yusuke1997/dblp-id-title huggingface dataset:
Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting
The 11th International Workshop on Urban Computing
Segmentation and Automated Social Hierarchy Detection through Email Network Analysis
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation
CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors
Alpha seeding for support vector machines
Collaboration Equilibrium in Federated Learning
Prognosis and Diagnosis of Parkinson's Disease Using Multi-Task Learning
Mining discrete patterns via binary matrix factorization
Promoting Fairness and Priority in Selecting k -Winners Using IRV
Mixture models for learning low-dimensional roles in high-dimensional data
Mining unexpected rules by pushing user dynamics
Can Modifying Data Address Graph Domain Adaptation?
Top-k frequent itemsets via differentially private FP-trees
AdKDD 2025
Refining causality: who copied from whom?
Lifelong Machine Learning and Computer Reading the Web
Applying data mining in investigating money laundering crimes
Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes
Support for Diverse Students
Leveraging collaborative tagging for web item design
Can we push more constraints into frequent pattern mining?
Optimization of Collection Efforts in Automobile Financing - a KDD Supported Environment
Voxel Deconvolutional Networks for 3D Brain Image Labeling
Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion
Collaborative boosting for activity classification in microblogs
Adapting the right measures for K-means clustering
Intelligent Instruments: Discovering How to Turn Spectral Data into Information
Real-time ranking with concept drift using expert advice
Meta Structure: Computing Relevance in Large Heterogeneous Information Networks
Box drawings for learning with imbalanced data
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters
ALSA: Context-Sensitive Prompt Privacy Preservation in Large Language Models
PEBL: positive example based learning for Web page classification using SVM
Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression
Topology-Driven Multi-View Clustering via Tensorial Refined Sigmoid Rank Minimization
Efficient Sphere-Effect Based Information Diffusion Prediction on Large-scale Social Networks
Symbolic Regression: A Pathway to Interpretability Towards Automated Scientific Discovery
On effective classification of strings with wavelets
Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data
A framework for summarizing and analyzing twitter feeds
Identifying prospective customers
Preference-Optimized Retrieval and Ranking for Efficient Multimodal Recommendation
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, August 12-15, 2007
One-shot Multi-view Visual Conversational Recommendation
Mining the internet: the eighth wonder of the world
Incremental Label Distribution Learning
Mining frequent graph patterns with differential privacy
Exploratory analysis of highly heterogeneous document collections
Reserving-Masking-Reconstruction Model for Self-Supervised Heterogeneous Graph Representation
Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning
Towards a reliable prediction of conversion from Mild Cognitive Impairment to Alzheimer's Disease: stepwise learning using time windows
A Color-blind 3-Approximation for Chromatic Correlation Clustering and Improved Heuristics
PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models
Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction
Debiasing Recommendation by Learning Identifiable Latent Confounders
Real-Time Top-R Topic Detection on Twitter with Topic Hijack Filtering
Finding Effective Geo-social Group for Impromptu Activities with Diverse Demands
Exploiting Cognitive Structure for Adaptive Learning
Exploiting vulnerability to secure user privacy on a social networking site
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X
Point-of-Interest Recommendations: Learning Potential Check-ins from Friends
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction
Position-normalized click prediction in search advertising
Why Data Scientists Prefer Glassbox Machine Learning: Algorithms, Differential Privacy, Editing and Bias Mitigation
Evaluating Recommendation Systems Using the Power of Embeddings
SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, San Francisco, CA, USA, August 26-29, 2001
Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study
Cross-Network Learning with Partially Aligned Graph Convolutional Networks
i SAX: indexing and mining terabyte sized time series
Max-Min Diversification with Asymmetric Distances
Learning Patterns-Guided Data Generation for Knowledge Tracing
Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs
A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction
Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning
DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
Stock Price Prediction via Discovering Multi-Frequency Trading Patterns
Mining comparable bilingual text corpora for cross-language information integration
Planning Bike Lanes based on Sharing-Bikes' Trajectories
Constrained stochastic gradient descent for large-scale least squares problem
Real-time air quality monitoring through mobile sensing in metropolitan areas
Incremental Dual-memory LSTM in Land Cover Prediction
Using Instruction-Tuned LMs for Scalable Use Case-Based Shopping - Where Customers Meet Their Needs
Reinforced Anchor Knowledge Graph Generation for News Recommendation Reasoning
Learning with a non-exhaustive training dataset: a case study: detection of bacteria cultures using optical-scattering technology
Fast best-effort pattern matching in large attributed graphs
Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data
Fraud Transactions Detection via Behavior Tree with Local Intention Calibration
Applying collaborative filtering techniques to movie search for better ranking and browsing
A Context-aware Attention Network for Interactive Question Answering
