yusuke1997/dblp-id-title huggingface dataset:
Estimation of Topological Dimension
Collective Kernel Construction in Noisy Environment
Mining Logical Arithmetic Expressions From Proper Representations
Distributed Top-K Outlier Detection from Astronomy Catalogs using the DEMAC System
TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification
Fast Flow-based Random Walk with Restart in a Multi-query Setting
HACS: Heuristic Algorithm for Clustering Subsets
International Workshop on Cost-Sensitive Learning, COST@SDM 2018, San Diego, California, USA, May 5, 2018
Accelerating Graph Adjacency Matrix Multiplications with Adjacency Forest
CloSpan: Mining Closed Sequential Patterns in Large Datasets
MeiKe: Influence-based Communities in Networks
Co-regularized Monotone Retargeting for Semi-supervised LeTOR
Detecting Communities in Social Networks Using Max-Min Modularity
Finding Representative Association Rules from Large Rule Collections
PNrule: A New Framework for Learning Classifier Models in Data Mining (A Case-Study in Network Intrusion Detection)
Discovering and Controlling for Latent Confounds in Text Classification Using Adversarial Domain Adaptation
Infusing Geo-Recency Mixture Models for Effective Location Prediction in LBSN
RELIANT: Fair Knowledge Distillation for Graph Neural Networks
Regularized Weighted Linear Regression for High-dimensional Censored Data
Divide and Conquer Strategies for Effective Information Retrieval
A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data
Robust Mining of Time Intervals with Semi-interval Partial Order Patterns
Language Models are Explorers for Join Discovery on Data Lakes
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training
Decision Tree Classification of Spatial Data Patterns from Videokeratography using Zernicke Polynomials
On Demand Phenotype Ranking through Subspace Clustering
Mining Patterns in Networks using Homomorphism
A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization
Incremental Mining of Constrained Association Rules
Heterogeneous Datasets Representation and Learning using Diffusion Maps and Laplacian Pyramids
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Attention-Based Autoregression for Accurate and Efficient Multivariate Time Series Forecasting
Learning to Learn Task Transformations for Improved Few-Shot Classification
SUMDocS: Surrounding-aware Unsupervised Multi-Document Summarization
A Divide-and-Conquer Algorithm for Betweenness Centrality
CORE: Nonparametric Clustering of Large Numeric Databases
Learning Correlative and Personalized Structure for Online Multi-Task Classification
Learning Bayesian Network Structure from Distributed Data
Exploring the Impact of Dynamic Mutual Influence on Social Event Participation
Topic-Level Expert Modeling in Community Question Answering
Scalable Tensor Factorizations with Missing Data
Leveraging Dependencies among Learned Temporal Subsequences
Deep Contrastive One-Class Time Series Anomaly Detection
Representation Learning for Imbalanced Cross-Domain Classification
Latent Factor Transition for Dynamic Collaborative Filtering
Interpretable Molecular Graph Generation via Monotonic Constraints
Calibrating Probability Estimation Trees using Venn-Abers Predictors
Finding Friends on a New Site Using Minimum Information
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling
CPM: A Covariance-preserving Projection Method
Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes
Product Adoption Rate Prediction: A Multi-factor View
Equipping Graph Autoencoders: Revisiting Masking Strategies from a Robustness Perspective
Online Anomaly Detection by Improved Grammar Compression of Log Sequences
Sequence-aware Heterogeneous Graph Neural Collaborative Filtering
Aerosol Optical Depth Prediction from Satellite Obsercations by Multiple Instance Regression
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data?
