yusuke1997/dblp-id-title huggingface dataset:
Nonparametric hierarchal bayesian modeling in non-contractual heterogeneous survival data
Ensemble-Based Anomaly Detetction using Cooperative Learning
Fast nearest-neighbor search in disk-resident graphs
Co-clustering based classification for out-of-domain documents
Coupled Context Modeling for Deep Chit-Chat: Towards Conversations between Human and Computer
Two approaches to understanding when constraints help clustering
Pre-trained Language Model for Web-scale Retrieval in Baidu Search
Sleuthing for adverse outcomes: Using anomaly detection to identify unusual behaviors of third-party agents
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching
Scalable Active Learning by Approximated Error Reduction
Social media data analysis for revealing collective behaviors
Unifying learning to rank and domain adaptation: enabling cross-task document scoring
Proceedings of EvalRS: A Rounded Evaluation Of Recommender Systems 2023 co-located with 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023), Long Beach,CA, USA, August 7, 2023
Community-based Dynamic Graph Learning for Popularity Prediction
TSPRank: Bridging Pairwise and Listwise Methods with a Bilinear Travelling Salesman Model
QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
Generating succinct titles for web URLs
Diversifying Restricted Boltzmann Machine for Document Modeling
Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms
Few-shot Learning for Trajectory-based Mobile Game Cheating Detection
Causal Relationship Prediction with Continuous Additive Noise Models
Online Fairness Auditing through Iterative Refinement
Modeling Truth Existence in Truth Discovery
A Fast Computer Intrusion Detection Algorithm Based on Hypothesis Testing of Command Transition Probabilities
LightPath: Lightweight and Scalable Path Representation Learning
Dynamic Bike Reposition: A Spatio-Temporal Reinforcement Learning Approach
Hierarchical model-based clustering of large datasets through fractionation and refractionation
CLARE: A Semi-supervised Community Detection Algorithm
Adversarial Attacks on Deep Models for Financial Transaction Records
Proactive workflow modeling by stochastic processes with application to healthcare operation and management
IPOC: An Adaptive Interval Prediction Model based on Online Chasing and Conformal Inference for Large-Scale Systems
Grouped graphical Granger modeling methods for temporal causal modeling
Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints
G2NET: A General Geography-Aware Representation Network for Hotel Search Ranking
Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, ADKDD 2014, August 24, 2014, New York City, New York, USA
Privacy-Preserving Distributed Multi-Task Learning with Asynchronous Updates
Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods
Bypass rates: reducing query abandonment using negative inferences
Cultivating Human Expertise Through AI-Assisted Data Science
Optimal Reserve Price for Online Ads Trading Based on Inventory Identification
Why Does Bagging Work? A Bayesian Account and its Implications
Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute
On Big Data Learning for Small Data Problems
Data-Efficient and Interpretable Tabular Anomaly Detection
Money Never Sleeps: Maximizing Liquidity Mining Yields in Decentralized Finance
Generalized component analysis for text with heterogeneous attributes
BTS: A Comprehensive Benchmark for Tie Strength Prediction
A Message Passing Neural Network Space for Better Capturing Data-dependent Receptive Fields
Fair Multilingual Vandalism Detection System for Wikipedia
Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning
Learning to Discover Causes of Traffic Congestion with Limited Labeled Data
A Collaborative Learning Framework to Tag Refinement for Points of Interest
LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity
Virus Propagation in Multiple Profile Networks
2nd International Workshop on Data Quality Assessment for Machine Learning
FreeSpan: frequent pattern-projected sequential pattern mining
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks
Induction of Condensed Determinations
Inverted matrix: efficient discovery of frequent items in large datasets in the context of interactive mining
Local Homophily-Aware Graph Neural Network with Adaptive Polynomial Filters for Scalable Graph Anomaly Detection
Available Technology for Discovering Causal Models, Building Bayes Nets, and Selecting Predictors: The TETRAD II Program
Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls"
Model selection in markovian processes
Using General Impressions to Analyze Discovered Classification Rules
Data intensive analysis on the gordon high performance data and compute system
Personalized Attraction Enhanced Sponsored Search with Multi-task Learning
CoRGi: Content-Rich Graph Neural Networks with Attention
Analysing Binary Associations
Visualization of navigation patterns on a Web site using model-based clustering
Attribution Modeling Increases Efficiency of Bidding in Display Advertising
Multi-task copula by sparse graph regression
Contrastive Learning with Complex Heterogeneity
Mind the Gap: Delayed Label Bias-Variance Tradeoffs in Predicting Likelihood of Nonpayment
Overlapping decomposition for causal graphical modeling
Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection
WHEN: A Wavelet-DTW Hybrid Attention Network for Heterogeneous Time Series Analysis
Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation
