yusuke1997/dblp-id-title huggingface dataset:
Sub-Matrix Factorization for Real-Time Vote Prediction
Fast discovery of connection subgraphs
Generative Auto-bidding via Conditional Diffusion Modeling
Learning semantics-preserving distance metrics for clustering graphical data
From Online to Non-i.i.d. Batch Learning
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
Kernel Ridge Regression-Based Graph Dataset Distillation
Robust Treecode Approximation for Kernel Machines
Siren: an interactive tool for mining and visualizing geospatial redescriptions
Using predictive analysis to improve invoice-to-cash collection
Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning
Efficient Coreset Selection with Cluster-based Methods
Eliminating noisy information in Web pages for data mining
Knowledge Discovery in Telecommunication Services Data Using Bayesian Network Models
Fast DTT: a near linear algorithm for decomposing a tensor into factor tensors
Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges
Spectral Clustering in Social Networks
Representation Learning for Attributed Multiplex Heterogeneous Network
Tell me what i need to know: succinctly summarizing data with itemsets
ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems
Mining Multimedia and Complex Data, KDD Workshop MDM/KDD 2002, PAKDD Workshop KDMCD 2002, Revised Papers
On Structural Expressive Power of Graph Transformers
Efficient Specific-to-General Rule Induction
Methods for ordinal peer grading
A User-Centered Concept Mining System for Query and Document Understanding at Tencent
Approximate Graph Propagation
Lossless Set Compression by Binary Tree Coding
TIES: Temporal Interaction Embeddings for Enhancing Social Media Integrity at Facebook
Fast mining of spatial collocations
Delivery Scope: A New Way of Restaurant Retrieval for On-demand Food Delivery Service
Understanding Content Reuse on the Web: Static and Dynamic Analyses
Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare
MAML-en-LLM: Model Agnostic Meta-Training of LLMs for Improved In-Context Learning
DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
Data Quality for Machine Learning Tasks
Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation
High-precision phrase-based document classification on a modern scale
How to use Graph Data in the Wild to Help Graph Anomaly Detection?
Failure detection and localization in component based systems by online tracking
Optimized Cost per Click in Taobao Display Advertising
REDEEMing Modality Information Loss: Retrieval-Guided Conditional Generation for Severely Modality Missing Learning
Community evolution in dynamic multi-mode networks
NodeImport: Imbalanced Node Classification with Node Importance Assessment
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods
Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning
Reinforcement Learning Enhances the Experts: Large-scale COVID-19 Vaccine Allocation with Multi-factor Contact Network
Arbitrary-Order Proximity Preserved Network Embedding
Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability
Assessing The Factual Accuracy of Generated Text
Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, CD@KDD 2019, Anchorage, Alaska, USA, August 5, 2019
FBLG: a simple and effective approach for temporal dependence discovery from time series data
Easy Perturbation EEG Algorithm for Spectral Importance (easyPEASI): A Simple Method to Identify Important Spectral Features of EEG in Deep Learning Models
Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection
Class-incremental Learning for Time Series: Benchmark and Evaluation
Query chains: learning to rank from implicit feedback
Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding
VRDU: A Benchmark for Visually-rich Document Understanding
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network
Linear scale semantic mining algorithms in microsoft SQL server's semantic platform
Sequence As Genes: An User Behavior Modeling Framework for Fraud Transaction Detection in E-commerce
Meta-classification of Multi-type Cancer Gene Expression Data
Dynamic Embeddings for User Profiling in Twitter
Maximal boasting
Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data
Revisiting Self-attention for Cross-domain Sequential Recommendation
Mean-entropy discretized features are effective for classifying high-dimensional biomedical data
Precursor-of-Anomaly Detection for Irregular Time Series
FedAPM: Federated Learning via ADMM with Partial Model Personalization
A Unified Solution to Constrained Bidding in Online Display Advertising
Hierarchical mixture models: a probabilistic analysis
IBM AutoAI: Human-in-the-Loop Automated Machine Learning Supports Data Scientists to Build Better Models
Enhancing Bone Mineral Density Estimation from X-ray Images with Cross-Modal Knowledge Distillation
Synthetic Tabular Data: Methods, Attacks and Defenses
An Architecture for Agile Machine Learning in Real-Time Applications
Stable Prediction across Unknown Environments
Finding Similar Exercises in Online Education Systems
Mining regular routes from GPS data for ridesharing recommendations
Analysis of COVID-19 Offensive Tweets and Their Targets
GLAD: group anomaly detection in social media analysis
Task Negative Sampling Enhanced Graph Few-shot Learning
