommendation
Exploring Latent Sparse Graph for Large-Scale Semi-supervised Learning
QUEST: Query Expansion Using Synonyms over Time
Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition
Machine Learning and Data Mining for Sports Analytics - 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings
Generalized Chronicles for Temporal Sequence Classification
Balancing Energy Flexibilities Through Aggregation
On the Granularity of Explanations in Model Agnostic NLP Interpretability
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V
Practical and General Backdoor Attacks Against Vertical Federated Learning
Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis
Generating Workflow Graphs Using Typed Genetic Programming
Pareto Multi-objective Alignment for Language Models
Rényi Divergence Deep Mutual Learning
Facial Analysis Systems and Down Syndrome
Unimodal Strategies in Density-Based Clustering
Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News Without Modifying it
MT-HCCAR: Multi-task Deep Learning with Hierarchical Classification and Attention-Based Regression for Cloud Property Retrieval
Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge
Adaptive Constraint Pushing in Frequent Pattern Mining
MuSE: A Multi-scale Emotional Flow Graph Model for Empathetic Dialogue Generation
Approximate Probabilistic Power Flow
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I
Online Feature Selection by Adaptive Sub-gradient Methods
Empirical Study of Relational Learning Algorithms in the Phase Transition Framework
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration
Transductive Classification via Dual Regularization
ARConvL: Adaptive Region-Based Convolutional Learning for Multi-class Imbalance Classification
Multi-future Merchant Transaction Prediction
A Robustness Measure of Association Rules
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
Majority Classification by Means of Association Rules
Gathering and Exploiting Higher-Order Information when Training Large Structured Models
Finding Dynamic Co-evolving Zones in Spatial-Temporal Time Series Data
An Effective Recommender System for Highly Dynamic and Large Web Sites
Cross-Modal Causal Scheduling for Enhancing Target-Oriented Multi-modal Sentiment Classification
The Good, The Bad, and The Average: Benchmarking of Reconstruction Based Multivariate Time Series Anomaly Detection
A Fast and Simple Method for Mining Subsequences with Surprising Event Counts
Fast Inbound Top-K Query for Random Walk with Restart
Unbiased Recommendation Through Invariant Representation Learning
On the Use of Self-Organizing Maps for Clustering and Visualization
FROB: Few-Shot ROBust Model for Joint Classification and Out-of-Distribution Detection
TeleComVis: Exploring Temporal Communities in Telecom Networks
A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving
Machine Learning Assists the Classification of Reports by Citizens on Disease-Carrying Mosquitoes
Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty
Expectation Propagation for Bayesian Multi-task Feature Selection
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
Progressive Supervision for Node Classification
Semi-supervised Blockmodelling with Pairwise Guidance
Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles
RSDC'09: Tag Recommendation Using Keywords and Association Rules
From Black Box to Glass Box: Evaluating the Faithfulness of Process Predictions with GCNNs
BoostMF: Boosted Matrix Factorisation for Collaborative Ranking
Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Hierarchical Distance-Based Conceptual Clustering
From Empirical Analysis to Public Policy: Evaluating Housing Systems for Homeless Youth
CDPS: Constrained DTW-Preserving Shapelets
Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer
PIQARD System for Experimenting and Testing Language Models with Prompting Strategies
Fast Support Vector Machines for Structural Kernels
Merging Embedded Topics with Optimal Transport for Online Topic Modeling on Data Streams
VeriDL: Integrity Verification of Outsourced Deep Learning Services
MINI: Mining Informative Non-redundant Itemsets
Product Reputation Model: An Opinion Mining Based Approach
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part III
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part V
Anonymizing Data with Relational and Transaction Attributes
MESS: Coarse-Grained Modular Two-Way Dialogue Entity Linking Framework
Counterfactual-Based Root Cause Analysis for Dynamical Systems
Bayesian Multi-head Convolutional Neural Networks with Bahdanau Attention for Forecasting Daily Precipitation in Climate Change Monitoring
A Filter-Based Neural ODE Approach for Modelling Natural Systems with Prior Knowledge Constraints
Speech-to-Visualization: Toward End-to-End Speech-Driven Data Visualization Generation from Natural Language Questions
Large-Scale Clustering through Functional Embedding
Stochastic Adversarial Gradient Embedding for Active Domain Adaptation
KL Regularized Normalization Framework for Low Resource Tasks
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
Content- and Graph-based Tag Recommendation: Two Variations
Rejection Ensembles with Online Calibration
OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation
A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements
Adaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery
A Condensed Representation of Itemsets for Analyzing Their Evolution over Time
Transfer Learning with Multiple Sources via Consensus Regularized Autoencoders
Learning Parsers for Technical Drawings
Leveraging Gradient Information for Out-of-Domain Performance Estimations
A Fully Automated Periodicity Detection in Time Series
Inferring Unusual Crowd Events from Mobile Phone Call Detail Records
