yusuke1997/dblp-id-title huggingface dataset:
Graph sketching-based Space-efficient Data Clustering
Evaluating the Performance of Association Mining Methods in 3-D Medical Image Databases
AlignGraph: A Group of Generative Models for Graphs
Learning Stroke Treatment Progression Models for an MDP Clinical Decision Support System
Structural Analysis in Multi-Relational Social Networks
Ensemble Learning Methods for Binary Classification with Multi-modality within the Classes
A Latent Dirichlet Model for Unsupervised Entity Resolution
Mining and Validating Localized Frequent Itemsets with Dynamic Tolerance
Exploration and Reduction of the Feature Space by Hierarchical Clustering
Stable Synthetic Control with Anomaly Detection for Causal Inference
Node Classification in Signed Social Networks
Estimating Latent Population Flows from Aggregated Data via Inversing Multi-Marginal Optimal Transport
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
Iterative Framework Radiation Hybrid Mapping
Semantic Graph Kernels for Automated Reasoning
On Node Classification in Dynamic Content-based Networks
SUMSRM: A New Statistic for the Structural Break Detection in Time Series
Toward Optimal Ordering of Prediction Tasks
Blue Sky: Multilingual, Multimodal Domain Independent Deception Detection
Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents
On Periodicity Detection and Structural Periodic Similarity
One-Class Recommendation with Asymmetric Textual Feedback
Uncovering Group Level Insights with Accordant Clustering
Model-based von Mises-Fisher Co-clustering with a Conscience
Towards Entity-Aware Conditional Variational Inference for Heterogeneous Time-Series Prediction: An application to Hydrology
Time-Series Classification in Many Intrinsic Dimensions
Discovering Fully Dependent Patterns
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation
You Are How You Move: Linking Multiple User Identities From Massive Mobility Traces
Bus Travel Speed Prediction using Attention Network of Heterogeneous Correlation Features
Iterative Mining for Rules with Constrained Antecedents
Data Integration via Constrained Clustering: An Application to Enzyme Clustering
GeoAttn: Localization of Social Media Messages via Attentional Memory Network
Sequential Minimal Optimization in Adaptive-Bandwidth Convex Clustering
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Mining Visual and Textual Data for Constructing a Multi-Modal Thesaurus
Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions
The Power of Second-Order Decision Tables
A Quadratic Mean based Supervised Learning Model for Managing Data Skewness
SPADE: Streaming PARAFAC2 DEcomposition for Large Datasets
Application of Bayesian Partition Models in Warranty Data Analysis
Indexing and classifying gigabytes of time series under time warping
Robust Subspace Discovery through Supervised Low-Rank Constraints
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning
The Benefits of Personalized Smartphone-Based Activity Recognition Models
Contextual Time Series Change Detection
Cheetah : Fast Graph Kernel Tracking on Dynamic Graphs
Mining for Outliers in Sequential Databases
On Anonymization of Multi-graphs
Cost of Collaboration vs Individual Effort in Social Networks
Features or Shape? Tackling the False Dichotomy of Time Series Classification
CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance
The Generalized Dimensionality Reduction Problem
Proceedings of the SIAM International Conference on Data Mining, SDM 2009, April 30 - May 2, 2009, Sparks, Nevada, USA
Detecting the Change of Clustering Structure in Categorical Data Streams
Well-calibrated and specialized probability estimation trees
An Instance-Specific Algorithm for Learning the Structure of Causal Bayesian Networks Containing Latent Variables
Detecting Periodicity in Nonideal Datasets
Online Matrix Completion Through Nuclear Norm Regularisation
Tracking User Mobility to Detect Suspicious Behavior
Mining Complex Spatio-Temporal Sequence Patterns
Bridging Numbers and Narratives: Enhancing Financial Market Risk Predictions through Numerical Information from Financial Documents
Non-Negative Residual Matrix Factorization with Application to Graph Anomaly Detection
On the performance of bisecting K-means and PDDP
Structural Orthogonal Procrustes Regression for Face Recognition with Pose Variations and Misalignment
MUSK: Uniform Sampling of k Maximal Patterns
Mining Top-K Patterns from Binary Datasets in Presence of Noise
Self-Taught Spectral Clustering via Constraint Augmentation
