yusuke1997/dblp-id-title huggingface dataset:
Privacy Preserving Naïve Bayes Classifier for Vertically Partitioned Data
MODS: Multiple One-class Data Streams Learning from Homogeneous Data
Constrained Mean Shift Clustering
Human Dynamics in Large Communication Networks
Helper Recommendation with seniority control in Online Health Community
Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
A Range Query Approach for High Dimensional Euclidean Space Based on EDM Estimation
An Efficient Algorithm for Assessing the Number of st -Paths in Large Graphs
Efficient Summarizing of Evolving Events from Twitter Streams
DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering
Hierarchical Classification of Real Life Documents
A Bayesian Technique for Estimating the Credibility of question Answerers
Learning from Imbalanced Crowdsourced Labeled Data
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
Hierarchical Superpixel Segmentation via Structural Information Theory
Hierarchical Reinforced Urban Planning: Jointly Steering Region and Block Configurations
Semi-Supervised Dimensionality Reduction
Decomposition of Event Sequences into Independent Components
Test-Time Training for Spatial-Temporal Forecasting
Incomplete Conditional Density Estimation for Fast Materials Discovery
MACFP: Maximal Approximate Consecutive Frequent Pattern Mining under Edit Distance
CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection
Targeted matrix completion
One-Class-Based Uncertain Data Stream Learning
Detecting Irregularly Shaped Significant Spatial and Spatio-Temporal Clusters
Vertex-reinforced Random Walk for Network Embedding
Concept Drift Detection with Hierarchical Hypothesis Testing
AutoSTDiff: Autoregressive Spatio-Temporal Denoising Diffusion Model for Asynchronous Trajectory Generation
Correlating Surgical Vital Sign Quality with 30-Day Outcomes using Regression on Time Series Segment Features
A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions
Understanding Importance of Collaborations in Co-authorship Networks: A Supportiveness Analysis Approach
Joint Cluster Analysis of Attribute Data and Relationship Data: the Connected k-Center Problem
Disinformation Detection: An Evolving Challenge in the Age of LLMs
Adversarial Learning with Bayesian Hierarchical Mixtures of Experts
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks
Explainable AI for Real-Time Video Anomaly Anticipation
Kernelized Sparse Self-Representation for Clustering and Recommendation
Exceptional Model Mining meets Multi-objective Optimization
Weighted Graph Compression for Parameter-free Clustering With PaCCo
Bayesian Cluster Ensembles
Near-separable Non-negative Matrix Factorization with ℓ 1 and Bregman Loss Functions
Robust Estimation of Causal Heteroscedastic Noise Models
On Classification of Graph Streams
Cyclic Transfer Learning for Recommender Systems with Heterogeneous Feedbacks
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
Selecting Shortcuts for a Smaller World
Scalable Software-Defect Localisation by Hierarchical Mining of Dynamic Call Graphs
CoFiSet: Collaborative Filtering via Learning Pairwise Preferences over Item-sets
IFD: Iterative Feature and Data Clustering
Classifying Documents Without Labels
Probabilistic Decomposition Transformer for Time Series Forecasting
Active Mining of Data Streams
On Finding Joint Subspace Boolean Matrix Factorizations
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases
Query-based Biclustering using Formal Concept Analysis
Graph-based Methods for Orbit Classification
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation
Randomizing Social Networks: a Spectrum Preserving Approach
Result Integrity Verification of Outsourced Privacy-preserving Frequent Itemset Mining
Maximizing the Effect of Information Adoption: A General Framework
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30 - May 2, 2015
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Principal Component Analysis and Effective K-Means Clustering
A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems
Fairness in representation: quantifying stereotyping as a representational harm
Deterministic Latent Variable Models and Their Pitfalls
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences
Multi-state Survival Analysis using Pseudo value-based Deep Neural Networks
Linear and Kernel Classification: When to Use Which?
