yusuke1997/dblp-id-title huggingface dataset:
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks
Graphical Models for Identifying Fraud and Waste in Healthcare Claims
Mining Multi-Relational Gradual Patterns
SSSNET: Semi-Supervised Signed Network Clustering
Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion
On using Page Cooccurrences for Computing Clickstream Similarity
Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics
D 2 M: Dynamic Defense and Modeling of Adversarial Movement in Networks
Mining Relationships Between Interacting Episodes
Mining Cohesive Patterns from Graphs with Feature Vectors
Unsupervised Feature Selection for Multi-View Data in Social Media
A Nondeterministic Normalization based Scan Statistic (NN-scan) towards Robust Hotspot Detection: A Summary of Results
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly
Reconstruction-based Anomaly Detection with Completely Random Forest
Density of States Graph Kernels
GPU-Accelerated Constraint-Based Causal Structure Learning for Discrete Data
A Cutting Algorithm for the Minimum Sum-of-Squared Error Clustering
Which Distance Metric is Right: An Evolutionary K-Means View
A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation
Pruning Decision Trees via Max-Heap Projection
Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression
HICAP: Hierarchical Clustering with Pattern Preservation
Biclustering: An application of Dual Topic Models
Context-aware Search for Personal Information Management Systems
Semi-supervised Embedding in Attributed Networks with Outliers
Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets
Proximity-Based Anomaly Detection Using Sparse Structure Learning
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations
Scalable, Balanced Model-based Clustering
On2Vec: Embedding-based Relation Prediction for Ontology Population
Towards Accurate Histogram Publication under Differential Privacy
Subspace Clustering of High Dimensional Data
Online Sparse Passive Aggressive Learning with Kernels
The Metric Dilemma: Competence-Conscious Associative Classification
Multi-View Low-Rank Analysis for Outlier Detection
Robust Learning via Golden Symmetric Loss of (un)Trusted Labels
Selective Markov Models for Predicting Web-Page Accesses
ClosedPROWL: Efficient Mining of Closed Frequent Continuities by Projected Window List Technology
Deriving Private Information from Randomly Perturbed Ratings
The Discovery of Generalized Causal Models with Mixed Variables Using MML Criterion
Robust Factorization Machine: A Doubly Capped Norms Minimization
Inter-Well Active Magnetic Ranging with Temporal and Interaction Network
Mobile App Security Risk Assessment: A Crowdsourcing Ranking Approach from User Comments
On Skewed Multi-dimensional Distributions: the FusionRP Model, Algorithms, and Discoveries
Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization
Convex Principal Feature Selection
Labeling Educational Content with Academic Learning Standards
Benchmarking Nearest Neighbor Search: Influence of Local Intrinsic Dimensionality and Result Diversity in Real-World Datasets
On Indexing High Demensional Data with Uncertainty
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
Generation of Alternative Clusterings Using the CAMI Approach
Flow-Based Local Graph Clustering with Better Seed Set Inclusion
A Random Walks Perspective on Maximizing Satisfaction and Profit
Multi-Objective Multi-Label Classification
Methods for Large-Scale Mining of Networks of Human Genes
Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness
Beam Methods for the Profile Hidden Markov Model
Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks
Multimodal Network Alignment
BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals
A Hidden Markov Forest Model for Terrain-Aware Flood Inundation Mapping from Earth Imagery
Refining Pre-trained Language Models for Domain Adaptation with Entity-Aware Discriminative and Contrastive Learning
DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages
CausalCDR: Causal Embedding Learning for Cross-domain Recommendation
A Generalized Mixture Framework for Multi-label Classification
On Approximate Solutions to Support Vector Machines
Integrating Community and Role Detection in Information Networks