Mining Approximate Frequent Itemsets In the Presence of Noise: Algorithm and Analysis
Node ranking in labeled networks
HIDRA: Head Initialization across Dynamic targets for Robust Architectures
Shared State for Client-Server Mining
An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction
Collaborative Information Extraction and Mining from Multiple Web Documents
Discovering Frequent Tree Patterns over Data Streams
Cube Lattices: A Framework for Multidimensional Data Mining
Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate
Multiple Kernel Clustering
Community Detection with Prior Knowledge
Nearest-Neighbor Search on a Time Budget via Max-Margin Trees
Mining Complex, Maximal and Complete Sub-graph and Sets of Correlated Variables with Applications to Feature Subset Selection
CREDOS: Classification Using Ripple Down Structure (A Case for Rare Classes)
IntruMine: Mining Intruders in Untrustworthy Data of Cyber-physical Systems
Feature Selection by Joint Graph Sparse Coding
On the Information Unfairness of Social Networks
Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining
Ranking with Confidence for Large Scale Comparison Data
Learning Diverse Gaussian Graphical Models and Interpreting Edges
Semi-Supervised Classification with Universum
Geometric methods to accelerate k -means algorithms
On Clustering Graph Streams
Cluster Description Formats, Problems and Algorithms
Active Learning with Model Selection in Linear Regression
An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data
Clustering by weighted cuts in directed graphs
SMF: Drift-Aware Matrix Factorization with Seasonal Patterns
Statistically-sound Knowledge Discovery from Data
ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations
A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction
An Analysis of Logistic Models: Exponential Family Connections and Online Performance
Dual Transfer Learning
SONAR: Signal De-mixing for Robust Correlation Clustering
Consumer Segmentation and Knowledge Extraction from Smart Meter and Survey Data
Emergence of Cooperation in Multi-Agent Reinforcement Learning via Coalition Labeling and Structural Entropy
Outlier Detection with Uncertain Data
Discovery of Causal Time Intervals
Twin Vector Machines for Online Learning on a Budget
Non-Euclidean Spatial Graph Neural Network
Taming the Empirical Hubness Risk in Many Dimensions
Reinforcement Learning Guided Multi-Objective Exam Paper Generation
Scalable Batch Acquisition for Deep Bayesian Active Learning
REAFUM: Representative Approximate Frequent Subgraph Mining
Cumulative Knowledge-based Regression Models for Next-term Grade Prediction
Data-centric AI: Perspectives and Challenges
Optimizing Hashing Functions for Similarity Indexing in Arbitrary Metric and Nonmetric Spaces
Fast Mining of Distance-Based Outliers in High Dimensional Datasets
UPFL: Unsupervised Personalized Federated Learning towards New Clients
ODAC: Hierarchical Clustering of Time Series Data Streams
Exploiting Associations between Word Clusters and Document Classes for Cross-Domain Text Categorization
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies
Active Learning of Functional Networks from Spike Trains
Computing Statistical Profiles of Active Sites in Proteins
Preemptive Measures against Malicious Party in Privacy-Preserving Data Mining
Contextual Combinatorial Bandit and its Application on Diversified Online Recommendation
Global-and-Local Aware Data Generation for the Class Imbalance Problem
Alleviating the Sparsity Problem in Collaborative Filtering by Using an Adapted Distance and a Graph-Based Method
Context-Driven Data Mining Through Bias Removal and Incompleteness Mitigation
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
Learning Convolutional Text Representations for Visual Question Answering
Graph-based semi-supervised learning for relational networks
WCAMiner: A Novel Knowledge Discovery System for Mining Concept Associations using Wikipedia
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction
Efficient Substructure Discovery from Large Semi-structured Data
Hierarchical Neural Topic Model with Embedding Cluster and Neural Variational Inference
Finding similar situations in sequences of events via random projections
Scalable Name Disambiguation using Multi-level Graph Partition
Mining for Surprise Events Within Text Streams
Future Influence Ranking of Scientific Literature
DIAS: A Disassemble-Assemble Framework for Highly Sparse Text Clustering
Feature-based Inductive Transfer Learning through Minimum Encoding