Assortativity in Chung Lu Random Graph Models
Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems
Evaluating online ad campaigns in a pipeline: causal models at scale
Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks
Bias and controversy: beyond the statistical deviation
Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
Evolutionary clustering using frequent itemsets
DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks
Fairness without Demographics through Learning Graph of Gradients
Collective graph identification
Data selection for support vector machine classifiers
Big Data Analytics: Optimization and Randomization
CausalBench: Causal Learning Research Streamlined
Differentially Private Synthetic Data Release for Topics API Outputs
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction
KDD workshop on Evaluation and Trustworthiness of Generative AI Models
Network mining and analysis for social applications
Anonymizing healthcare data: a case study on the blood transfusion service
Discovering associations with numeric variables
Toward a Multi-Strategy and Cooperative Discovery System
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
Group formation in large social networks: membership, growth, and evolution
Efficient frequent item counting in multi-core hardware
Selective block minimization for faster convergence of limited memory large-scale linear models
HRSTORY: Historical News Review Based Online Story Discovery
Interactive exploration of coherent patterns in time-series gene expression data
PTE: Enumerating Trillion Triangles On Distributed Systems
Deep Inclusion Relation-aware Network for User Response Prediction at Fliggy
Big data analytics with small footprint: squaring the cloud
Chasing the Timber Trail: Machine Learning to Reveal Harvest Location Misrepresentation
A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction
Assessment and pruning of hierarchical model based clustering
CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning
The Spectral Zoo of Networks: Embedding and Visualizing Networks with Spectral Moments
Lazy naive credal classifier
TAG: Toward Accurate Social Media Content Tagging with a Concept Graph
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction
Mining asynchronous periodic patterns in time series data
Scalable SDE Filtering and Inference with Apache Spark
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
A Novel Approach for Prediction of Protein Subcellular Localization from Sequence Using Fourier Analysis and Support Vector Machines
Data mining solves tough semiconductor manufacturing problems
Analyzing microblogs with affinity propagation
A DEA approach for model combination
Adaptive Conformal Prediction Intervals for Invariant Learning
Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data
The Microsoft academic search dataset and KDD Cup 2013
Data Science for Assembly Engineering
Anomaly pattern detection in categorical datasets
A Novel Feature Space Augmentation Method to Improve Classification Performance and Evaluation Reliability
Synthetic review spamming and defense
Adaptive Stream Clustering Using Incremental Graph Maintenance
Decision support and profit prediction for online auction sellers
Understanding the Weakness of Large Language Model Agents within a Complex Android Environment
Large-scale matrix factorization with distributed stochastic gradient descent
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
A bayesian framework for estimating properties of network diffusions
Semi-Supervised Graph Imbalanced Regression
Deploying Analytics with the Portable Format for Analytics (PFA)
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
Modeling Network-level Traffic Flow Transitions on Sparse Data
PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce
Accelerated Equivalence Structure Extraction via Pairwise Incremental Search
Machine Learning for Materials Science (MLMS)
Mining the network value of customers
Source code identifier splitting using Yahoo image and web search engine
Group and topic discovery from relations and text
CLEAR: Addressing Representation Contamination in Multimodal Healthcare Analytics
GPCA: an efficient dimension reduction scheme for image compression and retrieval
Trustworthy Recommender Systems: Foundations and Frontiers
Image and Video Understanding for Recommendation and Spam Detection Systems
Marble: high-throughput phenotyping from electronic health records via sparse nonnegative tensor factorization
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection
Detecting Devastating Diseases in Search Logs
Graph Positional Autoencoders as Self-supervised Learners
Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit
Leveraging Knowledge Bases for Contextual Entity Exploration
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
Lessons Learned while Running ML Models in Harsh Environments
Change detection in rainfall and temperature patterns over India
Co-clustering by block value decomposition
Intelligent Request Strategy Design in Recommender System
Fast algorithms for maximal clique enumeration with limited memory
Classifying Treatment Responders: Bounds and Algorithms
City-Scale Map Creation and Updating using GPS Collections
Rank-heterogeneous Preference Models for School Choice
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems
A maximum entropy web recommendation system: combining collaborative and content features
Collaborative Filtering Meets Spectrum Shift: Connecting User-Item Interaction with Graph-Structured Side Information
Enhancing Financial Decision-Making Using Social Behavior Modeling
Deep Variational Network Embedding in Wasserstein Space
The 14th International Workshop on Urban Computing
Bringing data science to the speakers of every language
A classifier for semi-structured documents
Goal-Directed Inductive Matrix Completion
Core-periphery Partitioning and Quantum Annealing
Can a Deep Learning Model be a Sure Bet for Tabular Prediction?
