yusuke1997/dblp-id-title huggingface dataset:
Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning
General-Purpose User Embeddings based on Mobile App Usage
Bringing structure to text: mining phrases, entities, topics, and hierarchies
Average Sensitivity of Spectral Clustering
Online phishing classification using adversarial data mining and signaling games
Algorithms for speeding up distance-based outlier detection
Extracting decision trees from trained neural networks
Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units
3rd Workshop on End-End Customer Journey Optimization
A spectral method to separate disconnected and nearly-disconnected web graph components
Developing a Comprehensive Framework for Multimodal Feature Extraction
Proceedings of the 8th Workshop on Social Network Mining and Analysis, New York, NY, USA, August 24, 2014
Temporal-Contextual Recommendation in Real-Time
Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery
A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding
The interplay between dynamics and networks: centrality, communities, and cheeger inequality
Modality-Aware Diffusion Augmentation with Consistent Subspace Disentanglement for Session-based Recommendation
Supporting Employer Name Normalization at both Entity and Cluster Level
Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning
Neural Manifold Operators for Learning the Evolution of Physical Dynamics
A Clustering Algorithm Merging MCMC and EM Methods Using SQL Queries
Unlocking the Value of Privacy: Trading Aggregate Statistics over Private Correlated Data
Language Representation Favored Zero-Shot Cross-Domain Cognitive Diagnosis
Meta-Learned Spatial-Temporal POI Auto-Completion for the Search Engine at Baidu Maps
FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition
Avoiding Biases due to Similarity Assumptions in Node Embeddings
Incorporating Domain Knowledge with Video and Voice Data Analysis in News Broadcasts
Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors
Bidirectional Diffusion Bridge Models
CLOUDS: A Decision Tree Classifier for Large Datasets
Deep Learning to Detect Medical Treatment Fraud
Dynamics of news events and social media reaction
Evidence combination in biomedical natural-language processing
Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction
Learning to predict train wheel failures
Towards a Generic Framework for Mechanism-guided Deep Learning for Manufacturing Applications
The offset tree for learning with partial labels
It's who you know: graph mining using recursive structural features
Scaling multi-class support vector machines using inter-class confusion
Diet Planning with Machine Learning: Teacher-forced REINFORCE for Composition Compliance with Nutrition Enhancement
Diffusion-Guided Diversity for Single Domain Generalization in Time Series Classification
The Missing Indicator Method: From Low to High Dimensions
A Hyper-surface Arrangement Model of Ranking Distributions
Predicting Cascading Failures with a Hyperparametric Diffusion Model
IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics
Computer Vision: Deep Dive into Object Segmentation Approaches
ThermoCast: a cyber-physical forecasting model for datacenters
Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data
Exploring the Urban Region-of-Interest through the Analysis of Online Map Search Queries
A new challenge of information processing under the 21st century
Reducing Exposure to Harmful Content via Graph Rewiring
Labeled Data Generation with Inexact Supervision
Parallel computation of high dimensional robust correlation and covariance matrices
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders
Algebraic visual analysis: the Catalano phone call data set case study
Automatic selection of social media responses to news
ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks
Bridging centrality: graph mining from element level to group level
MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search
Identifying and labeling search tasks via query-based hawkes processes
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
Real Estate Ranking via Mixed Land-use Latent Models
Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings
Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis
Diversified ranking on large graphs: an optimization viewpoint
Multi-space probabilistic sequence modeling
Unsupervised Ranking Ensemble Model for Recommendation
Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning
Interpretable and Steerable Sequence Learning via Prototypes
Knowledge Graph Reasoning and Its Applications
Advances in Mining Heterogeneous Healthcare Data
A privacy preserving framework for managing vehicle data in road pricing systems
REMIX: Automated Exploration for Interactive Outlier Detection
Automated Machine Learning on Graph
A Request-level Guaranteed Delivery Advertising Planning: Forecasting and Allocation
ChemicalX: A Deep Learning Library for Drug Pair Scoring
A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments
Removing Camouflage and Revealing Collusion: Leveraging Gang-crime Pattern in Fraudster Detection
Mining for misconfigured machines in grid systems
Dynamic Structural Clustering Unleashed: Flexible Similarities, Versatile Updates and for All Parameters