Time-Decayed Correlated Aggregates over Data Streams
SeqIndex: Indexing Sequences by Sequential Pattern Analysis
Reduced Set KPCA for Improving the Training and Execution Speed of Kernel Machines
Unsupervised Neural Categorization for Scientific Publications
Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware
Convex Matrix Completion: A Trace-Ball Optimization Perspective
Genius: Subteam Replacement with Clustering-based Graph Neural Networks
What Do Questions Exactly Ask? MFAE: Duplicate Question Identification with Multi-Fusion Asking Emphasis
Dense Neighborhood Pattern Sampling in Numerical Data
Proceedings of the Third SIAM International Conference on Data Mining, San Francisco, CA, USA, May 1-3, 2003
A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources
Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Block-LDA: Jointly modeling entity-annotated text and entity-entity links
A Pattern Search Method for Model Selection of Support Vector Regression
Bridging Domains with Words: Opinion Analysis with Matrix Tri-factorizations
CoT-Decoding: Complex Reasoning via Chain-of-Thought Decoding
Detecting and Tracking Coordinated Groups in Dense, Systematically Moving, Crowds
A Clustering Technique for Mining Data from Text Tables
Multi-task Multiple Kernel Learning
Clustering Evaluation in High-Dimensional Data
Finding low-tension communities
An Interpretable Measure of Dataset Complexity for Imbalanced Classification Problems
Contextual Bandits for Advertising Campaigns: A Diffusion-Model Independent Approach
Multi-Layered Framework for Modeling Relationships between Biased Objects
Random Features Strengthen Graph Neural Networks
HP2PC: Scalable Hierarchically-Distributed Peer-to-Peer Clustering
Deep Transfer Reinforcement Learning for Text Summarization
A Predictive Optimization Framework for Hierarchical Demand Matching
Slim: Directly Mining Descriptive Patterns
On Point Sampling Versus Space Sampling for Dimensionality Reduction
Modeling Item-specific Effects for Video Click
Density-based Projected Clustering over High Dimensional Data Streams
CLSI: A Flexible Approximation Scheme from Clustered Term-Document Matrices
Data Reduction in Support Vector Machines by a Kernelized Ionic Interaction Model
Sort-Merge Feature Selection for Video Data
Large-Scale Nonparametric Estimation of Vehicle Travel Time Distributions
Context-Aware Frequency-Embedding Networks for Spatio-Temporal Portfolio Selection
Harmonic Alignment
From Theory to Practice: Efficient Active Cost-sensitive Classification with Expected Error Reduction
Synthesizing Skeletal Motion and Physiological Signals as a Function of a Virtual Human's Actions and Emotions
Clustering with Constraints: Feasibility Issues and the k-Means Algorithm
A PAC Bound for Approximate Support Vector Machines
Generic Methods for Multi-criteria Evaluation
A Graph-Based Approach for Active Learning in Regression
VizCluster: An Interactive Visualization Approach to Cluster Analysis and Its Application on Microarray Data
Feature-based factorized Bilinear Similarity Model for Cold-Start Top- n Item Recommendation
DOMISA: DOM-Based Information Space Adsorption of Web Information Hierarchy Mining
Time-delayed Multivariate Time Series Predictions
Positive Unlabeled Learning for Data Stream Classification
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network
Accurately Estimating Unreported Infections using Information Theory
Maximizing Approximately k -Submodular Functions
Functional Node Detection on Linked Data
Online Discovery of Top-k Similar Motifs in Time Series Data
A Framework for Clustering Massive Text and Categorical Data Streams
Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection
Adaptive User Distance Modeling in Social Media
Boolean matrix factorization meets consecutive ones property
Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity
Ensembles of Elastic Distance Measures for Time Series Classification
Estimating Ad Impact on Clicker Conversions for Causal Attribution: A Potential Outcomes Approach
Feature Weighted SVMs Using Receiver Operating Characteristics
Vocal Competence Based Karaoke Recommendation: A Maximum-Margin Joint Model
Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation
Bridging Semantics: Mobility Analytics Framework for Knowledge Transfer
NLRR++: Scalable Subspace Clustering via Non-Convex Block Coordinate Descent
Triangle counting in streamed graphs via small vertex covers
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach
The Set Classification Problem and Solution Methods
High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic
WAT: Finding Top-K Discords in Time Series Database