GRIA: Graphical Regularization for Integrative Analysis
Adversarial Hard Negative Generation for Complementary Graph Contrastive Learning
Missing or Inapplicable: Treatment of Incomplete Continuous-valued Features in Supervised Learning
Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS)
SpaRClus: Spatial Relationship Pattern-Based Hierarchial Clustering
A Sparse Nonlinear Classifier Design Using AUC Optimization
Proceedings of the Sixth SIAM International Conference on Data Mining, April 20-22, 2006, Bethesda, MD, USA
A New Framework for Traffic Anomaly Detection
Evolving Separating References for Time Series Classification
ROCsearch - An ROC-guided Search Strategy for Subgroup Discovery
Unstable Communities in Network Ensembles
Contradictory Structure Learning for Semi-supervised Domain Adaptation
Exploiting Hierarchical Structures for Unsupervised Feature Selection
Ensemble-based Adaptive Intrusion Detection
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles
Local L2-Thresholding Based Data Mining in Peer-to-Peer Systems
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification
SOR: Scalable Orthogonal Regression for Low-Redundancy Feature Selection and its Healthcare Applications
Transfer Topic Modeling with Ease and Scalability
Optimal Distance Estimation Between Compressed Data Series
Multi-Task Feature Selection on Multiple Networks via Maximum Flows
Dynamic Classification of Online Customers
Denoising Long- and Short-term Interests for Sequential Recommendation
EBV: Electronic Bee-Veterinarian for Principled Mining and Forecasting of Honeybee Time Series
CISpan: Comprehensive Incremental Mining Algorithms of Closed Sequential Patterns for Multi-Versional Software Mining
Hypergraph Contrastive Learning for Electronic Health Records
Avoidance Region Discovery: A Summary of Results
Learning Hierarchical Relationships among Partially Ordered Objects with Heterogeneous Attributes and Links
Noisy Truncated SGD: Optimization and Generalization
Exploring the Unknown - Query Synthesis in One-Class Active Learning
On Influential Nodes Tracking in Dynamic Social Networks
Fair Classification Under Strict Unawareness
Semi-supervised Learning of a Markovian Metric
Discovering bursts revisited: guaranteed optimization of the model parameters
Surveying Data for Patchy Structure
Weighted Clustering Ensembles
On Error Correlation and Accuracy of Nearest Neighbor Ensemble Classifiers
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction
Sketching Landscapes of Page Farms
Harvester: Principled Factorization-based Temporal Tensor Granularity Estimation
Branch and Border: Partition-Based Change Detection in Multivariate Time Series
Embedding Transfer with Enhanced Correlation Modeling for Cross-Domain Recommendation
Sparse Hybrid Variational-Gibbs Algorithm for Latent Dirichlet Allocation
Derivative Dynamic Time Warping
Semantics-Aware Hidden Markov Model for Human Mobility
Accelerated Attributed Network Embedding
Concept Discovery for Fast Adaptation
Multiperiod Corporate Default Prediction Through Neural Parametric Family Learning
Deep Self-representative Concept Factorization Network for Representation Learning
Proceedings of the SIAM International Conference on Data Mining, SDM 2008, April 24-26, 2008, Atlanta, Georgia, USA
Graph Summarization for Preserving Spectral Characteristics
Detection of Underrepresented Biological Sequences using Class-Conditional Distribution Models
Clustering in the Face of Fast Changing Streams
Flexible Anonymization For Privacy Preserving Data Publishing: A Systematic Search Based Approach
Efficient Algorithms for a Robust Modularity-Driven Clustering of Attributed Graphs
A Hybrid Data Mining Metaheuristic for the p-Median Problem
Conical Dimension as an Intrinsic Dimension Estimator and its Applications
A Fast Kernel for Attributed Graphs
Leveraging Subsequence-orders for Univariate and Multivariate Time-series Classification
Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach
Discriminative Density-ratio Estimation
Radius Plots for Mining Tera-byte Scale Graphs: Algorithms, Patterns, and Observations
Naive Bayes Classifier for Positive Unlabeled Learning with Uncertainty
Meta Adversarial Weight for Unsupervised Domain Adaptation
Modeling Asymmetry and Tail Dependence among Multiple Variables by Using Partial Regular Vine
Characterising Seismic Data
DAVA: Distributing Vaccines over Networks under Prior Information
Batch Mode Active Learning with Hierarchical-Structured Embedded Variance
Predicting Preference Tags to Improve Item Recommendation
