yusuke1997/dblp-id-title huggingface dataset:
Slope One Predictors for Online Rating-Based Collaborative Filtering
CAMLP: Confidence-Aware Modulated Label Propagation
We Are Not Your Real Parents: Telling Causal from Confounded using MDL
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series
Spherical Principal Component Analysis
Discriminative Training of Structured Dictionaries via Block Orthogonal Matching Pursuit
Meta-Learning with Motif-based Task Augmentation for Few-Shot Molecular Property Prediction
A New Method for Rule Finding Via Bootstrapped Confidence Intervals
Sparse Decomposition for Time Series Forecasting and Anomaly Detection
Approximate Splitting for Ensembles of Trees using Histograms
Private and Right-Protected Big Data Publication: An Analysis
HyperFLoRA: Federated Learning with Instantaneous Personalization
WIP: mining Weighted Interesting Patterns with a strong weight and/or support affinity
Robust Sparse Online Learning for Data Streams with Streaming Features
Data Peeler: Contraint-Based Closed Pattern Mining in n-ary Relations
Filling Missing Values on Wearable-Sensory Time Series Data
Multi-Label Collective Classification
Proceedings of the Fourth SIAM International Conference on Data Mining, Lake Buena Vista, Florida, USA, April 22-24, 2004
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems
Group Centrality Maximization via Network Design
Efficient Anytime Density-based Clustering
Fast Eigen-Functions Tracking on Dynamic Graphs
Robust Clustering for Tracking Noisy Evolving Data Streams
Creating a Cluster Hierarchy under Constraints of a Partially Known Hierarchy
Regularized Structured Output Learning with Partial Labels
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Tracking Events Using Time-dependent Hierarchical Dirichlet Tree Model
H 2 ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions
A Flexible Open-Source Toolbox for Scalable Complex Graph Analysis
Identifying Information-Rich Subspace Trends in High-Dimensional Data
A Graduated Non-Convexity Relaxation for Large Scale Seriation
Adaptive Holding for Online Bottleneck Matching with Delays
Continuous-Time Bayesian Modeling of Clinical Data
Supervised Clustering of Label Ranking Data
K-Means Clustering Over a Large, Dynamic Network
Laplacian Spectral Properties of Graphs from Random Local Samples
Sentiment Topic Model with Decomposed Prior
BreachRadar: Automatic Detection of Points-of-Compromise
FAMER: Making Multi-Instance Learning Better and Faster
Learning Time-series Shapelets Enhancing Discriminability
Document Clustering Meets Topic Modeling with Word Embeddings
Mining Connection Pathways for Marked Nodes in Large Graphs
Mining Frequent Sequential Patterns under Regular Expressions: A Highly Adaptive Strategy for Pushing Contraints
Efficient Permutation Testing for Significant Sequential Patterns
Mining Behavior Graphs for "Backtrace" of Noncrashing Bugs
BRNet: Branched Residual Network for Fast and Accurate Predictive Modeling of Materials Properties
FutureRank: Ranking Scientific Articles by Predicting their Future PageRank
Predictive Optimization with Zero-Shot Domain Adaptation
An Index For Temporal Closeness Computation in Evolving Graphs
Faster Jobs in Distributed Data Processing using Multi-Task Learning
High Dimensional Structured Estimation with Noisy Designs
Metrics for Inter-Dataset Similarity with Example Applications in Synthetic Data and Feature Selection Evaluation
Prior-Free Rare Category Detection
CBS: A New Classification Method by Using Sequential Patterns
Beyond Models! Explainable Data Valuation and Metric Adaption for Recommendation
SamBaTen: Sampling-based Batch Incremental Tensor Decomposition
Constrained Spectral Clustering using L1 Regularization
Hybrid Bayesian Optimization with DIRECT
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Traffic
Monitoring and Mining Insect Sounds in Visual Space
RBA: An Integrated Framework for Regression based on Association Rules
Detecting Seasonal Trends and Cluster Motion Visualization for Very High Dimensional Transactional Data
2-Dimensional Singular Value Decomposition for 2D Maps and Images
Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection
Providing Privacy through Plausibly Deniable Search
Correlation by Compression
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications
Generalized Sensitivity Analysis: A Framework for Evaluating Data Analysis Results
Visualizing RFM Segmentation
Analytical Evaluation of Clustering Results Using Computational Negative Controls
A New Gravitational Clustering Algorithm
Efficient Distribution Mining and Classification
Preventing Information Leaks in Email
Beyond The Evidence Lower Bound: Dual Variational Graph Auto-Encoders For Node Clustering
Anomaly Detection via Graph Contrastive Learning
Class-Specific Ensembles for Active Learning
Temporal-Aware Graph Neural Network for Credit Risk Prediction
Turning the Tide: Curbing Deceptive Yelp Behaviors
Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of the Ethereum Graph?
MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification
On Predicting and Generating a Good Break Shot in Billiards Sports
Fast Exact Max-Kernel Search
Representation is Everything: Towards Efficient and Adaptable Similarity Measures for Biological Data
Active Sampling: An Effective Approach to Feature Selection
Extracting Researcher Metadata with Labeled Features
A Compression Based Distance Measure for Texture
Exact and Approximate Reverse Nearest Neighbor Search for Multimedia Data
Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection
A Lagrangian-based approach to learn distance metrics for clustering with minimal data transformation
Reservoir-Based Random Sampling with Replacement from Data Stream
Explicit Thermodynamic Properties using Radial Basis Functions Neural Networks
Learning Confident Classifiers in the Presence of Label Noise
Explainable Concept Graph Completion by Bridging Open-Domain Relations and Concepts
A Deep Learning Approach to Link Prediction in Dynamic Networks
Discovering Context-aware Influential Objects
Early Forecasting of the Impact of Traffic Accidents Using a Single Shot Observation
Time-Transformer: Integrating Local and Global Features for Better Time Series Generation
A Fast Trust-Region Newton Method for Softmax Logistic Regression
DSL: Discriminative Subgraph Learning via Sparse Self-Representation
Lazy Learning by Scanning Memory Image Lattice
Active Multitask Learning Using Both Latent and Supervised Shared Topics
Personalized Ranking on Poisson Factorization
A Framework for Exploring Categorical Data
Unsupervised Feature Learning by Deep Sparse Coding
Predicting Customer Churn in Mobile Networks through Analysis of Social Groups
Towards Attack-Resilient Geometric Data Perturbation
Patient Risk Prediction Model via Top-k Stability Selection
Neural Locality Sensitive Hashing for Entity Blocking
A Foundational Approach to Mining Itemset Utilities from Databases
Highlighting Diverse Concepts in Documents
Combining Active Learning and Dynamic Dimensionality Reduction
Learning on Probabilistic Labels
GAD: General Activity Detection for Fast Clustering on Large Data
Collaborative User Network Embedding for Social Recommender Systems
Triadic Measures on Graphs: The Power of Wedge Sampling
Black-box Expectation Propagation for Bayesian Models
Linking Heterogeneous Input Spaces with Pivots for Multi-Task Learning
Significance of Patterns in Time Series Collections
Hierarchical Clustering for Thematic Browsing and Summarization of Large Sets of Association Rules
Spatial Scan Statistics for Graph Clustering
Optimal Intervention on Weighted Networks via Edge Centrality
Evolutionary Soft Co-Clustering
Shared Memory Paraellization of Data Mining Algorithms: Techniques, Programming Interface, and Performance
k-means-: A Unified Approach to Clustering and Outlier Detection
Multi-field Correlated Topic Modeling
XGExplainer: Robust Evaluation-based Explanation for Graph Neural Networks
On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples
DensEst: Density Estimation for Data Mining in High Dimensional Spaces
Adaptive Informative Sampling for Active Learning
Learning a Neural-network-based Representation for Open Set Recognition
Towards Similarity-Aware Time-Series Classification
Causal Discovery by Graph Attention Reinforcement Learning
Sparse Latent Semantic Analysis
Semantic Smoothing for Bayesian Text Classification with Small Training Data
Fisher Deep Domain Adaptation
Signed Network Embedding in Social Media
Do winning tickets exist before DNN training?
