yusuke1997/dblp-id-title huggingface dataset:
Health Day: Building Health AI Ecosystem: From Data Harmonization to Knowledge Discovery
Machine Learning for Encrypted Malware Traffic Classification: Accounting for Noisy Labels and Non-Stationarity
Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering
Using strong triadic closure to characterize ties in social networks
GraphScope: parameter-free mining of large time-evolving graphs
Knowledge Graph Self-Supervised Rationalization for Recommendation
Improving Deep Learning for Airbnb Search
PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions
Beyond myopic inference in big data pipelines
PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network
Graph Neural Network Training and Data Tiering
Empirical Bayes Selection for Value Maximization
DV365: Extremely Long User History Modeling at Instagram
SCode: A Spherical Code Metric Learning Approach to Continuously Monitoring Predictive Events in Networked Data
Building an engine for big data
Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion
Smoothed Dilated Convolutions for Improved Dense Prediction
Mining, indexing, and querying historical spatiotemporal data
Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing
CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation
Advances in Exploratory Data Analysis, Visualisation and Quality for Data Centric AI Systems
Learning to Generate Rock Descriptions from Multivariate Well Logs with Hierarchical Attention
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Spatiotemporal Neighborhood Discovery for Sensor Data
Preventing Rhino Poaching through Machine Learning
Building connected neighborhood graphs for isometric data embedding
From Labels to Decisions: A Mapping-Aware Annotator Model
The Secret Lives of Names?: Name Embeddings from Social Media
NonStop SQL/MX Primitives for Knowledge Discovery
Fast Query of Biharmonic Distance in Networks
An Efficient White-box LLM Watermarking for IP Protection on Online Market Platforms
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
Digital Preservation and Curation of Self-Tracking Data: A Position Paper
Addressing Non-Representative Surveys using Multiple Instance Learning
Optimizing Peer Learning in Online Groups with Affinities
Lytic: synthesizing high-dimensional algorithmic analysis with domain-agnostic, faceted visual analytics
Stackelberg games for adversarial prediction problems
Mining Indirect Associations in Web Data
Knowledge Discovery in Textual Databases (KDT)
Fast approximate similarity search based on degree-reduced neighborhood graphs
Correlation clustering: from theory to practice
Finding simple intensity descriptions from event sequence data
Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks
Data mining in the online services industry
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems
Multi-View Clustering for Open Knowledge Base Canonicalization
Joint Policy-Value Learning for Recommendation
A transfer learning based framework of crowd-selection on twitter
SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations
Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising
Multi-fidelity Hierarchical Neural Processes
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
HICF: Hyperbolic Informative Collaborative Filtering
Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change
Analysis and identification of spamming behaviors in Sina Weibo microblog
ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation
Optimal Allocation of Real-Time-Bidding and Direct Campaigns
Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks
Differentially private network data release via structural inference
Nearest-Biclusters Collaborative Filtering with Constant Values
Evaluation of Causal Structure Learning Methods on Mixed Data Types
A framework for analysis of dynamic social networks
Spatial-temporal causal modeling for climate change attribution
Experimental comparison of scalable online ad serving
Multi-objective Optimization of Notifications Using Offline Reinforcement Learning
Clustering moving objects
Hardening soft information sources
Connections between the lines: augmenting social networks with text
Distributional Prototype Learning for Out-of-distribution Detection
Supervised probabilistic principal component analysis
Spectral domain-transfer learning
Graph Representation Learning: Foundations, Methods, Applications and Systems
IU4Rec: Interest Unit-Based Product Organization and Recommendation for E-Commerce Platform
FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
KDD Health Day 2025: Harnessing AI Opportunities in Biomedicine and Healthcare
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006
Comparing International Development Patterns Using Multi-Operator Learning and Discovery Tools
Open-Domain Aspect-Opinion Co-Mining with Double-Layer Span Extraction
FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction
COSSUM: Towards Conversation-Oriented Structured Summarization for Automatic Medical Insurance Assessment
HiGPT: Heterogeneous Graph Language Model
Towards time-aware link prediction in evolving social networks
Discovering the set of fundamental rule changes
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Quakefinder: A Scalable Data Mining System for Detecting Earthquakes from Space
The Illusion of Inclusion: Large Scale Genomic Data Sovereignty and Indigenous Populations