Mining Persistent Activity in Continually Evolving Networks
Empirical glitch explanations
Algorithms for estimating relative importance in networks
Avoiding the crowds: understanding Tube station congestion patterns from trip data
Reconstructing Graph Diffusion History from a Single Snapshot
KRATOS: Context-Aware Cell Type Classification and Interpretation using Joint Dimensionality Reduction and Clustering
Smarter outlier detection and deeper understanding of large-scale taxi trip records: a case study of NYC
Data Mining, the Internet, and Privacy
An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images
Fast discovery of unexpected patterns in data, relative to a Bayesian network
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations
StockAssIstant: A Stock AI Assistant for Reliability Modeling of Stock Comments
Three Principles of Data Science: Predictability, Stability and Computability
DI-2022: The Third Document Intelligence Workshop
Generative Pretrained Hierarchical Transformer for Time Series Forecasting
On formal models for social verification
A game theoretic framework for heterogenous information network clustering
Early detection of insider trading in option markets
Label Learning Method Based on Tensor Projection
NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs
NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching
EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments
POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning
MediaRank: Computational Ranking of Online News Sources
Temporal Restoration and Spatial Rewiring for Source-Free Multivariate Time Series Domain Adaptation
GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems
PolyAnalyst - A Machine Discovery System Inferring Functional Programs
MIX: Multi-Channel Information Crossing for Text Matching
Combining email models for false positive reduction
8th Workshop on Machine Learning in Finance
Attention based Multi-Modal New Product Sales Time-series Forecasting
A Visual Dialog Augmented Interactive Recommender System
Exploiting Visualization in Knowledge Discovery
An Efficient Diffusion-based Non-Autoregressive Solver for Traveling Salesman Problem
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
Scalable Rule Lists Learning with Sampling
STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning
ESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare
Modeling Dual Period-Varying Preferences for Takeaway Recommendation
Detecting Interference using Dyadic Data in Online Controlled Experiments
A Multiple Test Correction for Streams and Cascades of Statistical Hypothesis Tests
Information Mining Platforms: An Infrastructure for KDD Rapid Deployment
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search
Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation
Unifying dependent clustering and disparate clustering for non-homogeneous data
The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013
Applying Vision Based Predictive Modelling for Rapid Characterization of Shape Memory Polymer
Inferring the Strength of Social Ties: A Community-Driven Approach
User browsing models: relevance versus examination
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Safe Learning in Robotics
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
Community membership identification from small seed sets
Detecting Change in Categorical Data: Mining Contrast Sets
Rotative Factorization Machines
Embedding-Driven Multi-Dimensional Topic Mining and Text Analysis
Data, predictions, and decisions in support of people and society
Causal Meta-Mediation Analysis: Inferring Dose-Response Function From Summary Statistics of Many Randomized Experiments
Discovering urban spatial-temporal structure from human activity patterns
Mixing Time Matters: Accelerating Effective Resistance Estimation via Bidirectional Method
BagMinHash - Minwise Hashing Algorithm for Weighted Sets
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems
Data Science at Visa
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank
Return of the AI: An Analysis of Legal Research on Artificial Intelligence using Topic Modeling
RL4CO: An Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
Acoustic Measures for Real-Time Voice Coaching
Integrating Web Conceptual Modeling and Web Usage Mining
Optimizing Case-Based Reasoning System for Functional Test Script Generation with Large Language Models
CloseGraph: mining closed frequent graph patterns
Building Near Realtime Contextual Recommendations for Active Communities on LinkedIn
Key lessons learned building recommender systems for large-scale social networks
Similarity measure based on partial information of time series
Towards Collaborative Fairness in Federated Learning Under Imbalanced Covariate Shift
Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data
Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining
Enhancing the lift under budget constraints: an application in the mutual fund industry
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs
MineSet: An Integrated System for Data Mining
Path-Specific Counterfactual Fairness for Recommender Systems
FASER: Seismic Phase Identifier for Automated Monitoring
Mining for proposal reviewers: lessons learned at the national science foundation
Machine learning for stock selection
Flow Matching for Collaborative Filtering
MISP: A Multimodal-based Intelligent Server Failure Prediction Model for Cloud Computing Systems