Anti-Ad Blocking Strategy: Measuring its True Impact
Apolo: interactive large graph sensemaking by combining machine learning and visualization
VFLAIR-LLM: A Comprehensive Framework and Benchmark for Split Learning of LLMs
Overlapping community detection via bounded nonnegative matrix tri-factorization
Large-Scale Learnable Graph Convolutional Networks
Collective Opinion Spam Detection: Bridging Review Networks and Metadata
Quantitative evaluation of approximate frequent pattern mining algorithms
Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs
Are your data gathered?
Proceedings of the Third International Workshop on Multimedia Data Mining, MDM/KDD'2002, July 23rd, 2002, Edmonton, Alberta, Canada
Tolerating Data Missing in Breast Cancer Diagnosis from Clinical Ultrasound Reports via Knowledge Graph Inference
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods
A sparsity-inducing formulation for evolutionary co-clustering
Using ghost edges for classification in sparsely labeled networks
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting
Learning and making decisions when costs and probabilities are both unknown
MI2LS: multi-instance learning from multiple informationsources
Automatic Classification of Critical Findings in Radiology Reports
Discovering significant OPSM subspace clusters in massive gene expression data
DAGger: clustering correlated uncertain data (to predict asset failure in energy networks)
Naïve filterbots for robust cold-start recommendations
Single-pass online learning: performance, voting schemes and online feature selection
Data Science with Human in the Loop
TSMO 2024: Two-sided Marketplace Optimization
Mining preferences from superior and inferior examples
New EM derived from Kullback-Leibler divergence
Synthesising Audio Adversarial Examples for Automatic Speech Recognition
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Disentangled Multi-interest Representation Learning for Sequential Recommendation
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
Complicated Semantic Alignment for Long-Tail Query Rewriting in Taobao Search Based on Large Language Model
Instability of decision tree classification algorithms
Efficient mini-batch training for stochastic optimization
A Hierarchical Algorithm for Extreme Clustering
Networked bandits with disjoint linear payoffs
Precise Mobility Intervention for Epidemic Control Using Unobservable Information via Deep Reinforcement Learning
Seaweed: a web application for designing economic games
Hard to Park?: Estimating Parking Difficulty at Scale
FLAP: An End-to-End Event Log Analysis Platform for System Management
End-to-end Learning for Short Text Expansion
Object Detection for Hierarchical Image Classification
Inferring Network Effects from Observational Data
Beyond Traditional Characterizations in the Age of Data: Big Models, Scalable Algorithms, and Meaningful Solutions
Improving the Consistency in Cross-Lingual Cross-Modal Retrieval with 1-to-K Contrastive Learning
Knowledge Enhanced Search Result Diversification
Rapid Image Labeling via Neuro-Symbolic Learning
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis
Harnessing Mobile Phone Social Network Topology to Infer Users Demographic Attributes
Data Science on Blockchains
Self-Supervised Continual Graph Learning via Adaptive Spaced Replay on Node Proxies
Predictive discrete latent factor models for large scale dyadic data
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control
Gmail Smart Compose: Real-Time Assisted Writing
FORA: Simple and Effective Approximate Single-Source Personalized PageRank
Advances in decision tree construction
A Method for Reasoning with Structured and Continuous Attributes in the INLEN-2 Multistrategy Knowledge Discovery System
Deconfounded Recommendation for Alleviating Bias Amplification
Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent
Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs
Deep Bayesian Active Learning for Accelerating Stochastic Simulation
Efficient Attribute Recommendation with Probabilistic Guarantee
Television Discourse Decoded: Comprehensive Multimodal Analytics at Scale
Urban Region Pre-training and Prompting: A Graph-based Approach
Scalable near real-time failure localization of data center networks
Dynamic Graph Segmentation for Deep Graph Neural Networks
The dataminer's guide to scalable mixed-membership and nonparametric bayesian models
Measuring Item Freshness in Data Streams
2nd Workshop on Causal Inference and Machine Learning in Practice
Real-time Attention Based Look-alike Model for Recommender System
Self-Supervised Learning for Graph Dataset Condensation
Golden Path Analyzer: using divide-and-conquer to cluster Web clickstreams
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect
User-centered design of a social game to tag music
Breaking Barriers: A Hands-On Tutorial on AI-Enabled Accessibility to Social Media Content