Looking for Nonlinearities in the Large Scale Dynamics of the Atmosphere
Adaptive Grids for Clustering Massive Data Sets
Boosting Optimal Logical Patterns Using Noisy Data
Error Metrics for Learning Reliable Manifolds from Streaming Data
Fairness-aware Agnostic Federated Learning
Integrity Verification of K-means Clustering Outsourced to Infrastructure as a Service (IaaS) Providers
Learning from Time-Changing Data with Adaptive Windowing
Word Embedding with Neural Probabilistic Prior
Linear Time Motif Discovery in Time Series
On Finding the Point Where There Is No Return: Turning Point Mining on Game Data
Second-order Optimization for Non-convex Machine Learning: an Empirical Study
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction
Density-Connected Subspace Clustering for High-Dimensional Data
Unsupervised Selective Manifold Regularized Matrix Factorization
Discrete Listwise Collaborative Filtering for Fast Recommendation
Propagation-based Sentiment Analysis for Microblogging Data
Time-Aware Subscription Prediction Model for User Acquisition in Digital News Media
Variational Invariant Representation Learning for Multimodal Recommendation
Pluggable Deep Thompson Sampling with Applications to Recommendation
Cheaper by the Dozen: Batched Algorithms
Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18-20, 2024
Robust Textual Data Streams Mining Based on Continuous Transfer Learning
Frugal Traffic Monitoring with Autonomous Participatory Sensing
RelSim: Relation Similarity Search in Schema-Rich Heterogeneous Information Networks
Sign-Regularized Multi-Task Learning
Do You Trust to Get Trust? A Study of Trust Reciprocity Behaviors and Reciprocal Trust Prediction
Non-negative Matrix Factorization, Convexity and Isometry
Learning Time-series Shapelets via Supervised Feature Selection
Fine-grained Attributed Graph Clustering
Group Sparsity in Nonnegative Matrix Factorization
Graph-based Student Knowledge Profile for Online Intelligent Education
Inferring Probability Distributions of Graph Size and Node Degree from Stochastic Graph Grammars
CaMU: Disentangling Causal Effects in Deep Model Unlearning
Mining Changes of Classification by Correspondence Tracing
Feature Selection for Nonlinear Regression and its Application to Cancer Research
Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling
Multiresolution Motif Discovery in Time Series
Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022, Alexandria, VA, USA, April 28-30, 2022
Bursty Feature Representation for Clustering Text Streams
Accelerating Time Series Searching with Large Uniform Scaling
Outlier Detection with Globally Optimal Exemplar-Based GMM
Active Semi-Supervision for Pairwise Constrained Clustering
Online Analysis of Community Evolution in Data Streams
Boosting Localized Classifiers in Heterogeneous Databases
Pattern detection in large temporal graphs using algebraic fingerprints
Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x
Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning
Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs
Risk-Sensitive Learning via Expected Shortfall Minimization
Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns
Near-optimal Supervised Feature Selection among Frequent Subgraphs
Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction
Towards Spatially-Lucid AI Classification in Non-Euclidean Space: An Application for MxIF Oncology Data
Sign-aware Perturbations Regression
Efficient Computation of Partial-Support for Mining Interesting Itemsets
Predictive Modeling with Heterogeneous Sources
Reconstructing Randomized Social Networks
Simultaneous Unsupervised Learning of Disparate Clusterings
Communication and Memory Efficient Parallel Decision Tree Construction
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation
Time-sensitive Classification of Behavioral Data
A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks
Parameter-Efficient Interventions for Enhanced Model Merging
Hash-Based Feature Learning for Incomplete Continuous-Valued Data
DMDHC: Discovery of Multi-Density Hierarchical Cluster Structures
Unsupervised Segmentation of Conversational Transcripts
An LLE based Heterogeneous Metric Learning for Cross-media Retrieval
From Categorical to Numerical: Multiple Transitive Distance Learning and Embedding
Reconstruction from Randomized Graph via Low Rank Approximation
The Asymmetric Approximate Anytime Join: A New Primitive with Applications to Data Mining
Feature Interaction Aware Automated Data Representation Transformation
Generalized Similarity Kernels for Efficient Sequence Classification