Controllable Multi-Behavior Recommendation for In-Game Skins with Large Sequential Model
Efficient kernel feature extraction for massive data sets
Dimensionality Reduction Via Graph Structure Learning
Portraying Collective Spatial Attention in Twitter
Internal Promotion Optimization
Dynamic Hierarchical Classification for Patient Risk-of-Readmission
User effort minimization through adaptive diversification
Extreme States Distribution Decomposition Method for Search Engine Online Evaluation
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Data mining in metric space: an empirical analysis of supervised learning performance criteria
Latent Variable Time-varying Network Inference
Augmenting the generalized hough transform to enable the mining of petroglyphs
A sequential sampling algorithm for a general class of utility criteria
A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009
Adaptive-Halting Policy Network for Early Classification
KDD 2024 Finance Day
Profit-maximizing cluster hires
A Deep Hybrid Model for Weather Forecasting
ScalaGBM: Memory Efficient GBDT Training for High-Dimensional Data on GPU
Estimating Properties of Social Networks via Random Walk considering Private Nodes
Learning to Count Mosquitoes for the Sterile Insect Technique
Knowledge Discovery from Multiple Databases
Profit Maximization for Online Advertising Demand-Side Platforms
Multiple coordinated views supporting visual analytics
A general approach to incorporate data quality matrices into data mining algorithms
Ensembles of Adaptive Model Rules from High-Speed Data Streams
Keynote Speaker: Yolanda Gil
Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals
Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach
A Content Based Video Description Scheme And Video Database Navigator
Capacity Constrained Influence Maximization in Social Networks
Towards Fair Disentangled Online Learning for Changing Environments
Distributed and parallel knowledge discovery (workshop session - title only)
Narrow the Input Mismatch in Deep Graph Neural Network Distillation
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
SEWeP: using site semantics and a taxonomy to enhance the Web personalization process
Spectral Survival Analysis
Acclimatizing taxonomic semantics for hierarchical content classification from semantics to data-driven taxonomy
Medical coding classification by leveraging inter-code relationships
Finding trendsetters in information networks
LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction
FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection
Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
Disentangled Self-Supervision in Sequential Recommenders
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
Large-scale Human Mobility Data Regeneration for Open Urban Research
DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting
Structural Diversity and Homophily: A Study Across More Than One Hundred Big Networks
Model-shared subspace boosting for multi-label classification
How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
Contextual Distillation Model for Diversified Recommendation
False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments
Service Time Prediction for Delivery Tasks via Spatial Meta-Learning
Data-driven study of urban infrastructure to enable city-wide ubiquitous computing
AI for Nature: From Science to Impact
DataMine: Application Programming Interface and Query Language for Database Mining
Why We Twitter: An Analysis of a Microblogging Community
Prospecting the Career Development of Talents: A Survival Analysis Perspective
Beyond streams and graphs: dynamic tensor analysis
Social action tracking via noise tolerant time-varying factor graphs
Towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing
Unified 2D and 3D Pre-Training of Molecular Representations
Graph Neural Processes for Spatio-Temporal Extrapolation
Mining Segment-Wise Periodic Patterns in Time-Related Databases
Mining discriminative subgraphs from global-state networks
Towards Equitable Assignment: Data-Driven Delivery Zone Partition at Last-mile Logistics
An Empirical Test of the Weighted Effect Approach to Generalized Prediction Using Recursive Neural Nets
Beyond Input Attribution: A Hands-On Tutorial to Concept-Based Explainable AI and Mechanistic Interpretability
Recurrent Poisson Factorization for Temporal Recommendation
Challenges and Innovations in Building a Product Knowledge Graph
Internet scale data analysis
Exploiting contexts to deal with uncertainty in classification
Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid
STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation
Synthetic Survey Data Generation and Evaluation
Hypergraph Clustering Based on PageRank
Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing
Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility Data
Automatic identification of quasi-experimental designs for discovering causal knowledge
Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software
A theoretical framework for learning from a pool of disparate data sources
Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models
Electron-Informed Coarse-Graining Molecular Representation Learning for Real-World Molecular Physics
Planet-Scale Land Cover Classification with FPGAs