On the Detectability of Node Grouping in Networks
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study
On Anonymization of String Data
Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization
A SAT-based Framework for Efficient Constrained Clustering
Uncovering the Spatiotemporal Patterns of Collective Social Activity
Network Inference from Contrastive Groups Using Discriminative Structural Regularization
Toward Data-driven, Semi-automatic Inference of Phenomenological Physical Models: Application to Eastern Sahel Rainfall
Fast optimal bandwidth selection for kernel density estimation
Automated Knowledge Discovery from Simulators
Feature-Engineered Random Forests
DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion
Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning
Fast Multilevel Transduction on Graphs
Trend Relational Analysis and Grey-Fuzzy Clustering Method
A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees
GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model
Multi-interest Sequence Modeling for Recommendation with Causal Embedding
A Fast Algorithm for Sparse PCA and a New Sparsity Control Criteria
Dual-stage Flows-based Generative Modeling for Traceable Urban Planning
Interpretable Categorization of Heterogeneous Time Series Data
Quantifying trust dynamics in signed graphs, the S-Cores approach
Three Myths about Dynamic Time Warping Data Mining
Where Graph Topology Matters: The Robust Subgraph Problem
LDFeRR: A Fuel-efficient Route Recommendation Approach for Long-distance Driving Based on Historical Trajectories
R1STM: One-class Support Tensor Machine with Randomised Kernel
Maximum Margin Classifiers with Specified False Positive and False Negative Error Rates
Finding Affordable and Collaborative Teams from a Network of Experts
On Low-Rank Updates to the Singular Value and Tucker Decompositions
Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features
Relative distance comparisons with confidence judgements
Pattern Aided Classification
Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases
A Family of Tractable Graph Distances
An Abstract Weighting Framework for Clustering Algorithms
CHARM: An Efficient Algorithm for Closed Itemset Mining
A Novel Genetic Algorithm for Feature Selection in Hierarchical Feature Spaces
Efficient Nonnegative Matrix Factorization with Random Projections
PCA without eigenvalue calculations: a case study on face recognition
Are approximation algorithms for consensus clustering worthwhile?
An Entity Based Model for Coreference Resolution
Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets
UNIANO: robust and efficient anomaly consensus in time series sensitive to cross-correlated anomaly profiles
Better AI For Understanding Life on Earth: Predict First, Design Later
Computational Developments of ψ -learning
Deperturbation of Online Social Networks via Bayesian Label Transition
Feature Enhanced Zero-Shot Stance Detection via Contrastive Learning
Routine Mining Based Anomaly Detection in Mobile Phone Data
NetCodec: Community Detection from Individual Activities
AUC dominant unsupervised ensemble of binary classifiers
On Supervised Change Detection in Graph Streams
Leveraging Contextual Graphs for Stochastic Weight Completion in Sparse Road Networks
Hierarchical Active Transfer Learning
Differentially Private Significance Testing on Paired-Sample Data
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions
Sensitivity-aware Distance Measurement for Boosting Metric Learning
Flexible Image Captioning via Internal Understanding and External Reasoning
Frequentness-Transition Queries for Distinctive Pattern Mining from Time-Segmented Databases
Balancing Task Coverage and Expert Workload in Team Formation
Summarizing and Mining Skewed Data Streams
Efficient Multiplicative Updates for Support Vector Machines
A Unified View of Localized Kernel Learning
Subspace Clustering for Uncertain Data
GRM: A New Model for Clustering Linear Sequences
Who Should Label What? Instance Allocation in Multiple Expert Active Learning
Time Series Motifs Statistical Significance
Risk Clearance with Guaranteed Precision
Subnetwork Mining with Spatial and Temporal Smoothness
Clustering from Constraint Graphs
An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease
Euclidean Co-Embedding of Ordinal Data for Multi-Type Visualization
Binary Classifier Calibration Using a Bayesian Non-Parametric Approach
Exact Mean Computation in Dynamic Time Warping Spaces
Fast Rule Mining Over Multi-Dimensional Windows
DeepGLSTM: Deep Graph Convolutional Network and LSTM based approach for predicting drug-target binding affinity
Personalized Knowledge Discovery: Mining Novel Association Rules from Text
The Similarity Between Stochastic Kronecker and Chung-Lu Graph Models
Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), Calgary, Alberta, Canada, May 4th, 2019
Frameworks to Encode User Preferences for Inferring Topic-sensitive Information Networks
Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining
A General Probabilistic Framework for Mining Labeled Ordered Trees
An Algorithm for Well Structured Subspace Clusters
Acceleration in Low-Rank Tensor Completion
Structure and Dynamics of Research Collaboration in Computer Science
Combating Product Review Spam Campaigns via Multiple Heterogeneous Pairwise Features
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Modeling Users' Adoption Behaviors with Social Selection and Influence
Speeding Up Secure Computations via Embedded Caching
Multi-Task Learning based Survival Analysis for Predicting Alzheimer's Disease Progression with Multi-Source Block-wise Missing Data
Automatic Frankensteining: Creating Complex Ensembles Autonomously
Principled Neuro-Functional Connectivity Discovery
Statistical Density Prediction in Traffic Networks
Topic Models For Feature Selection in Document Clustering
A New Privacy-Preserving Distributed k-Clustering Algorithm
VisTabNet: Adapting Vision Transformers for Tabular Data
Bayesian K-Means as a "Maximization-Expectation" Algorithm
Influencers and the Giant Component: The Fundamental Hardness in Privacy Protection for Socially Contagious Attributes
Matrix Profile XXVIII: Discovering Multi-Dimensional Time Series Anomalies with K of N Anomaly Detection †
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification
Structured Regression on Multilayer Networks
Finding the True Frequent Itemsets
Discovering Frequent Substructures from Hierarchical Semi-structured Data
Universal Dependency Analysis
Multi-skill Collaborative Teams based on Densest Subgraphs
Cross-Modal Retrieval: A Pairwise Classification Approach
Data Mining Challenges and Opportunities to Achieve Net Zero Carbon Emissions: Focus on Electrified Vehicles
t-BNE: Tensor-based Brain Network Embedding
Markov Chain Monitoring
Using Low-Memory Representations to Cluster Very Large Data Sets
Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems
Blue Sky: Expert-in-the-Loop Representation Learning Framework for Audio Anti-Spoofing: Multimodal, Multilingual, Multi-speaker, Multi-attack (4M) Scenarios
Extracting Precursor Rules from Time SeriesA Classical Statistical Viewpoint
Analyses for Service Interaction Networks with Applications to Service Delivery
Point-of-Interest Recommendation in Location Based Social Networks with Topic and Location Awareness
Constraint Programming for Association Rules
Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets
Adaptive Precision Training (AdaPT): A dynamic quantized training approach for DNNs
Kronecker Factorization for Speeding up Kernel Machines
Data mining for real mining: A robust algorithm for prospectivity mapping with uncertainties
Large-Scale Many-Class Learning
Robust Road Map Inference through Network Alignment of Trajectories
Set Coverage Problems in a One-Pass Data Stream
Optimal Distance Bounds on Time-Series Data
Efficient Multiclass Boosting Classification with Active Learning
Publishing Skewed Sensitive Microdata
Near-Neighbor Search in Pattern Distance Spaces
Bayesian Supervised Multilabel Learning with Coupled Embedding and Classification
HG-Meta: Graph Meta-learning over Heterogeneous Graphs
Discovering Bucket Orders from Data
Adaptive Multi-task Sparse Learning with an Application to fMRI Study
Learning A Task-Specific Deep Architecture For Clustering
Improved Knowledge Distillation via Full Kernel Matrix Transfer
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Differentially Private Associative Co-clustering
The PageTrust Algorithm: How to rank web pages when negative links are allowed?