Exploiting Coherence for the Simultaneous Discovery of Latent Facets and associated Sentiments
Efficient Mining of Temporally Annotated Sequences
Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery
EstImAgg: A Learning Framework for Groupwise Aggregated Data
Exploiting Structure for Fast Kernel Learning
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction
Automatic Unsupervised Tensor Mining with Quality Assessment
Direct Density Ratio Estimation with Dimensionality Reduction
Classifying Imbalanced Data Streams via Dynamic Feature Group Weighting with Importance Sampling
It Takes Two to Tango: Exploring Social Tie Development with Both Online and Offline Interactions
RHINE: A Regime-Switching Model with Nonlinear Representation for Discovering and Forecasting Regimes in Financial Markets
Structural Diversity for Privacy in Publishing Social Networks
A Dual-Tree Algorithm for Fast k -means Clustering With Large k
Rank Aggregation for Similar Items
Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
Area Under ROC Optimisation using a Ramp Approximation
Depth-First Non-Derivable Itemset Mining
Nonnegative Principal Component Analysis for Proteomic Tumor Profiles
Probabilistic Inverse Modeling: An Application in Hydrology
Robust Reputation-Based Ranking on Bipartite Rating Networks
Loadstar: A Load Shedding Scheme for Classifying Data Streams
On Privacy-Preservation of Text and Sparse Binary Data with Sketches
Top-k Correlative Graph Mining
CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction
Community Discovery in Social Networks via Heterogeneous Link Association and Fusion
Predicting the Popularity of News Articles
Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering
Topic-driven Clustering for Document Datasets
Fine-grained Spatio-temporal Event Prediction with Self-adaptive Anchor Graph
Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window
Discovery of Rare Sequential Topic Patterns in Document Stream
FEDRA: A Fast and Efficient Dimensionality Reduction Algorithm
Mining Minimal Contrast Subgraph Patterns
A Spectral Clustering Approach To Finding Communities in Graph
A Statistical Learning Theory Framework for Supervised Pattern Discovery
Outlier Detection with Space Transformation and Spectral Analysis
Multi-View Clustering via Joint Nonnegative Matrix Factorization
Ranking with submodular functions on the fly
Taxonomy-Guided Fine-Grained Entity Set Expansion
AutoGFS: Automated Group-based Feature Selection via Interactive Reinforcement Learning
Directed Interpretable Discovery in Tensors with Sparse Projection
Lag-Aware Multivariate Time-Series Segmentation
Change Detection from Temporal Sequences of Class Labels: Application to Land Cover Change Mapping
Estimating Mutual Information via Geodesic k NN
The Odd One Out: Identifying and Characterising Anomalies
Mining Association Rules of Simple Conjunctive Queries
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature
An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms
Fast Unsupervised Location Category Inference from Highly Inaccurate Mobility Data
Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
Heterogeneous Multi-Agent Framework for Dynamic Generalized Category Discovery
Capricorn: An Algorithm for Subtropical Matrix Factorization
GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction
Evaluating Time Series Models with Knowledge Discovery
Image Constrained Blockmodelling: A Constraint Programming Approach
Mining Text for Word Senses Using Independent Component Analysis
Missed Opportunities in Fair AI
A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection
Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series
p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics
Learning Topics in Short Texts by Non-negative Matrix Factorization on Term Correlation Matrix
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series
HALO: Learning to Prune Neural Networks with Shrinkage
On the Non-Trivial Generalization of Dynamic Time Warping to the Multi-Dimensional Case
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
Item Sets that Compress
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting
Multi-label Classification without the Multi-label Cost
Exact Passive-Aggressive Algorithm for Multiclass Classification Using Support Class
PageRank: HITS and a Unified Framework for Link Analysis
Efficient Mining of Maximal Sequential Patterns Using Multiple Samples
Centralities in Large Networks: Algorithms and Observations
Verifying Tree Ensembles by Reasoning about Potential Instances
Discriminative Transfer Learning on Manifold