Similarity Measures for Categorical Data: A Comparative Evaluation
Automated Learning of Semantic Embedding Representations for Diffusion Models
Aspect-Based Sentiment Analysis with Minimal Guidance
A Systematic Cross-Comparison of Sequence Classifiers
A Tree-Based Kernel for Graphs
Exploring Latent Semantic Factors to Find Useful Product Reviews
Online Discovery of Group Level Events in Time Series
On Classification of High-Cardinality Data Streams
Exploiting Multifaceted Nature of Items and Users for Session-based Recommendation
Deep Co-Clustering
GIN: A Clustering Model for Capturing Dual Heterogeneity in Networked Data
On the Comparison of Relative Clustering Validity Criteria
STABLE: Identifying and Mitigating Instability in Embeddings of the Degenerate Core
Active Multi-task Learning via Bandits
Striking Two Birds With One Stone: Simultaneous Mining of Positive and Negative Spatial Patterns
Efficient Active Learning with Boosting
Margin Distribution Logistic Machine
Density-Based Clustering Validation
Coarse-to-Fine Open Information Extraction via Relation Oriented Reading Comprehension
Matrix Condition Number Prediction with SVM Regression and Feature Selection
Unified Modeling and Clustering of Mobility Trajectories with Spatiotemporal Point Processes
Very Fast Similarity Queries on Semi-Structured Data from the Web
Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model
Vertex Clustering of Augmented Graph Streams
Cycle-Balanced Representation Learning For Counterfactual Inference
Functional Autoencoders for Functional Data Representation Learning
Abnormal Event Detection via Hypergraph Contrastive Learning
Towards the Prediction of Protein Abundance from Tandem Mass Spectrometry Data
A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System
A Framework for the Evaluation and Management of Network Centrality
User Preference Learning with Multiple Information Fusion for Restaurant Recommendation
Top-N Recommendation with Novel Rank Approximation
MM-Pred: A Deep Predictive Model for Multi-attribute Event Sequence
Correlation Clustering for Learning Mixtures of Canonical Correlation Models
Weighted Rank-One Binary Matrix Factorization
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Price Recommendation on Vacation Rental Websites
Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification
Large Scale Graph Mining and Inference for Malware Detection
Hybrid Tokenization and Datasets for Solving Mathematics and Science Problems Using Transformers
Weighted Consensus Clustering
HAR: Hub, Authority and Relevance Scores in Multi-Relational Data for Query Search
Collaborative Document Clustering
Understanding Influence Maximization via Higher-Order Decomposition
A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations
Joint Post and Link-level Influence Modeling on Social Media
Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions
Integration of Multiple Networks for Robust Label Propagation
Frank-Wolfe algorithm for learning SVM-type multi-category classifiers
Deep Anomaly Detection on Attributed Networks
The Impact of Community Safety on House Ranking
Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series
Pattern-based Time Series Semantic Segmentation with Gradual State Transitions
Estimating Propensity Scores with Deep Adaptive Variable Selection
Heterogeneous Data Fusion via Space Alignment Using Nonmetric Multidimensional Scaling
Semi-supervised Learning by Sparse Representation
Mining Non-Derivable Association Rules
Cluster Validity Analysis of Alternative Results from Multi-Objective Optimization
Understanding and Utilizing the Hierarchy of Abnormal BGP Events
Learning On-the-Job to Re-rank Anomalies from Top-1 Feedback
Discovery of Precursors to Adverse Events using Time Series Data
Capturing Model Uncertainty with Data Augmentation in Deep Learning
PLUMS: Predicting Links Using Multiple Sources
Scalable Anomaly Ranking of Attributed Neighborhoods
Multi-Domain Manifold Learning for Drug-Target Interaction Prediction
MARBLES: Mining Association Rules Buried in Long Event Sequences
Collective Opinion Spam Detection using Active Inference
TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing
Name Reference Resolution in Organizational Email Archives
Near-Optimal Mapping of Network States using Probes
Transductive HSIC Lasso
Constraint-Based Subspace Clustering
VOG: Summarizing and Understanding Large Graphs
Robust Unsupervised Feature Selection on Networked Data
Multi-Interest Network with Simple Diffusion for Multi-Behavior Sequential Recommendation
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization
Fisher Scoring Method for Neural Networks Optimization
Model-based Clustering With Probabilistic Constraints