Stacked Graphical Models for Efficient Inference in Markov Random Fields
Text Mining Using Non-Negative Matrix Factorizations
Multi-core K-means
Embedded Supervised Feature Selection for Multi-class Data
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning
The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
Transfer Learning of Distance Metrics by Cross-Domain Metric Sampling across Heterogeneous Spaces
What We Talk About When We Talk About AI for Science
Measuring Discrimination in Socially-Sensitive Decision Records
Label Distribution Learning-Enhanced Dual-KNN for Text Classification
Clustered low rank approximation of graphs in information science applications
A Framework for Local Supervised Dimensionality Reduction of High Dimensional Data
Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids
Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding
Unanticipated Replenishment: Online Policy for Dynamic Service Composition in Manufacturing Cloud
On Graph Stream Clustering with Side Information
Mining Patters of Activity from Video Data
YACC: A Framework Generalizing TuránShadow for Counting Large Cliques
Granger Causality Analysis in Irregular Time Series
A Dimensionality-Driven Approach for Unsupervised Out-of-distribution Detection
Beating Human Analysts in Nowcasting Corporate Earnings by using Publicly Available Stock Price and Correlation Features
Large-scale Kernel RankSVM
Straightforward Feature Selection for Scalable Latent Semantic Indexing
Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis
Proceedings of the 2017 SIAM International Conference on Data Mining, Houston, Texas, USA, April 27-29, 2017
Conformal Edge-Weight Prediction in Latent Space
Efficient Partial Order Preserving Unsupervised Feature Selection on Networks
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop
A Two-View EEG Representation for Brain Cognition by Composite Temporal-Spatial Contrastive Learning
ActNeT: Active Learning for Networked Texts in Microblogging
Fast Random Walk Graph Kernel
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Cone Cluster Labeling for Support Vector Clustering
ShatterPlots: Fast Tools for Mining Large Graphs
XDC: Adaptive Cross Domain Short Text Clustering
StepDIRECT - A Derivative-Free Optimization Method for Stepwise Functions
A Structure Function for Transaction Data
Autocannibalistic and Anyspace Indexing Algorithms with Application to Sensor Data Mining
Coupled Clustering of Time-Series and Networks
BDA: Bandit-based Transferable AutoAugment
Semantic Discord: Finding Unusual Local Patterns for Time Series
On the Dangers of Cross-Validation. An Experimental Evaluation
Multi-Transfer: Transfer Learning with Multiple Views and Multiple Sources
Dimensionality-Aware Outlier Detection
Laplacian Score Benefit Adaptive Filter Selection for Graph Neural Networks
Active Learning with Monotonicity Constraints
A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification
Optimal Bidding Strategy without Exploration in Real-time Bidding
Discriminative Prototype Set Learning for Nearest Neighbor Classification
Efficient Clustering of Metagenomic Sequences using Locality Sensitive Hashing
AMORI: A Metric-Based One Rule Inducer
STES: A Spatiotemporal Explanation Supervision Framework
Improving Credit Card Fraud Detection with Calibrated Probabilities
An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification
Approximating splits for decision trees quickly in sparse data streams
Less is More: Similarity of Time Series under Linear Transformations
Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network
MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation
Modelling Recurrent Events for Improving Online Change Detection
Two-Sample Testing for Event Impacts in Time Series
Finding Sequential Patterns from a Massive Number of Spatio-Temporal Events
Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model
Clustering with Model-level Constraints
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction
Collaborative Filtering with Noisy Ratings
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
Active Learning for Graphs with Noisy Structures
Mining Easily Understandable Models from Complex Event Logs
Deep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy
Mining Maximally Banded Matrices in Binary Data
The Power of Certainty: A Dirichlet-Multinomial Model for Belief Propagation
Saliency-Augmented Memory Completion for Continual Learning
RSVM: Reduced Support Vector Machines