Simultaneous Urban Region Function Discovery and Popularity Estimation via an Infinite Urbanization Process Model
FRNet: Frequency-based Rotation Network for Long-term Time Series Forecasting
Finding Repeated Structures in Time Series: Algorithms and Applications: A Unifying View of Time Series Motifs/Shapelets/Chains and Similar Primitives
Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning
AffinityTune: A Prompt-Tuning Framework for Few-Shot Anomaly Detection on Graphs
Mining templates from search result records of search engines
CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research
Towards a Benchmark for Knowledge Base Exchange
Efficient Similar Region Search with Deep Metric Learning
Discovering word senses from text
A Dual-Agent Scheduler for Distributed Deep Learning Jobs on Public Cloud via Reinforcement Learning
Efficient Approximation Algorithms for Spanning Centrality
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer
Representing Discovered Patterns Using Attributed Hypergraph
Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation
A Guide to Misinformation Detection Data and Evaluation
Earth Observations from a New Generation of Geostationary Satellites
Learning Prosodic Patterns for Mandarin Speech Synthesis
Guilt by association: large scale malware detection by mining file-relation graphs
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration, Paris, France, June 28, 2009
Fair Set Cover
ShapleyFL: Robust Federated Learning Based on Shapley Value
Proposal and Empirical Comparison of a Parallelizable Distance-Based Discretization Method
All You Need to Know to Build a Product Knowledge Graph
Cryptographically private support vector machines
Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning
EcoVal: An Efficient Data Valuation Framework for Machine Learning
A hybrid unsupervised approach for document clustering
Diffusion Models for Recommender Systems: From Content Distribution To Content Creation
Improving quality control by early prediction of manufacturing outcomes
Bayesian Inference for Identifying Solar Active Regions
Recent Advances in Multimodal Educational Data Mining in K-12 Education
Influence Maximization via Graph Neural Bandits
Efficient Centrality Maximization with Rademacher Averages
Classifying Multimodal Data Using Transformers
Kam1n0: MapReduce-based Assembly Clone Search for Reverse Engineering
DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems
Precision Health in the Age of Large Language Models
Towards subspace clustering on dynamic data: an incremental version of PreDeCon
Binned Kernels for Anomaly Detection in Multi-timescale Data using Gaussian Processes
Relevant overlapping subspace clusters on categorical data
Identifying non-actionable association rules
Tail-GNN: Tail-Node Graph Neural Networks
Similarity Preserving Adversarial Graph Contrastive Learning
The recommender problem revisited: morning tutorial
Spotlighting Anomalies using Frequent Patterns
Inferring Hierarchical Clustering Structures by Deterministic Annealing
Bayesian Stream Tuner: Dynamic Hyperparameter Optimization for Real-Time Data Streams
Mining phenotypes and informative genes from gene expression data
epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery
TaxoTrans: Taxonomy-Guided Entity Translation
Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation
Generative Retrieval for Book Search
Bootstrapped language identification for multi-site internet domains
MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting
Boosting Bot Detection via Heterophily-Aware Representation Learning and Prototype-Guided Cluster Discovery
Towards Mitigating the Class-Imbalance Problem for Partial Label Learning
Minimizing Localized Ratio Cut Objectives in Hypergraphs
MARAS: Signaling Multi-Drug Adverse Reactions
Semi-supervised sparse metric learning using alternating linearization optimization
Graph sample and hold: a framework for big-graph analytics
Analysis of an associative memory neural network for pattern identification in gene expression data
Knowledge = Concepts: A Harmful Equation
Hypertext data mining (tutorial AM-1)
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model
Link Prediction with Signed Latent Factors in Signed Social Networks
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles
Discovery of climate indices using clustering
Integrating Inductive and Deductive Reasoning for Database Mining
GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications
Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale
False Positives in A/B Tests
Mining Graphs and Networks: A 15-Year Journey
Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications
Order Fulfillment Cycle Time Estimation for On-Demand Food Delivery
Separated Trust Regions Policy Optimization Method
Treatment Effect Estimation with Adjustment Feature Selection
Medical Dialogue Response Generation with Pivotal Information Recalling
Communication Dynamics of Blog Networks
EpiDeep: Exploiting Embeddings for Epidemic Forecasting
Large-Scale Training Framework for Video Annotation
ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering
CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis
Finding similar files in large document repositories
Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask
Spatio-temporal Diffusion Point Processes
CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation
Enhancing semi-supervised clustering: a feature projection perspective
YALE: rapid prototyping for complex data mining tasks
Estimating Individualized Causal Effect with Confounded Instruments
Empirical comparisons of various voting methods in bagging
Data Scientists and Designers Can Create The Jobs of The Future
Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases
Query Workloads for Data Series Indexes
CACTUS - Clustering Categorical Data Using Summaries
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs
Spatial Heterophily Aware Graph Neural Networks
Scalable Betweenness Centrality Maximization via Sampling
Layer-Wise Adaptive Gradient Norm Penalizing Method for Efficient and Accurate Deep Learning
On demand classification of data streams
Deep Censored Learning of the Winning Price in the Real Time Bidding
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions
Enhancing SVMs with Problem Context Aware Pipeline
Continual Collaborative Distillation for Recommender System
Efficient Frequent Directions Algorithm for Sparse Matrices
Coordinated clustering algorithms to support charging infrastructure design for electric vehicles
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Local Latent Space Models for Top-N Recommendation
Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification
iPinYou Global RTB Bidding Algorithm Competition Dataset
Robust Decision Trees: Removing Outliers from Databases
Advancing Confidence Calibration and Quantification in Medication Recommendation
Fast Enumeration of Large k-Plexes
Finding Frequent Substructures in Chemical Compounds
Interactive visual analytics for high dimensional data
A Hierarchical and Disentangling Interest Learning Framework for Unbiased and True News Recommendation
The 5th International Workshop on Talent and Management Computing (TMC'2024)
Catching the drift: learning broad matches from clickthrough data
Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks
Fairness in Recommendation Ranking through Pairwise Comparisons
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition
Stabilizing Voltage in Power Distribution Networks via Multi-Agent Reinforcement Learning with Transformer
A Unified Core Structure in Multiplex Networks: From Finding the Densest Subgraph to Modeling User Engagement
Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning
Nestedness and segmented nestedness
JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu
A spectral clustering approach to optimally combining numericalvectors with a modular network
SVM selective sampling for ranking with application to data retrieval
Discriminative vs Informative Learning
KDD 2023 Workshop on Data Science and AI for Sports
Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce
Conditional Random Field Enhanced Graph Convolutional Neural Networks
An integrated data mining approach to real-time clinical monitoring and deterioration warning
Where to wait for a taxi?
Social Network Mining with Nonparametric Relational Models
Cross-Species Insights: Transforming Drug Efficacy from Rats to Humans Using Tissue-Specific Generative Models
CAPTCHA-based image labeling on the Soylent Grid
Graph Data Condensation via Self-expressive Graph Structure Reconstruction
Scalable Heterogeneous Graph Neural Networks for Predicting High-potential Early-stage Startups
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank
Efficient Bitruss Decomposition without Butterfly Enumeration
Workload-aware anonymization
DGI: An Easy and Efficient Framework for GNN Model Evaluation
Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality
Fast euclidean minimum spanning tree: algorithm, analysis, and applications
Classification and visualization for high-dimensional data
Conformal Counterfactual Inference under Hidden Confounding
Know, Grow, and Protect Net Worth: Using ML for Asset Protection by Preventing Overdraft Fees
Killing Two Birds with One Stone: Cross-modal Reinforced Prompting for Graph and Language Tasks
NewsEmbed: Modeling News through Pre-trained Document Representations
Data-driven multi-touch attribution models
PipeRAG: Fast Retrieval-Augmented Generation via Adaptive Pipeline Parallelism
Regression error characteristic surfaces
Statistical learning from relational data
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009
Indirect Invisible Poisoning Attacks on Domain Adaptation
CompactETA: A Fast Inference System for Travel Time Prediction
PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information
Workshop on Online and Adaptative Recommender Systems (OARS)
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, Nevada, USA, August 24-27, 2008
Unified Point-of-Interest Recommendation with Temporal Interval Assessment
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler
Accelerating large-scale data mining using in-database analytics
DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection
Global Interpretable Graph-level Anomaly Detection via Prototype
A Scalable and Efficient Signal Integration System for Job Matching
Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation
CommerceMM: Large-Scale Commerce MultiModal Representation Learning with Omni Retrieval
Database Mining in the Architecture of a Semantic Preprocessor for State Aware Query Optimization
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage
Effective and Real-time In-App Activity Analysis in Encrypted Internet Traffic Streams