Semi-supervised Tensor Factorization for Brain Network Analysis
On the Difficulty of Designing Processor Arrays for Deep Neural Networks
BelMan: An Information-Geometric Approach to Stochastic Bandits
A New Natural Policy Gradient by Stationary Distribution Metric
Early Classification of Time Series as a Non Myopic Sequential Decision Making Problem
Corpus-Based Relation Extraction by Identifying and Refining Relation Patterns
Identifying Disputed Topics in the News
Topic Modeling for Personalized Recommendation of Volatile Items
A Pre-screening Approach for Faster Bayesian Network Structure Learning
An Embedded Continual Learning System for Facial Emotion Recognition
OpenML: A Collaborative Science Platform
Transfer Spectral Clustering
Neural User Embedding from Browsing Events
Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database
Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets
A Joint Analysis of Trajectory Mining and Process Mining for Smartphone User Behaviour
Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation
Continual Visual Reinforcement Learning with A Life-Long World Model
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part VI
Efficient Estimation of General Additive Neural Networks: A Case Study for CTG Data
Fast kNN Graph Construction with Locality Sensitive Hashing
Interestingness-Driven Diffusion Process Summarization in Dynamic Networks
A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction
Learning Graph-Based Representations for Continuous Reinforcement Learning Domains
Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval
GRETEL 2.0: Generation and Evaluation of Graph Counterfactual Explanations Evolved
Towards Automatic Feature Construction for Supervised Classification
Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19
Clustering and Prediction of Mobile User Routes from Cellular Data
RankMerging: Learning to Rank in Large-scale Social Networks
FCFL: A Fairness Compensation-Based Federated Learning Scheme with Accumulated Queues
Properly Acting under Partial Observability with Action Feasibility Constraints
Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width
A Dynamic Clustering Algorithm for Mobile Objects
Assessing Frailty Using Behavioral and Physical Health Data in Everyday Living Settings
Probabilistic Frequent Subtree Kernels
Joint Semi-supervised Similarity Learning for Linear Classification
Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models
Statistical Hypothesis Testing in Positive Unlabelled Data
A User-Driven Process for Mining Association Rules
Unsupervised Feature Analysis with Class Margin Optimization
SaccadeDet: A Novel Dual-Stage Architecture for Rapid and Accurate Detection in Gigapixel Images
Dealing with Imbalanced Data in Multi-class Network Intrusion Detection Systems Using XGBoost
Native Advertisement Selection and Allocation in Social Media Post Feeds
A Unified View of Matrix Factorization Models
Ancestor Relations in the Presence of Unobserved Variables
Semi-supervised Projection Clustering with Transferred Centroid Regularization
Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint
Support Vector Machines, Data Reduction, and Approximate Kernel Matrices
Future Locations Prediction with Uncertain Data
Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information
Physics-Based Region Clustering to Boost Inference on Computational Fluid Dynamics Flow Fields
Local Outlier Detection with Interpretation
Enhancing Performance of Occlusion-Based Explanation Methods by a Hierarchical Search Method on Input Images
Learning the Difference between Partially Observable Dynamical Systems
Discovery of Diagnostic Patterns from Protein Sequence Databases
FastPoint: Scalable Deep Point Processes
Learning Subgraph Patterns from text for Extracting Disease - Symptom Relationships
Event Detection and Summarization Using Phrase Network
Large Margin vs. Large Volume in Transductive Learning
BipNRL: Mutual Information Maximization on Bipartite Graphs for Node Representation Learning
Efficient Density Clustering Method for Spatial Data
Predicting Tennis Serve Directions with Machine Learning
No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects
On Structured Output Training: Hard Cases and an Efficient Alternative
An Educational News Dataset for Recommender Systems
The autofeat Python Library for Automated Feature Engineering and Selection
Bag-of-Temporal-SIFT-Words for Time Series Classification
MEAN: Multi-Expert Adaptive Network For Customer Lifetime Value Prediction
Harnessing Superclasses for Learning from Hierarchical Databases
Mobile Game Theory with Street Gangs
Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport
Adaptively Denoising Graph Neural Networks for Knowledge Distillation
Pre-processing Large Spatial Data Sets with Bayesian Methods
On Calibration of Mathematical Finance Models by Hypernetworks
Federated Multi-view Matrix Factorization for Personalized Recommendations
An Efficient Algorithm for Computing Entropic Measures of Feature Subsets
Human Dynamics: From Human Mobility to Predictability
On Oblique Random Forests
A Self-attention Network Based Node Embedding Model
PATHATTACK: Attacking Shortest Paths in Complex Networks
Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context
BeeTLe: A Framework for Linear B-Cell Epitope Prediction and Classification
Cloud Imputation for Multi-sensor Remote Sensing Imagery with Style Transfer
Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning
Forecast of Study Success in the STEM Disciplines Based Solely on Academic Records
Localized Heat Kernel for Graph Neural Networks
Deep Discrete Hashing with Self-supervised Pairwise Labels
Sampling a Longer Life: Binary versus One-class classification Revisited