Daily Prediction of Major Stock Indices from Textual WWW Data
A Unified Notion of Outliers: Properties and Computation
A Survey on Model Extraction Attacks and Defenses for Large Language Models
Modeling Context-aware Features for Cognitive Diagnosis in Student Learning
WattHome: A Data-driven Approach for Energy Efficiency Analytics at City-scale
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data
Mitigating Pooling Bias in E-commerce Search via False Negative Estimation
LAICOS: an open source platform for personalized social web search
A framework for community identification in dynamic social networks
Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation
Domain-constrained semi-supervised mining of tracking models in sensor networks
A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks
Entity-centric topic-oriented opinion summarization in twitter
Analyzing the Benefits of Domain Knowledge in Substructure Discovery
How Powerful is Graph Filtering for Recommendation
Counseling Summarization Using Mental Health Knowledge Guided Utterance Filtering
Stratified k-means clustering over a deep web data source
Interpretable Prediction and Feature Selection for Survival Analysis
Probabilistic Attention for Sequential Recommendation
Three-Dimensional Stable Matching Problem for Spatial Crowdsourcing Platforms
Unsupervised Alignment of Hypergraphs with Different Scales
Large Vison-Language Foundation Model in Baidu AIGC Image Advertising
pureGAM: Learning an Inherently Pure Additive Model
Automated Identification of Causal Moderators in Time-Series Data
Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy
Causal discovery in social media using quasi-experimental designs
Learning to extract chemical names based on random text generation and incomplete dictionary
Applying syntactic similarity algorithms for enterprise information management
4 Perspectives in Human-Centered Machine Learning
Algorithmic Aspects of Temporal Betweenness
Bayesian Networks for Lossless Dataset Compression
On burstiness-aware search for document sequences
Cross-task crowdsourcing
Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks
READ: Robust and Efficient Anomaly Detection under Data Contamination and Limited Supervision
Extracting knowledge from gene expression data: A case study of Batten Disease
Computing Optimized Rectilinear Regions for Association Rules
Handling Concept Drifts in Incremental Learning with Support Vector Machines
CALDS: context-aware learning from data streams
A robust and scalable clustering algorithm for mixed type attributes in large database environment
Unsupervised feature selection for linked social media data
Latent aspect rating analysis on review text data: a rating regression approach
R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering
Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds
Using Twitter to Predict When Vulnerabilities will be Exploited
Probabilistic latent semantic user segmentation for behavioral targeted advertising
Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability
Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction
Calculating latent demand in the long tail
Cost-aware travel tour recommendation
MoDiff - Graph Generation with Motif-aware Diffusion Model
Robustness Evaluation of Graph-based News Detection Using Network Structural Information
Compression-aware I/O performance analysis for big data clustering
Estimating Campaign Benefits and Modeling Lift
Incomplete Multi-View Drug Recommendation via Multi-Level Representation Learning and Curriculum Learning
Protein sequence alignment and structural disorder: a substitution matrix for an extended alphabet
Lumos: Empowering Multimodal LLMs with Scene Text Recognition
The Gamma Operator for Big Data Summarization on an Array DBMS
Scalable kNN search on vertically stored time series
Learning nonstationary models of normal network traffic for detecting novel attacks
NRFormer: Nationwide Nuclear Radiation Forecasting with Spatio-Temporal Transformer
Knowledge Discovery in a Water Quality Database
PubMed search and exploration with real-time semantic network construction
Spatio-temporal Outlier Detection in Precipitation Data
Dataset Regeneration for Sequential Recommendation
The generalized Bayesian committee machine
Model Degradation Hinders Deep Graph Neural Networks
Zero-shot Multi-lingual Interrogative Question Generation for "People Also Ask" at Bing
Cross-Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction
Federated Few-shot Learning
Submodular Feature Selection for Partial Label Learning
Scalable Spectral Clustering Using Random Binning Features
iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation
ECGGAN: A Framework for Effective and Interpretable Electrocardiogram Anomaly Detection
Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English
HeavyGuardian: Separate and Guard Hot Items in Data Streams
FEZE: Alignment-Flexible Zero-Shot Vertical Federated Learning
A Data-driven Process Recommender Framework
MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction
Proceedings of the ACM SIGKDD International Workshop on Urban Computing, UrbComp@KDD 2012, Beijing, China, August 12, 2012
First Workshop on Content Understanding and Generation for E-commerce