Reading Customer Reviews to Answer Product-related Questions
Data-Enhanced Predictive Modeling for Sales Targeting
A Random Walks Method for Text Classification
Residual Bayesian Co-clustering for Matrix Approximation
CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference
STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies
Classifier Performance Estimation with Unbalanced, Partially Labeled Data
Reconstructing a cascade from temporal observations
Finding Motifs in a Database of Shapes
Dissimilarity Measures for Detecting Hepatotoxicity in Clinical Trial Data
Deep Skip-Gram Networks for Text Classification
A Framework for Discovering Co-Location Patterns in Data Sets with Extended Spatial Objects
Believe It Today or Tomorrow? Detecting Untrustworthy Information from Dynamic Multi-Source Data
Framework for Inferring Leadership Dynamics of Complex Movement from Time Series
STAMP: On Discovery of Statistically Important Pattern Repeats in Long Sequential Data
Same bang, fewer bucks: efficient discovery of the cost-influence skyline
Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach
Adversarially Reprogramming Pretrained Neural Networks for Data-limited and Cost-efficient Malware Detection
Constrained Group Testing to Predict Binding Response of Candidate Compounds
Agglomerative Mean-Shift Clustering via Query Set Compression
DANR: Discrepancy-aware Network Regularization
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection
Multi-Task Clustering using Constrained Symmetric Non-Negative Matrix Factorization
MKBoost: A Framework of Multiple Kernel Boosting
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains
Mining Tree Patterns with Almost Smallest Supertrees
On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation
MET: A Fast Algorithm for Minimizing Propagation in Large Graphs with Small Eigen-Gaps
Segmentation and dimensionality reduction
Yet Meta Learning Can Adapt Fast, it Can Also Break Easily
Transform Regression and the Kolmogorov Superposition Theorem
Retweeting: An Act of Viral Users, Susceptible Users, or Viral Topics?
Early Multiple Temporal Patterns Based Event Prediction in Heterogeneous Multivariate Temporal Data
Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases
Robust Dual Recurrent Neural Networks for Financial Time Series Prediction
Auto-play: A Data Mining Approach to ODI Cricket Simulation and Prediction
To Sample or To Smash? Estimating reachability in large time-varying graphs
Finding Frequent Patterns in a Large Sparse Graph
Uncovering Latent Behaviors in Ant Colonies
Hybrid Attribute Reduction for Classification Based on A Fuzzy Rough Set Technique
Adaptive Filtering for Efficient Record Linkage
Dynamic Shaker Detection from Evolving Entities
Effective Crowd Expertise Modeling via Cross Domain Sparsity and Uncertainty Reduction
Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network
Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition
An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks
MISS: Multiclass Interpretable Scoring Systems
Significant Subgraph Mining with Multiple Testing Correction
Feature Selection for High-dimensional Integrated Data
Data Silences: How to Unsilence the Uncertainties in Data Science
Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining
VolTime: Unsupervised Anomaly Detection on Users' Online Activity Volume
Inference of Node Replacement Recursive Graph Grammars
FedMe: Federated Learning via Model Exchange
When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events
Tracking Spatio-Temporal Diffusion in Climate Data
Deep Multimodality Model for Multi-task Multi-view Learning
Semi-supervised Variable Weighting for Clustering
A Generative Model with Network Regularization for Semi-Supervised Collective Classification
Large-Scale Multi-Label Learning with Incomplete Label Assignments
PICS: Parameter-free Identification of Cohesive Subgroups in Large Attributed Graphs
Exemplar-based Robust Coherent Biclustering
Sparse Graphical Modeling via Stochastic Complexity
Predicting Neighbor Distribution in Heterogeneous Information Networks
On Evaluation of Outlier Rankings and Outlier Scores
Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management
Parallel Large Scale Feature Selection for Logistic Regression
Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data
On the number of iterations of the DBA algorithm
Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS
Heavy Nodes in a Small Neighborhood: Algorithms and Applications
Kernel Based Detection of Mislabeled Training Examples