SimplePPT: A Simple Principal Tree Algorithm
Bregman Divergences and Triangle Inequality
Distributed Monitoring of the R2 Statistic for Linear Regression
Gaussian Process Learning for Cyber-Attack Early Warning
Pretraining Molecules with Explicit Substructure Information
Drought Detection of the Last Century: An MRF-based Approach
Nonparametric Bayesian Co-clustering Ensembles
Robust Estimation for Mixture of Probability Tables based on beta-likelihood
Feature Deviation Embedding Improves Graph Structure Learning for Spatial Interpolation
SMART: Semi-Supervised Music Emotion Recognition with Social Tagging
Efficient search of the best warping window for Dynamic Time Warping
Cost-Sensitive Learning: Preface
Discovering Hidden Topical Hubs and Authorities in Online Social Networks
An Information-Theoretic Approach to Finding Informative Noisy Tiles in Binary Databases
On Maximum Coverage in the Streaming Model & Application to Multi-topic Blog-Watch
ABACUS: Mining Arbitrary Shaped Clusters from Large Datasets based on Backbone Identification
A Practitioners' Guide to Transfer Learning for Text Classification using Convolutional Neural Networks
COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification
On Randomly Projected Hierarchical Clustering with Guarantees
Lattice based Clustering of Temporal Gene-Expression Matrices
Context-Preserving Hashing for Fast Text Classification
The Relevant-set Correlation Model for Data Clustering
MultiC 2 : an Optimization Framework for Learning from Task and Worker Dual Heterogeneity
Temporally Coherent CRP: A Bayesian Non-Parametric Approach for Clustering Tracklets with applications to Person Discovery in Videos
A Framework to Adjust Dependency Measure Estimates for Chance
Making Time-Series Classification More Accurate Using Learned Constraints
Multimodal Graph Learning for Cross-Modal Retrieval
Active Learning to Rank using Pairwise Supervision
Graph Generation with Prescribed Feature Constraints
Neural Graph Matching for Pre-training Graph Neural Networks
Heterogeneous Graph Contrastive Multi-view Learning
Incremental Multi-view Support Vector Machine
Mining Sequence Classifiers for Early Prediction
HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
Mining Massive Archives of Mice Sounds with Symbolized Representations
Legislative Prediction with Dual Uncertainty Minimization from Heterogeneous Information
PatentCom: A Comparative View of Patent Document Retrieval
Instance Selection Techniques for Memory-based Collaborative Filtering
An incremental data-stream sketch using sparse random projections
Mining Control Flow Abnormality for Logic Error Isolation
Adapting K-Medians to Generate Normalized Cluster Centers
Two-View Transductive Support Vector Machines
Training Support Vector Machines Using Adaptive Clustering
AMAS: Attention Model for Attributed Sequence Classification
Back Matter
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning
Evaluation of Unsupervised Learning Results: Making the Seemingly Impossible Possible
Consecutive Ones Property and Spectral Ordering
Semi-Supervised Convolution Graph Kernels for Relation Extraction
ApproxMAP: Approximate Mining of Consensus Sequential Patterns
Co-Preserving Patterns in Bipartite Partitioning for Topic Identification
Non-parametric Information-Theoretic Measures of One-Dimensional Distribution Functions from Continuous Time Series
The Infinite Push: A New Support Vector Ranking Algorithm that Directly Optimizes Accuracy at the Absolute Top of the List
Localizing Temporal Anomalies in Large Evolving Graphs
Privacy Preservation in Social Networks with Sensitive Edge Weights
ATLaS: A Native Extension of SQL for Data Mining
Distance Preserving Dimension Reduction for Manifold Learning
Relational Regularization and Feature Ranking
Utility-Oriented String Mining
Tesselation and Clustering by Mixture Models and Their Parallel Implementations
On Robust Wasserstein Barycenter: The Model and Algorithm
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
A Spatial-Temporal Probabilistic Matrix Factorization Model for Point-of-Interest Recommendation
Mixed-Transfer: Transfer Learning over Mixed Graphs
Determining the Number of Clusters via Iterative Consensus Clustering
Decision List Optimization based on Continuous Relaxation
Resource-Aware Mining with Variable Granularities in Data Streams
Lazy Learning for Classification Based on Query Projections
Directed Network Community Detection: A Popularity and Productivity Link Model
Stacked Mixed-Order Graph Convolutional Networks for Collaborative Filtering
Sparse Representation for HIV-1 Protease Drug Resistance Prediction