CAPRI: a tool for mining complex line patterns in large log data
R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language Models
Model order selection for boolean matrix factorization
Grale: Designing Networks for Graph Learning
Farming the Web for Systematic Business Intelligence (Invited talk, Abstract only)
Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams
BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learning
Neural Instant Search for Music and Podcast
Hierarchical Reinforcement Learning for Scarce Medical Resource Allocation with Imperfect Information
RGVisNet: A Hybrid Retrieval-Generation Neural Framework Towards Automatic Data Visualization Generation
Combinatorial Black-Box Optimization with Expert Advice
Mining complex power networks for blackout prevention
Focused clustering and outlier detection in large attributed graphs
Using randomized response techniques for privacy-preserving data mining
Protecting location privacy using location semantics
Coupled Variational Recurrent Collaborative Filtering
On the identification of intra-seasonal changes in the Indian summer monsoon
Semi-Supervised Deep Learning for Multiplex Networks
Addressing Bias and Fairness in Machine Learning: A Practical Guide and Hands-on Tutorial
MapEmbed: Perfect Hashing with High Load Factor and Fast Update
Designing Policy Recommendations to Reduce Home Abandonment in Mexico
Predicting COVID-19 Spread from Large-Scale Mobility Data
Visually mining and monitoring massive time series
DimCL: Dimension-Aware Augmentation in Contrastive Learning for Recommendation
BE3R: BERT based Early-Exit Using Expert Routing
Text Is All You Need: Learning Language Representations for Sequential Recommendation
Rumor Detection with Diverse Counterfactual Evidence
Adversarial Attacks and Defenses: Frontiers, Advances and Practice
A Customizable Behavior Model for Temporal Prediction of Web User Sequences
Exponential random graph estimation under differential privacy
Pest Management In Cotton Farms: An AI-System Case Study from the Global South
An Empirical Analysis of Backward Compatibility in Machine Learning Systems
Predicting rare classes: can boosting make any weak learner strong?
Design of a temporal geosocial semantic web for military stabilization and reconstruction operations
Homogeneous Discoveries Contain No Surprises: Inferring Risk Profiles from Large Databases
Neural Retrievers are Biased Towards LLM-Generated Content
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal Discovery
Scaling Up Inductive Algorithms: An Overview
Psychological advertising: exploring user psychology for click prediction in sponsored search
LUDIA: an aggregate-constrained low-rank reconstruction algorithm to leverage publicly released health data
Calibrated Multi-Task Learning
Constraint programming for itemset mining
Proceedings of the 5th international workshop on Bioinformatics, BIOKDD 2005, Chicago, Illinois, USA, August 21, 2005
Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing
Multi-modal Time Series Analysis: A Tutorial and Survey
Game Action Modeling for Fine Grained Analyses of Player Behavior in Multi-player Card Games (Rummy as Case Study)
Interpreting Internal Activation Patterns in Deep Temporal Neural Networks by Finding Prototypes
Automatic taxonomy construction from keywords
Cross-Domain Web Information Extraction at Pinterest
Flexible Generation of Preference Data for Recommendation Analysis
"Which half Is wasted?": controlled experiments to measure online-advertising effectiveness
Topical query decomposition
Transfer Learning via Feature Isomorphism Discovery
Knowledge-based data mining
Multi-source domain adaptation and its application to early detection of fatigue
B 2 -Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning
Unsupervised Graph Alignment with Wasserstein Distance Discriminator
Toolkit for Time Series Anomaly Detection
Compressing Convolutional Neural Networks in the Frequency Domain
Fast vertical mining using diffsets
MoodLens: an emoticon-based sentiment analysis system for chinese tweets
Discriminant malware distance learning on structural information for automated malware classification
Self-Organizing wireless sensor networks in action
E-metrics: tomorrow's business metrics today (invited talk, abstract only)
Mining uncertain data with probabilistic guarantees
Personalized Language Model Learning on Text Data Without User Identifiers
Community-based game design: experiments on social games for commonsense data collection
Good-enough brain model: challenges, algorithms and discoveries in multi-subject experiments
An Efficient Framework for Balancing Submodularity and Cost
HGMF: Heterogeneous Graph-based Fusion for Multimodal Data with Incompleteness
Density-based clustering of uncertain data
Serendipitous learning: learning beyond the predefined label space
AutoSmart: An Efficient and Automatic Machine Learning Framework for Temporal Relational Data
Retrieval & Interaction Machine for Tabular Data Prediction
Inferring distant-time location in low-sampling-rate trajectories
Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases
Algorithms for time series knowledge mining
Efficient and Effective Express via Contextual Cooperative Reinforcement Learning
Achieving Non-Discrimination in Data Release
Analytics Journey Map: An Approach Enable to ML at Scale
Density-based spam detector
Normalized Space Alignment: A Versatile Metric for Representation Analysis
Prescriptive PCA: Dimensionality Reduction for Two-stage Stochastic Optimization