Dense and well-connected subgraph detection in dual networks
Mining Frequent Itemsets in Evolving Databases
Kernelized Matrix Factorization for Collaborative Filtering
Detection and Characterization of Anomalies in Multivariate Time Series
SemInf: A Burst-based Semantic Influence Model for Biomedical Topic Influence
Detecting Novel Network Intrusions Using Bayes Estimators
An Outlier-based Data Association Method for Linking Criminal Incidents
Equivalence of Several Two-Stage Methods for Linear Discriminant Analysis
MACH: Fast Randomized Tensor Decompositions
Mining Unconnected Patterns in Workflows
A Rare and Critical Condition Search Technique and its Application to Telescope Stray Light Analysis
Class Relevant Pattern Mining in Output-Polynomial Time
Multi-Task Multiple Kernel Relationship Learning
Efficient and Effective Accelerated Hierarchical Higher-Order Logistic Regression for Large Data Quantities
Multidimensional Association Rules in Boolean Tensors
Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times
Semi-Supervised Clustering with Partial Background Information
Computation of the Sample Fréchet Mean for Sets of Large Graphs with Applications to Regression
Extracting Cyber Communities through Patterns
Deep Multi-view Information Bottleneck
Improving Accessibility of Transaction-centric Web Objects
Tensor Spectral Clustering for Partitioning Higher-order Network Structures
MoVAE: A Variational AutoEncoder for Molecular Graph Generation
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning
Iterative Deepening Dynamic Time Warping for Time Series
Improved mixing time for k -subgraph sampling
Representation Learning on Dynamic Network of Networks
A Multi-label Least-Squares Hashing For Scalable Image Search
Membership Detection Using Cooperative Data Mining Algorithms
Health monitoring of a shaft transmission system via hybrid models of PCR and PLS
Learning Compressible Models
Efficient Matching of Substrings in Uncertain Sequences
Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces
Provable Distributed Stochastic Gradient Descent with Delayed Updates
Proceedings of the Twelfth SIAM International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012
CoSelect: Feature Selection with Instance Selection for Social Media Data
Finding Young Stellar Populations in Elliptical Galaxies from Independent Components of Optical Spectra
Result Integrity Verification of Outsourced Bayesian Network Structure Learning
R-MAT: A Recursive Model for Graph Mining
Advanced Prototype Machines: Exploring Prototypes for Classification
Disambiguation-Free Partial Label Learning
Power Simultaneous Spectral Data Embedding and Clustering
Learning to Read Between the Lines: The Aspect Bernoulli Model
Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection
JUMP: A Fast Deterministic Algorithm to Find the Closest Pair of Subsequences
Multi-view Weak-label Learning based on Matrix Completion
CADENCE: Community-Aware Detection of Dynamic Network States
Online Truth Discovery on Time Series Data
Improved Spatial-Temporal Forecasting through Modelling of Spatial Residuals in Recent History
EduHawkes: A Neural Hawkes Process Approach for Online Study Behavior Modeling
Theorectical Analysis of Subsequence Time-Series Clustering from a Frequency-Analysis Viewpoint
Identifying Potential Investors with Data Driven Approaches
Collusion in the U. S. Crop Insurance Program: Applied Data Mining
ℓ 0 -Regularized Sparsity for Probabilistic Mixture Models
Maximal Deviations of Incomplete U-statistics with Applications to Empirical Risk Sampling
Halite ds : Fast and Scalable Subspace Clustering for Multidimensional Data Streams
Exceptional Model Mining with Tree-Constrained Gradient Ascent
Single-Pass Distributed Learning of Multi-class SVMs Using Core-Sets
Pivot-based k-means Algorithm for Numerous-class Data Sets
Sampling Strategies to Evaluate the Performance of Unknown Predictors
Hierarchical Linear Discriminant Analysis for Beamforming
It Is Not Just What We Say, But How We Say Them: LDA-based Behavior-Topic Model
Constraint-Based Pattern Set Mining
Cost-Sensitive Double Updating Online Learning and Its Application to Online Anomaly Detection
Toward Relational Learning with Misinformation
On Flow Authority Discovery in Social Networks
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning
Cluster-Aware Compression with Provable K-means Preservation
Efficient Algorithms for Sequence Segmentation
StAGN: Spatial-Temporal Adaptive Graph Network via Contrastive Learning for Sleep Stage Classification
Towards Verification of Multi-Agent Systems
A View on the Architecture and Design of Highly Autonomous and Situated Agents