Efficient Online Relative Comparison Kernel Learning
Discovering Dynamic Dipoles in Climate Data
Modeling the Interaction Coupling of Multi-View Spatiotemporal Contexts for Destination Prediction
Adaptive Label Smoothing To Regularize Large-Scale Graph Training
Active Positive-Definite Matrix Completion
Multi-objective Multi-view Spectral Clustering via Pareto Optimization
Mining Actionable Subspace Clusters in Sequential Data
Shattering and Compressing Networks for Betweenness Centrality
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
Detecting Extreme Rank Anomalous Collections
Online Resource Allocation with Structured Diversification
Dynamic Graph Convolutional Networks Using the Tensor M-Product
Polynomial-Delay and Polynomial-Space Algorithms for Mining Closed Sequences, Graphs, and Pictures in Accessible Set Systems
Event Detection in Social Streams
Multi-Graph Learning with Positive and Unlabeled Bags
Cross Table Cubing: Mining Iceberg Cubes from Data Warehouses
Image Mining of Historical Manuscripts to Establish Provenance
Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data
Process Trace Clustering: A Heterogeneous Information Network Approach
Latitude: A Model for Mixed Linear-Tropical Matrix Factorization
Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models
Semi-Supervised Clustering via Structural Entropy with Different Constraints
Distributed Representations of Expertise
An Integrative Approach to Indentifying Biologically Relevant Genes
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
Modeling Co-Evolution Across Multiple Networks
TEM: High Utility Metric Differential Privacy on Text
Meta-Learning for Size and Fit Recommendation in Fashion
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
GraphShop: Graph-based Approach for Shop-type Recommendation
An Interpretable Measure for Quantifying Predictive Dependence between Continuous Random Variables
Towards Tuning-Free Minimum-Volume Nonnegative Matrix Factorization
EsaCL: An Efficient Continual Learning Algorithm
Sensitivity of Community Structure to Network Uncertainty
Context Aware Trace Clustering: Towards Improving Process Mining Results
Cross-Selling Optimization for Customized Promotion
iMet: Interactive Metric Learning in Healthcare Applications
ℓ 1, ∞ Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces
Deep Adversarial Canonical Correlation Analysis
Learning to Interact with Users: A Collaborative-Bandit Approach
A Linkage-based Doubly Imbalanced Graph Learning Framework for Face Clustering
Towards Trustworthy Representation Learning
Ensemble-Spotting: Ranking Urban Vibrancy via POI Embedding with Multi-view Spatial Graphs
GPU Accelerated Sub-Sampled Newton's Method for Convex Classification Problems
Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases
Towards Finding Valuable Topics
Semi-supervised Feature Selection via Spectral Analysis
LODES: Local Density Meets Spectral Outlier Detection
Doubly Robust Prediction and Evaluation Methods Improve Uplift Modeling for Observational Data
Knowledge Discovery from Heterogeneous Dynamic Systems using Change-Point Correlations
Multi-dimensional Graph Convolutional Networks
Approximating Representations for Large Numerical Databases
Temporal Graph Kernels for Classifying Dissemination Processes
Geospatial Topological Relation Extraction from Text with Knowledge Augmentation
Low-Entropy Set Selection
A Semi-Supervised Framework for Feature Mapping and Multiclass Classification
Text Categorization Using Word Similarities Based on Higher Order Co-occurrences
Polyadic Regression and its Application to Chemogenomics
Cascading Spatio-temporal Pattern Discovery: A Summary of Results
HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection
Learning Reliable Rules under Class Imbalance
A Salient Ensemble of Trees using Cascaded Linear Classifiers with Feature-Cost Constraints
iPath: Forecasting the Pathway to Impact
Spatially Cost-Sensitive Active Learning
Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020, Cincinnati, Ohio, USA, May 7-9, 2020
Scalable Graph Synthesis with Adj and 1 - Adj
Density Estimation with Adaptive Sparse Grids for Large Data Sets
Click versus Share: A Feature-driven Study of Micro-Video Popularity and Virality in Social Media
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
Hierarchical Document Classification Using Automatically Generated Hierarchy
Copula-HDP-HMM: Non-parametric Modeling of Temporal Multivariate Data for I/O Efficient Bulk Cache Preloading
Mining Preferences from Spatial-Temporal Data
ContexTour: Contextual Contour Analysis on Dynamic Multi-relational Clustering
Autoregressive Tree Models for Time-Series Analysis
Making Data Mining Models Useful to Model Non-paying Customers of Exchange Carriers