Transformation Based Ensembles for Time Series Classification
Extrinsic-Intrinsic Representation Learning Framework for Drug Discovery
Mining Frequent Agreement Subtrees in Phylogenetic Databases
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
Localized Graph Collaborative Filtering
A Probabilistic Approach to Uncovering Attributed Graph Anomalies
Fairness-aware Multi-view Clustering
An LSTM Approach to Patent Classification based on Fixed Hierarchy Vectors
Dynamic Community Detection in Weighted Graph Streams
Graph Mining with Variational Dirichlet Process Mixture Models
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets
TMSA: A Mutual Learning Model for Topic Discovery and Word Embedding
Summarizing Sequential Data with Closed Partial Orders
Proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013. Austin, Texas, USA
SMACD: Semi-supervised Multi-Aspect Community Detection
Discovering Multiple Co-Clusterings in Subspaces
Influence Maximization with Viral Product Design
UFNRec: Utilizing False Negative Samples for Sequential Recommendation
Risk Prediction with Electronic Health Records: A Deep Learning Approach
Feature Selection over Distributed Data Streams through Convex Optimization
Parallel Computation of RBF Kernels for Support Vector Classifiers
Mining frequent closed itemsets out-of-core
Measuring disentangled generative spatio-temporal representation
Defense Against Shortest Path Attacks
1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019)
Knowledge-enhanced Spherical Representation Learning for Text Classification
Basic Association Rules
ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection in Robot Behaviors
Training Sparse Graph Neural Networks via Pruning and Sprouting
A Data Parallel Approach for Large-Scale Gaussian Process Modeling
Transfer Significant Subgraphs across Graph Databases
Unsupervised Selection of Robust Audio Feature Subsets
Convolutional Methods for Predictive Modeling of Geospatial Data
An Iterative and Re-weighting Framework for Rejection and Uncertainty Resolution in Crowdsourcing
Building associations between markers of environmental stressors and adverse human health impacts using frequent itemset mining
CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning
End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection
A Bayesian Framework for Modeling Human Evaluations
Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach
Uncorrelated Patient Similarity Learning
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs
Characterizing Uncertain Data using Compression
On the Techniques for Data Clustering with Numerical Constraints
Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms
A Data-Dependent Algorithm for Querying Earth Mover's Distance with Low Doubling Dimensions
Heterogeneous Dual-Task Clustering with Visual-Textual Information
Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data
Self-Similar Graph Neural Network for Hierarchical Graph Learning
Semi-supervised Multi-label Learning by Solving a Sylvester Equation
EEG-based Motion Intention Recognition via Multi-task RNNs
An ADMM Algorithm for Clustering Partially Observed Networks
Multi-Armed Bandit Based Feature Selection
Personalized TV Recommendation with Mixture Probabilistic Matrix Factorization
PhraseScope: An Effective and Unsupervised Framework for Mining High Quality Phrases
Query-Aware Bayesian Committee Machine for Scalable Gaussian Process Regression
A Permutation Approach to Validation
Selecting a Representative Set of Diverse Quality Reviews Automatically
Conquest: A Distributed Tool for Constructing Summaries of High-Dimensional Discrete Attribute Data Sets
Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization
YOLO-OCR: End-to-end Compound Figure Separation and Label Recognition of Images in Scientific Publications
Sparse Fisher Discriminant Analysis for Computer Aided Detection
Detecting Media Self-Censorship without Explicit Training Data
Exploiting Emotional Information for Trust/Distrust Prediction
Exploiting Structured Reference Data for Unsupervised Text Segmentation with Conditional Random Fields
On the Use of Combining Rules in Relational Probability Trees
Transition Matrix Representation of Trees with Transposed Convolutions
Hierarchical Document Clustering using Frequent Itemsets
Unified and Contrasting Graphical Lasso for Brain Network Discovery
Attention-Based Multi-modal Missing Value Imputation for Time Series Data with High Missing Rate
A Novel Framework for Incorporating Labeled Examples into Anomaly Detection
Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering
A System for Keyword Search on Textual Streams
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability
Multivariate Confidence Intervals
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data
CISum: Learning Cross-modality Interaction to Enhance Multimodal Semantic Coverage for Multimodal Summarization
Correcting Sampling Bias in Structural Genomics through Iterative Selection of Underrepresented Targets
Graph-Based Marginal Ranking for Update Summarization
Who will Attend This Event Together? Event Attendance Prediction via Deep LSTM Networks
Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification
Towards Breaking the Curse of Dimensionality for High-Dimensional Privacy
Discovering Relational Items Sets Efficiently
Scalable Clustering of Time Series with U-Shapelets
On Improving Fairness of AI Models with Synthetic Minority Oversampling Techniques
Fast Lossless Frequent Itemset Mining in Data Streams using Crucial Patterns
Near-Optimal and Practical Algorithms for Graph Scan Statistics
A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget
Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments
Exploiting Synchronicity Networks for Finding Valuables in Heterogeneous Networks
Exploiting Geometry for Support Vector Machine Indexing
Modeling User Arguments, Interactions, and Attributes for Stance Prediction in Online Debate Forums
Distribution Regularized Regression Framework for Climate Modeling
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach
Scan Detection: A Data Mining Approach
Proximity Tracking on Time-Evolving Bipartite Graphs
Aligned Graph Classification with Regularized Logistic Regression
Optimal event sequence sanitization
Efficient and Effective Graph Convolution Networks
Text Mining from Site Invariant and Dependent Features for Information Extraction Knowledge Adaptation
Confidence Estimation Methods for Partially Supervised Information Extraction
Mining and Ranking Generators of Sequential Patterns
Semi-Supervised Isolation Forest for Anomaly Detection
A Spamicity Approach to Web Spam Detection
GIST: Graph Inference for Structured Time Series
Robust Clustering in Arbitrarily Oriented Subspaces
Inter-Series Attention Model for COVID-19 Forecasting
Discriminative Feature Selection for Uncertain Graph Classification
Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread
Proceedings of the 2025 SIAM International Conference on Data Mining, SDM 2025, Alexandria, VA, USA, May 1-3, 2025
A Fourier Analysis Based Approach to Learning Decision Trees in a Distributed Environment
Learning Causal Structure on Mixed Data with Tree-Structured Functional Models
A Generalized Tree Matching Algorithm Considering Nested Lists for Web Data Extraction
Query-Driven Maximum Quasi-Clique Search
A graphical model approach to ATLAS-free mining of MRI images
Only Attending What Matter within Trajectories - Memory-Efficient Trajectory Attention
Penalized Non-Linear Canonical Correlation Analysis for Ordinal Data with Application to the International Classification of Functioning, Disability and Health
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection
Exact and Heuristic Approaches to Speeding Up the MSM Time Series Distance Computation
Extracting Interpretable Features for Early Classification on Time Series
Augmented Multi-Task Learning by Optimal Transport
Mining Block I/O Traces for Cache Preloading with Sparse Temporal Non-parametric Mixture of Multivariate Poisson
Online Prediction of User Actions through an Ensemble Vote from Vector Representation and Frequency Analysis Models
Mining Interpretable and Predictive Diagnosis Codes from Multi-source Electronic Health Records
Building Decision Trees on Records Linked through Key References
Proceedings of the Second SIAM International Conference on Data Mining, Arlington, VA, USA, April 11-13, 2002
A Complexity-Invariant Distance Measure for Time Series
Physics-guided Graph Diffusion Network for Combining Heterogeneous Simulated Data: An Application in Predicting Stream Water Temperature
3D Molecular Geometry Analysis with 2D Graphs
Time Series Classification under More Realistic Assumptions
Adaptive Principal Component Analysis
Mining Frequent Graph Sequence Patterns Induced by Vertices
Making a Computational Attorney
Mixtures of Block Models for Brain Networks
HADT: Human-AI Diagnostic Team via Hierarchical Reinforcement Learning
Nonlinear Manifold Learning for Data Stream
Data-Mining of a Large Virtual Community: Relationship between Users DB and the Web-Log File
Topic Evolution in a Stream of Documents