Clustering spatial data using random walks
Data science through the lens of social science
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction
Temporal Biased Streaming Submodular Optimization
Proceedings of the ACM SIGKDD Workshop on CyberSecurity and Intelligence Informatics, Paris, France, June 28, 2009
Efficient Single-Source SimRank Query by Path Aggregation
Temporal mining for interactive workflow data analysis
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection
LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management
WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences
M3Care: Learning with Missing Modalities in Multimodal Healthcare Data
Using "big data" to solve "small data" problems
Adversarially Robust Submodular Maximization under Knapsack Constraints
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Statistical Models of Top- k Partial Orders
Febrl -: an open source data cleaning, deduplication and record linkage system with a graphical user interface
Fast and Effective GNN Training through Sequences of Random Path Graphs
Breaking the Barrier of Transactions: Mining Inter-Transaction Association Rules
TimeMachine: Timeline Generation for Knowledge-Base Entities
Inductive multi-task learning with multiple view data
The 4th Workshop on AI Agent for Information Retrieval: Generating and Ranking
Improving the Web Usage Analysis Process: A UML Model of the ETL Process
Faster Secure Data Mining via Distributed Homomorphic Encryption
Meta Multi-agent Exercise Recommendation: A Game Application Perspective
Socially-Aware Self-Supervised Tri-Training for Recommendation
Human mobility, social ties, and link prediction
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
Estimating rates of rare events at multiple resolutions
LOGML: Log Markup Language for Web Usage Mining
A Severity Score for Retinopathy of Prematurity
Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask
Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation
Identifying breakpoints in public opinion
Robust multi-task feature learning
A learning framework using Green's function and kernel regularization with application to recommender system
RBG: Hierarchically Solving Large-Scale Routing Problems in Logistic Systems via Reinforcement Learning
Simultaneous optimization of complex mining tasks with a knowledgeable cache
Interactive Paths Embedding for Semantic Proximity Search on Heterogeneous Graphs
Automatically tagging email by leveraging other users' folders
Ranking-based classification of heterogeneous information networks
Cross-media knowledge discovery
Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective
PAMAE: Parallel k -Medoids Clustering with High Accuracy and Efficiency
Quantum Time-index Models with Reservoir for Time Series Forecasting
Topic models with power-law using Pitman-Yor process
Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions
An Automated System for Data Attribute Anomaly Detection
Micro-climate Prediction - Multi Scale Encoder-decoder based Deep Learning Framework
Incremental maintenance of quotient cube for median
Maturity Framework for Enhancing Machine Learning Quality
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), New York City, New York, USA, August 27-31, 1998
Videoviews: A Content Based Video Description Schema and Database Navigation Tool
Mining top-k frequent items in a data stream with flexible sliding windows
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud
Integrating and Mining Distributed Customer Databases
Locally Balancing Signed Graphs
Scalable Top-n Local Outlier Detection
Leveraging Social Context for Modeling Topic Evolution
Building Socially Connected Skilled Teams to Accomplish Complex Tasks
Learning Feature Weights from User Behavior in Content-Based Image Retrieval
Learning Based Proximity Matrix Factorization for Node Embedding
Attention Realignment and Pseudo-Labelling for Interpretable Cross-Lingual Classification of Crisis Tweets
Parallel and Distributed Data Mining: An Introduction
Learning How to Propagate Messages in Graph Neural Networks
A Dynamic Pricing Model for Unifying Programmatic Guarantee and Real-Time Bidding in Display Advertising
Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment
Vamsa: Automated Provenance Tracking in Data Science Scripts
A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams
κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning
Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding
AI for Social Impact: Results from Deployments for Public Health and Conversation
Metric Learning from Probabilistic Labels
Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data
Commonsense-based topic modeling
MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Exceptional Knowledge Discovery in Databases Based on Information Theory