Way to Specialist: Closing Loop Between Specialized LLM and Evolving Domain Knowledge Graph
Succinct summarization of transactional databases: an overlapped hyperrectangle scheme
Learning Multivariate Hawkes Process via Graph Recurrent Neural Network
Discrepancy-Aware Graph Mask Auto-Encoder
AIM: Attributing, Interpreting, Mitigating Data Unfairness
Who, where, when and what: discover spatio-temporal topics for twitter users
Mining Subgroups with Exceptional Transition Behavior
Swarm Intelligence in Geo-Localization: A Multi-Agent Large Vision-Language Model Collaborative Framework
Multi-label learning by exploiting label dependency
Towards combining web classification and web information extraction: a case study
Distributing the Stochastic Gradient Sampler for Large-Scale LDA
A structural cluster kernel for learning on graphs
Efficient Data-specific Model Search for Collaborative Filtering
Knowledge vault: a web-scale approach to probabilistic knowledge fusion
Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs
To Tune or Not to Tune?: In Search of Optimal Configurations for Data Analytics
Exploiting duality in summarization with deterministic guarantees
A multinomial clustering model for fast simulation of computer architecture designs
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning
Latent graphical models for quantifying and predicting patent quality
Visualizing high dimensional datasets and multivariate relations (tutorial AM-2)
Multi-Label Inference for Crowdsourcing
Show me the money!: deriving the pricing power of product features by mining consumer reviews
An Open and Large-Scale Dataset for Multi-Modal Climate Change-aware Crop Yield Predictions
EntropyStop: Unsupervised Deep Outlier Detection with Loss Entropy
A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management
Redefining class definitions using constraint-based clustering: an application to remote sensing of the earth's surface
Learning Credible Models
Characterizing the Risk of Atrial Fibrillation in Cardiac Patients with Exceptional Electrocardiogram Phenotypes
Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity
Audience selection for on-line brand advertising: privacy-friendly social network targeting
DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters
BOSS: A Bilateral Occupational-Suitability-Aware Recommender System for Online Recruitment
A Framework for Multi-stage Bonus Allocation in Meal Delivery Platform
PDMC: Generating Feasible Algorithmic Recourse via Perturbation Data Manifold Constraint
A Higher-Order Temporal H-Index for Evolving Networks
Generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems
Long Short Memory Process: Modeling Growth Dynamics of Microscopic Social Connectivity
On the potential of domain literature for clustering and Bayesian network learning
WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points, Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers
Self-Distilled Disentangled Learning for Counterfactual Prediction
Surrogate for Long-Term User Experience in Recommender Systems
Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Efficient Algorithm for the b-Matching Graph
FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks
SAIL: summation-based incremental learning for information-theoretic clustering
AtSNE: Efficient and Robust Visualization on GPU through Hierarchical Optimization
Towards Understanding Link Predictor Generalizability Under Distribution Shifts
Estimating conversion rate in display advertising from past erformance data
Multi-level Mixture of Experts for Multimodal Entity Linking
Assessing Candidate Preference through Web Browsing History
Counterfactual Generative Models for Time-Varying Treatments
Graph Query Reformulation with Diversity
SMA-GNN: A Symbol-Aware Graph Neural Network for Signed Link Prediction in Recommender Systems
SMVC: semi-supervised multi-view clustering in subspace projections
Item selection by "hub-authority" profit ranking
Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature
Exploration and visualization of OLAP cubes with statistical tests
More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data
Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement
Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning
Rule extraction from linear support vector machines
On the Nature of Data Science
KDD 2025 Panel on AI for Science
Among those dark electronic mills: privacy and data mining (invited talk, abstract only)
R 2 SDH: Robust Rotated Supervised Discrete Hashing
Learning Deep Network Representations with Adversarially Regularized Autoencoders
Generative Imputation with Multi-level Causal Consistency for Variable Subset Forecasting
Enhancing Multi-field B2B Cloud Solution Matching via Contrastive Pre-training
Accelerating minor allele frequency computation with graphics processors
Near Real-time Optimization of Activity-based Notifications
2001: A Statistical Odyssey (Invited talk, Abstract only)
24 th International Workshop on Data Mining in Bioinformatics (BIOKDD 2025)
Enhanced Insurance Claim Prediction via Decoupled Graph Neural Networks with Pseudo Labeling
Text Matching Indexers in Taobao Search
Cost Aware Feature Elicitation
SPuManTE: Significant Pattern Mining with Unconditional Testing
Fair Column Subset Selection
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
Customized Regression Model for Airbnb Dynamic Pricing
CovDocker: Benchmarking Covalent Drug Design with Tasks, Datasets, and Solutions