Exploiting Problem Structure for Distributed Constraint Optimization
An Introduction to Congregating in Multiagent Systems
Proceedings of the First International Conference on Multiagent Systems, June 12-14, 1995, San Francisco, California, USA
Modeling Adaptive Organizations
Probabilistic Reasoning in a Distributed Multi-Agent Environment
Cooperation by Iterated Plan Revision
Agent Societies without Dilemmas: An Evolutionary Approach
An Agent Architecture for Dynamic Re-Design of Agents
Emergent Behavior in Information Economies
Asynchronous Weak-Commitment Search for Solving Large-Scale Distributed Constraint Satisfaction Problems
Cooperating to Learn: Knowledge Discovery through Intelligent Learning Agents
The Consensus of Uncertainties in Distributed Expert Systems
An Overview of the Extended VUB Ecosystem, a MAS of Heterogeneous Robots
Searching for Optimal Coalition Structures
Linguistic Support for Agent Migration
A Comprehensive Theory of Meaning for Communication Acts in Multi-Agent Systems
Designing Social Cognition Models for Multi-Agent Systems through Simulating Primate Societies
Self-Organizing Manufacturing Control: An Industrial Application of Agent Technology
A Multi-Agent Testbed for Diverse Seamless Personal Information Networking Applications
Coordination of Multiple Intelligent Agents in the Infosphere
Recursive Agent and Agent-Group Tracking in a Real-Time Dynamic Environment
Computationally Grounded Theories of Agency
Towards Large-Scale Conflict Resolution: Initial Results
An Agent Framework for a Dynamically Distributed Application
Developing Industrial Multi-Agent Systems
Self-Organization Based on Coordinated Actions of Autonomous Agents
Learning Team Coordination Constraints through Execution
A Model of Progressive Multi-Agent Negotiation
A Quantitative Analysis of the Contract Net Protocol
Rational Balancing of Planning and Communication in the Dynamic Multi-Agents World
VIENA: A Multiagent Interface to a Virtual Environment
The Emergence of Cooperation in a Society of Autonomous Agents - The Prisoner's Dilemma Game under the Disclosure of Contract Histories
Reactive Real-Time Cooperation as a Combination of Altruism and Self Satisfaction
An Extension of UML by Protocols for Multiagent Interaction
Example-Based Frame Mapping for Heterogeneous Information Agents
How Agents Do It in Stream Logic Programming
Hierarchical and Lateral Coordination in MAS: An Analysis of Message Traffic Flow
Issues in Automated Negotiation and Electronic Commerce: Extending the Contract Net Framework
Data Gardens: An Artistic Proposal towards the Representation of Distributed and Dynamic Data using Multiagent Systems
How Much Should an Agent Know what Other Agents are Doing in a Cooperative Team?
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Reasoning about Belief Based on Common Knowledge of Observability of Actions
Dynamics in Transition Mental Activit
BiddingBot: A Multiagent Support System for Cooperative Bidding in Multiple Auctions
Multiagent Planning as a Social Process: Voting, Privacy, and Manipulation
A Taxonomy of Middle-Agents for the Internet
Assessing Usage Patterns to Improve Data Allocation via Auctions
More than Envy-Free
A Metalevel Coordination Strategy for Reactive Cooperative Planning
Unifying Control in a Layered Agent Architecture
Trust and Reputation Management in a Small-World Network
A Multi-Agent System for Controlling Intelligent Buildings
An Experimental Evaluation of Domain-Independent Fault Handling Services in Open Multi-Agent Systems
Organization Models and Behavioral Requirements Specification for Multi-Agent Systems
The Benefits of Environment Adaptive Organizations for Agent Coordination and Network Routing Problems
Rights and Commitment in Multi-Agent Agreements
A Cooperation Language
Temporal Social Reasoning in Dynamic Multi-Agent Systems
A Multi-Agent Framework for Inter-Organizational Applications
An Organization-Related Information Maintenance Component
Agents as Reasoners, Observers, or Arbitrary Believers
Knowledge and Behavior in Multiagent Systems
On Social Commitment, Roles and Preferred Goals
A Microeconomic Approach to Intelligent Resource Sharing in Multiagent Systems
An Adaptive Organizational Policy for Multi Agent Systems - AASMAN
Organic Programming for Multi-Agents
Study of the Efficiency of Multi-Agent Organizational Structure: An Approach Based on an Experiment
A Game-Theoretic Account of Collaboration in Communication
A Multi-Agent System for Intelligent Network Load Control Using a Market-Based Approach
Dynamic Service Pricing for Brokers in a Multi-Agent Economy
Deciding When to Commit to Action During Observation-Based Coordination