Overview of the 1st Workshop on City Brain Research
Embedding Temporal Network via Neighborhood Formation
RSC: Mining and Modeling Temporal Activity in Social Media
Interactive Path Reasoning on Graph for Conversational Recommendation
Rax: Composable Learning-to-Rank Using JAX
Proceedings of the Tenth International Workshop on Data Mining in Bioinformatics, BIOKDD '11, San Diego, California, USA, August 21, 2011
SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation
GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network
From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams
Segmentation-based modeling for advanced targeted marketing
GELL: Automatic Extraction of Epidemiological Line Lists from Open Sources
Predicting Equity Returns from Securities Data with Minimal Rule Generation
Entity resolution for big data
Structured and Unstructured Induction with EDAGs
Deep Learning on Graphs: Methods and Applications (DLG-KDD2023)
Para-Pred: Addressing Heterogeneity for City-Wide Indoor Status Estimation in On-Demand Delivery
International Workshop on Online and Adaptive Recommender Systems (OARS 2025)
Knowledge-Guided Efficient Representation Learning for Biomedical Domain
A Visual Tour of Bias Mitigation Techniques for Word Representations
Optimal Distributed Submodular Optimization via Sketching
Application of kernels to link analysis
VideoConviction: A Multimodal Benchmark for Human Conviction and Stock Market Recommendations
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems
Learning from data with uncertain labels by boosting credal classifiers
Revisiting kd-tree for Nearest Neighbor Search
Parallel rough set based knowledge acquisition using MapReduce from big data
Interacting viruses in networks: can both survive?
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks
Scalable Multidimensional Hierarchical Bayesian Modeling on Spark
Improving Protein Function Annotation via Unsupervised Pre-training: Robustness, Efficiency, and Insights
Maximally informative k-itemsets and their efficient discovery
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), Newport Beach, California, USA, August 14-17, 1997
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling
Summarizing itemset patterns: a profile-based approach
Exploiting place features in link prediction on location-based social networks
Meta Clustering of Neural Bandits
WavingSketch: An Unbiased and Generic Sketch for Finding Top-k Items in Data Streams
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation
FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning
Correlation search in graph databases
Online Drift Detection with Maximum Concept Discrepancy
Parallel Halo Finding in N-Body Cosmology Simulations
Resource and Knowledge Discovery in Global Information Systems: A Preliminary Design and Experiment
Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding
The KDD 2021 Workshop on Causal Discovery, CD@KDD 2021, Singapore, August 15, 2021
Neural Insights for Digital Marketing Content Design
Learning for Counterfactual Fairness from Observational Data
Conditional Logical Message Passing Transformer for Complex Query Answering
Depth-Adaptive Graph Neural Networks via Learnable Bakry-Émery Curvature
Efficient Global String Kernel with Random Features: Beyond Counting Substructures
Orthogonal nonnegative matrix t-factorizations for clustering
Data Efficient Learning on Graphs
Challenges in KDD and ML for Sustainable Development
Scalable Temporal Motif Densest Subnetwork Discovery
Mining rich session context to improve web search
GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning
Correlating events with time series for incident diagnosis
Robust information-theoretic clustering
Counterfactual Explanations in Explainable AI: A Tutorial
1st Workshop on End-End Customer Journey Optimization
Enhancing Predictive Modeling of Nested Spatial Data through Group-Level Feature Disaggregation
Spotting out emerging artists using geo-aware analysis of P2P query strings
Sampling minimal frequent boolean (DNF) patterns
Locating secret messages in images
Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery
Machine Learning and Causal Inference for Policy Evaluation
Intention oriented itinerary recommendation by bridging physical trajectories and online social networks
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021)
Fast window correlations over uncooperative time series
Knowledge Discovery in RNA Sequence Families of HIV Using Scalable Computers
A Unified Framework for Marketing Budget Allocation
K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters
Discovering significant rules
Learning dynamic temporal graphs for oil-production equipment monitoring system
Detecting graph-based spatial outliers: algorithms and applications (a summary of results)
Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors
Managing Diversity in Airbnb Search
NGUARD: A Game Bot Detection Framework for NetEase MMORPGs
Practical collapsed variational bayes inference for hierarchical dirichlet process
The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach
Tripartite Vector Representations for Better Job Recommendation
Tracking trends: incorporating term volume into temporal topic models
PROXIMUS: a framework for analyzing very high dimensional discrete-attributed datasets
Navigating information facets on twitter (NIF-T)
Towards scalable critical alert mining