Deep Neural Networks with Knowledge Instillation
A Better Alternative to Piecewise Linear Time Series Segmentation
Exploiting Relationships for Domain-Independent Data Cleaning
Computationally Generated Cardiac Biomarkers: Heart Rate Patterns to Predict Death Following Coronary Attacks
Domain Knowledge Augmented Contrastive Learning on Dynamic Hypergraphs for Improved Health Risk Prediction
Regularization of Latent Variable Models to Obtain Sparsity
Unifying Human Mobility Forecasting and Trajectory Semantics Augmentation via Hawkes Process Based LSTM
Proceedings of the 2016 SIAM International Conference on Data Mining, Miami, Florida, USA, May 5-7, 2016
MultiVis: Content-Based Social Network Exploration through Multi-way Visual Analysis
Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments
Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error
Discriminating Subsequence Discovery for Sequence Clustering
FACETS: Adaptive Local Exploration of Large Graphs
RCMap: Efficiently Creating High-Quality Euclidean Embeddings
Efficient Sampling of Temporal Networks with Preserved Causality Structure
Nonlinear Joint Unsupervised Feature Selection
Domain-Knowledge Driven Cognitive Degradation Modeling for Alzheimer's Disease
Graphical Modeling of Macro Behavioral Targeting in Social Networks
Scaling log-linear analysis to datasets with thousands of variables
Fast Counting with AV-Space for Efficient Rule Induction
Fast Mining of a Network of Coevolving Time Series
Streaming Tensor Factorization for Infinite Data Sources
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
Citation Prediction in Heterogeneous Bibliographic Networks
Characterizing Transactional Databases for Frequent Itemset Mining
Heterogeneous Temporal Graph Neural Network
On Clustering Binary Data
An Examination of Practical Granger Causality Inference
A Framework for Scalable Cost-sensitive Learning Based on Combing Probabilities and Benefits
WFIM: Weighted Frequent Itemset Mining with a weight range and a minimum weight
A pattern mining approach toward discovering generalized sequence signatures
SAGA: Signal-Aware Graph Aggregation
An Interpretable Fast Model for Predicting The Risk of Heart Failure
StreamCast: Fast and Online Mining of Power Grid Time Sequences
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation
Modeling Evolutionary Behaviors for Community-based Dynamic Recommendation
Monitoring and mining GPS traces in transit space
A Generalized Framework for Mining Arbitrarily Positioned Overlapping Co-clusters
Generalized K -Harmonic Means - Dynamic Weighting of Data in Unsupervised Learning
Optimizing Transit Network Expansion with Gated Attentive Graph Reinforcement Learning
Time-aware Multi-interest Capsule Network for Sequential Recommendation
Toward Personalized Relational Learning
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
Forest Packing: Fast Parallel, Decision Forests
Instance Spaces for Objective Assessment of Algorithms and Benchmark Test Suites
Active Learning of Classification Models with Likert-Scale Feedback
Towards Classification of Social Streams
Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases
Proceedings of the 2018 SIAM International Conference on Data Mining, SDM 2018, May 3-5, 2018, San Diego Marriott Mission Valley, San Diego, CA, USA
Learning Linear Dynamical Systems from Multivariate Time Series: A Matrix Factorization Based Framework
OpenFE++: Efficient Automated Feature Generation via Feature Interaction
Towards Identifying Causal Relation Between Instances and Labels
Towards Learning Outcome Prediction via Modeling Question Explanations and Student Responses
GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
Parallel Pairwise Clustering
A Dynamic Nonparametric Model for Characterizing the Topical Communities in Social Streams
Attacking DBSCAN for Fun and Profit
Causal Inference by Direction of Information
WindMine: Fast and Effective Mining of Web-click Sequences
Structure-Enhanced Heterogeneous Graph Contrastive Learning
Redundancies in Data and their Effect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets
Sparse Max-Margin Multiclass and Multi-label Classifier Design for Fast Inference
Mining Abnormal Patterns from Heterogeneous Time-Series with Irrelevant Features for Fault Event Detection
Input Selection for Bandwidth-Limited Neural Network Inference
WIGM: Discovery of Subgraph Patterns in a Large Weighted Graph
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms
Global Nonlinear Metric Learning by Gluing Local Linear Metrics
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation
Outlier Detection with Autoencoder Ensembles
Integrating Distance Metrics Learned from Multiple Experts and its Application in Inter-Patient Similarity Assessment