A Look Into News Avoidance Through AWRS: An Avoidance-Aware Recommender System
Efficient Wind Speed Nowcasting with GPU-Accelerated Nearest Neighbors Algorithm
MultiNetAD: Multiplex Network-Based Anomaly Access Detection Featuring Semantic Hierarchies
Collaborative Attention Mechanism for Multi-Modal Time Series Classification
NSVD : Normalized Singular Value Deviation Reveals Number of Latent Factors in Tensor Decomposition
Performance of Recommendation Systems in Dynamic Streaming Environments
Fast and Accurate Gene Prediction by Decision Tree Classification
Fast Online SVD Revisions for Lightweight Recommender Systems
Symmetric Nonnegative Matrix Factorization for Graph Clustering
Generalized Inverse Classification
Discovering Substantial Distinctions among Incremental Bi-Clusters
Mining Maximal Induced Bicliques using Odd Cycle Transversals
On Multidimensional Sharpening of Uncertain Data
Mining Probabilistic Representative Frequent Patterns From Uncertain Data
Evaluating Event Credibility on Twitter
Deep Attention Model for Triage of Emergency Department Patients
Debiased Imitation Learning for Modulated Temporal Point Processes
Rare Disease Prediction by Generating Quality-Assured Electronic Health Records
Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification
A Constructive Setting for the Problem of Density Ratio Estimation
Refining Network Alignment to Improve Matched Neighborhood Consistency
Efficient Discovery of Interesting Patterns Based on Strong Closedness
Multi-topic Based Query-Oriented Summarization
Tensorized Hypergraph Neural Networks
Learning Feature Dependencies for Noise Correction in Biomedical Prediction
TADAM: Learning Timed Automata from Noisy Observations
Spatiotemporal Event Forecasting in Social Media
Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships
A Mixture Model for Clustering Ensembles
ParaSketch: Parallel Tensor Factorization via Sketching
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices
Adiabatic Quantum Computing for Max-Sum Diversification
Optimizing External and Internal Knowledge of Foundation Models for Scientific Discovery
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data
Influence without Authority: Maximizing Information Coverage in Hypergraphs
CPAR: Classification based on Predictive Association Rules
Practical Private Computation and Zero-Knowledge Tools for Privacy-Preserving Distributed Data Mining
Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data
Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions
Change-Point Detection using Krylov Subspace Learning
Class Augmented Active Learning
Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling
Mining Temporal Databases for Subsequence Patterns
Cluster Selection in Divisive Clustering Algorithms
Unveiling Variables in Systems of Linear Equations
Efficiently Summarising Event Sequences with Rich Interleaving Patterns
POLYGLOT-NER: Massive Multilingual Named Entity Recognition
Maximising the Quality of Influence
Mining Social Dependencies in Dynamic Interaction Networks
User Migration across Multiple Social Media Platforms
Fast Algorithms for Finding Extremal Sets
Mining Frequent Patterns by Differential Refinement of Clustered Bitmaps
Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem
Multi-polytope Machine for Classification
Embed and Conquer: Scalable Embeddings for Kernel k -Means on MapReduce
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering
Making k-means Even Faster
Online Clustering of Multivariate Time-series
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity
SpecLDA: Modeling Product Reviews and Specifications to Generate Augmented Specifications
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach
A Method to Accelerate Human in the Loop Clustering
Positive Borders or Negative Borders: How to Make Lossless Generator Based Representations Concise
NetSpot: Spotting Significant Anomalous Regions on Dynamic Networks
Roughly Balanced Bagging for Imbalanced Data
Efficient Filtering of Large DatasetA User-Centric Paradigm
Discovering Reliable Causal Rules
Statictical Models for Unequally Spaced Time Series
Evaluating Query Result Significance in Databases via Randomizations
A Marginalized Denoising Method for Link Prediction in Relational Data
Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation
Attention-Aware Answers of the Crowd
Dynamic Classification of Defect Structures in Molecular Dynamics Simulation Data
Outlier Detection for Text Data
Robust Map Matching for Heterogeneous Data via Dominance Decompositions
Gaussian Process for Dimensionality Reduction in Transfer Learning