Leveraging predictive modeling to reduce signal theft in a multi-service organization environment
From Online Behaviors to Offline Retailing
RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment
Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors
Extracting semantics from data cubes using cube transversals and closures
Advances in Web Mining and Web Usage Analysis, 6th International Workshop on Knowledge Discovery on the Web, WebKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers
LitFM: A Retrieval Augmented Structure-aware Foundation Model For Citation Graphs
A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis
Scalable graph clustering using stochastic flows: applications to community discovery
FusionSAM: Visual Multi-Modal Learning with Segment Anything Model
Knowledge-enhanced Black-box Attacks for Recommendations
UFIMT: an uncertain frequent itemset mining toolbox
BGP-lens: patterns and anomalies in internet routing updates
Auto-Keras: An Efficient Neural Architecture Search System
Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
Redundancy-aware maximal cliques
A process-centric data mining and visual analytic tool for exploring complex social networks
Graph Rationalization with Environment-based Augmentations
SlotPi: Physics-informed Object-centric Reasoning Models
ReprBERT: Distilling BERT to an Efficient Representation-Based Relevance Model for E-Commerce
A Unified Solution to Diverse Heterogeneities in One-Shot Federated Learning
Mining eBay: Bidding Strategies and Shill Detection
Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data
Automatic Multi-Task Learning Framework with Neural Architecture Search in Recommendations
Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications
D2K: Scalable Community Detection in Massive Networks via Small-Diameter k-Plexes
Scaling up deep learning
Determination of RNA folding pathway functional intermediates using a massively parallel genetic algorithm (abstract of invited talk)
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
Classification of Edge-dependent Labels of Nodes in Hypergraphs
SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning
RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift
Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance
Software systems through complex networks science: review, analysis and applications
Exploiting Web Log Mining for Web Cache Enhancement
Large Scale Distributed Data Science using Apache Spark
Learning to rank networked entities
Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization
Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks
Robust Task Grouping with Representative Tasks for Clustered Multi-Task Learning
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening
CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
Clustering with relative constraints
Malware detection using statistical analysis of byte-level file content
WeightGrad: Geo-Distributed Data Analysis Using Quantization for Faster Convergence and Better Accuracy
QUINT: On Query-Specific Optimal Networks
Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes
User reputation in a comment rating environment
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction
Relational learning via latent social dimensions
From frequent itemsets to semantically meaningful visual patterns
GRAM: Graph-based Attention Model for Healthcare Representation Learning
Automatic Temporal Relation in Multi-Task Learning
Foreword to the Applied Data Science: Invited Talks Track at KDD-2017
Advancing Tool-Augmented Large Language Models via Meta-Verification and Reflection Learning
Benchmarking Fraud Detectors on Private Graph Data
Redescription Model Mining
The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare
Integrating low-rank and group-sparse structures for robust multi-task learning
Item-Difficulty-Aware Learning Path Recommendation: From a Real Walking Perspective
Extensibility in Data Mining Systems
DARE to Diversify: DAta Driven and Diverse LLM REd Teaming
19th International Workshop on Mining and Learning with Graphs (MLG)
An iterative method for multi-class cost-sensitive learning
Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping
Gram-Schmidt Kernels Applied to Structure Activity Analysis for Drug Design
Sequential Learning Algorithms for Contextual Model-Free Influence Maximization
ReCDA: Concept Drift Adaptation with Representation Enhancement for Network Intrusion Detection
DDCDR: A Disentangle-based Distillation Framework for Cross-Domain Recommendation
Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems
TATC: Predicting Alzheimer's Disease with Actigraphy Data
NL2Code-Reasoning and Planning with LLMs for Code Development
A Collaborative Transfer Learning Framework for Cross-domain Recommendation
Sentiment analysis of blogs by combining lexical knowledge with text classification
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization Approach
Doctor Specific Tag Recommendation for Online Medical Record Management
Deep Distributed Fusion Network for Air Quality Prediction
Luck is Hard to Beat: The Difficulty of Sports Prediction
Suggesting friends using the implicit social graph
Entity categorization over large document collections
Anomaly Detection with Robust Deep Autoencoders
Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder
Statistical entity-topic models
AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System
Improving Long-tail User CTR Prediction via Hierarchical Distribution Alignment
Using data mining techniques to address critical information exchange needs in disaster affected public-private networks
Time series similarity measures (tutorial PM-2)
NL2SQL-BUGs: A Benchmark for Detecting Semantic Errors in NL2SQL Translation
Shapley Value-driven Data Pruning for Recommender Systems
Spatially regularized logistic regression for disease mapping on large moving populations
Combining predictions for accurate recommender systems
Diversity and Inclusion, a Perspective from a Four Years MSI Faculty Member
Improving discriminative sequential learning with rare--but--important associations
Revolutionizing Database Q&A with Large Language Models: Comprehensive Benchmark and Evaluation
REST: A Reference-based Framework for Spatio-temporal Trajectory Compression
Training Industry-scale GNNs with GiGL
AI and Science Day
Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising
Big Data System for Analyzing Risky Procurement Entities
A general bootstrap performance diagnostic
Scalable frequent-pattern mining methods: an overview
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data
A framework for specifying explicit bias for revision of approximate information extraction rules
Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages
TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation
Online multiple kernel regression
Proceedings of the ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2001)
DDR: Dialogue Based Doctor Recommendation for Online Medical Service
Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise
Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management
How Can Computer Science Education Address Inequities
Dual-Head Knowledge Distillation: Enhancing Logits Utilization with an Auxiliary Head
DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering
Benefits of bias: towards better characterization of network sampling
High density-focused uncertainty sampling for active learning over evolving stream data
Learning Balanced Tree Indexes for Large-Scale Vector Retrieval
A Fully Differentiable Set Autoencoder
Exploration mining in diabetic patients databases: findings and conclusions
A Database Interface for Clustering in Large Spatial Databases
Discrete Content-aware Matrix Factorization
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?
Repeat-Aware Neighbor Sampling for Dynamic Graph Learning
An Efficient Subgraph GNN with Provable Substructure Counting Power
Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data
Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Ensemble pruning via individual contribution ordering
A kernel fused perceptron for the online classification of large-scale data
Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs
Gradual AutoML using Lale
Lessons Learned from Developing and Deploying a Large-Scale Employer Name Normalization System for Online Recruitment
Malstone: towards a benchmark for analytics on large data clouds
Reduction of ground-based sensor sites for spatio-temporal analysis of aerosols
Social influence analysis in large-scale networks
MEDTO: Medical Data to Ontology Matching Using Hybrid Graph Neural Networks
Discovering missing links in Wikipedia
Density-based logistic regression
The untold story of the clones: content-agnostic factors that impact YouTube video popularity
Opinion Dynamics with Varying Susceptibility to Persuasion
Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care
AdaRD: An Adaptive Response Denoising Framework for Robust Learner Modeling
ErrorEraser: Unlearning Data Bias for Improved Continual Learning
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Algorithms for Characterization and Trend Detection in Spatial Databases
Ranking-based name matching for author disambiguation in bibliographic data
Using hierarchical clustering for learning theontologies used in recommendation systems
Online heterogeneous mixture modeling with marginal and copula selection
DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows
Uncertainty-Aware Reliable Text Classification
Heuristic approaches for time-lagged biclustering
Mining data from mobile devices: a survey of smart sensing and analytics
On Subjective Measures of Interestingness in Knowledge Discovery
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution
Accurate decision trees for mining high-speed data streams
Data mining to detect abnormal behavior in aerospace data
Integrating spreadsheet data via accurate and low-effort extraction
Weighting versus pruning in rule validation for detecting network and host anomalies
Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization
Scalable Graph Embeddings via Sparse Transpose Proximities
Partial Pre-Post Code Tree: A Memory-Efficient Tree Structure for Conjunctive Rule Mining
Inferring social roles and statuses in social networks
Adversarial Variational Embedding for Robust Semi-supervised Learning
Mining images on semantics via statistical learning
Exact sparse recovery with L0 projections
ASTNet: Asynchronous Spatio-Temporal Network for Large-Scale Chemical Sensor Forecasting