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation
Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data
Instance Space Analysis for Unsupervised Outlier Detection
AnchorDrug: A system for drug-induced gene expression prediction in new contexts through active learning
Vietoris-Rips Complex: A New Direction for Cross-Domain Cold-Start Recommendation
Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media
Meta-learning of Class Knowledge in Zero-shot Learning
Constructing Time Decompositions for Analyzing Time-Stamped Documents
Selecting Social Media Responses to News: A Convex Framework Based On Data Reconstruction
Clustering Based on Yukawa Potential
Exploring and Inferring User-User Pseudo-Friendship for Sentiment Analysis with Heterogeneous Networks
Anytime Query-Tuned Kernel Machines via Cholesky Factorization
Temporal Kernel Descriptors for Learning with Time-sensitive Patterns
Towards Permission Request Prediction on Mobile Apps via Structure Feature Learning
User-guided Cross-domain Sentiment Classification
A Weighted Adaptive Mean Shift Clustering Algorithm
On Mining Statistically Significant Attribute Association Information
Markov Models for Identification of Significant Episodes
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
Generalized Optimization Framework for Graph-based Semi-supervised Learning
Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series
Discriminant Analysis for Unsupervised Feature Selection
A Fast Algorithm for Combinatorial Hotspot Mining Based on Spatial Scan Statistic
Identifying When Effect Restoration Will Improve Estimates of Causal Effect
Fast Implementation of ℓ 1 Regularized Learning Algorithms Using Gradient Descent Methods
Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks
Summarizing Review Scores of "Unequal" Reviewers
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation
Speeding Up All-Pairwise Dynamic Time Warping Matrix Calculation
A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Deep Kernel Learning for Clustering
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification
An Empirical Study of the Suitability of Class Decomposition for Linear Models: When Does It Work Well?
Approximate Query Answering by Model Averaging
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach
Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice
Bayesian Modeling of Intersectional Fairness: The Variance of Bias
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution
How Can I Index My Thousands of Photos Effectively and Automatically? An Unsupervised Feature Selection Approach
FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery
A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series
Online Max-Margin Weight Learning for Markov Logic Networks
Expanding the Training Data Space Using Emerging Patterns and Genetic Methods
DualCast: Friendship-Preference Co-evolution Forecasting for Attributed Networks
Session-based Recommendation with Hypergraph Attention Networks
On Abnormality Detection in Spuriously Populated Data Streams
A New Constraint for Mining Sets in Sequences
On Modeling Community Behaviors and Sentiments in Microblogging
Adapting Distilled Knowledge for Few-shot Relation Reasoning over Knowledge Graphs
A Physics-guided NN-based Approach for Tropical Cyclone Intensity Estimation
Learning Simple Relations: Theory and Applications
Using Compression to Identify Classes of Inauthentic Texts
HBGG: a Hierarchical Bayesian Geographical Model for Group Recommendation
A Constrained Hidden Markov Model Approach for Non-Explicit Citation Context Extraction
Field-Theoretic Methods for Intractable Probabilistic Models
Higher Order Orthogonal Iteration of Tensors (HOOI) and its Relation to PCA and GLRAM
CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Information Theoretic Feature Crediting in Multiclass Support Vector Machines
Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering
Online IT Ticket Automation Recommendation Using Hierarchical Multi-armed Bandit Algorithms
Signature-Based Anomaly Detection in Networks
Lagrangian Constrained Clustering
Climate Multi-model Regression Using Spatial Smoothing
ALPINE: Progressive Itemset Mining with Definite Guarantees
Physics-Guided Meta-Learning Method in Baseflow Prediction over Large Regions
MC-MinH: Metagenome Clustering using Minwise based Hashing
Positive Unlabeled Learning with a Sequential Selection Bias
Extending Consensus Clustering to Explore Multiple Clustering Views
Multiplex Memory Network for Collaborative Filtering
Generalized and Heuristic-Free Feature Construction for Improved Accuracy