TurKit: tools for iterative tasks on mechanical Turk
Scaling Up Stochastic Dual Coordinate Ascent
LaDEEP: A Deep Learning-based Surrogate Model for Large Deformation of Elastic-Plastic Solids
A distributed learning framework for heterogeneous data sources
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedIn
RITIO - Rule Induction Two In One
The business impact of deep learning
Learning Slow and Fast System Dynamics via Automatic Separation of Time Scales
Chromosomal Structural Abnormality Diagnosis by Homologous Similarity
Mining mobility data to minimise travellers' spending on public transport
Mining Generalized Association Rules and Sequential Patterns Using SQL Queries
EvoGraph: An Effective and Efficient Graph Upscaling Method for Preserving Graph Properties
Question Independent Grading using Machine Learning: The Case of Computer Program Grading
Dynamical Origins of Distribution Functions
Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding
A study of online service and information exposure of public companies
Structured correspondence topic models for mining captioned figures in biological literature
Negative correlations in collaboration: concepts and algorithms
Causality - Exploiting Multi-Modal Data
Wedjat: Detecting Sophisticated Evasion Attacks via Real-time Causal Analysis
Variable latent semantic indexing
FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation
Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning
Event summarization for system management
MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems
UnifieR: A Unified Retriever for Large-Scale Retrieval
Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics
On interactive visualization of high-dimensional data using the hyperbolic plane
Detecting moving object outliers in massive-scale trajectory streams
Static Versus Dynamic Sampling for Data Mining
Differentially Private High-Dimensional Data Publication via Sampling-Based Inference
A spectral-based clustering algorithm for categorical data using data summaries
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance
Active learning for biomedical citation screening
Two Algorithms for Inducing Causal Models from Data
Convex Optimization for Linear Query Processing under Approximate Differential Privacy
ProgDiffusion: Progressively Self-encoding Diffusion Models
Training and testing of recommender systems on data missing not at random
Identifying Complicated Contagion Scenarios from Cascade Data
Collaborative Deep Metric Learning for Video Understanding
Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting
Statistical change detection for multi-dimensional data
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts
Social interactions in P2P lending
Generating semantic annotations for frequent patterns with context analysis
Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions
Discovery of Meaningful Rules in Time Series
A Treatment Engine by Predicting Next-Period Prescriptions
Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems
A VC View of Investing in ML
Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies
MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games
Graph building as a mining activity: finding links in the small
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs
Synergizing Implicit and Explicit User Interests: A Multi-Embedding Retrieval Framework at Pinterest
FairMatch: Promoting Partial Label Learning by Unlabeled Samples
Spaceborne Data Enters the Mainstream
InFoRM: Individual Fairness on Graph Mining
Combo-Fashion: Fashion Clothes Matching CTR Prediction with Item History
Brant-X: A Unified Physiological Signal Alignment Framework
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Optimal Interpretable Clustering Using Oblique Decision Trees
Incremental context mining for adaptive document classification
1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22)
Test-Time Training with Diversified Local Aggregation Consistency for Mortality Prediction using Clinical Time Series
AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks
Fast online learning through offline initialization for time-sensitive recommendation
Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines
Taking machine learning research online with OpenML
Conditional Generative Modeling for High-dimensional Marked Temporal Point Processes
Graph Machine Learning Meets Multi-Table Relational Data
Retrieval And Structuring Augmented Generation with Large Language Models
Streaming feature selection using alpha-investing
Mining Associations in Text in the Presence of Background Knowledge
Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation
A Cube Model and Cluster Analysis for Web Access Sessions
Real-time Indexing for Large-scale Recommendation by Streaming Vector Quantization Retriever
Discovery of Fraud Rules for Telecommunications - Challenges and Solutions
Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning
Web-based Long-term Spine Treatment Outcome Forecasting
Online feature selection for mining big data
FLMarket: Enabling Privacy-preserved Pre-training Data Pricing for Federated Learning
Selective sampling on graphs for classification
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions
Offline Trajectory Optimization for Offline Reinforcement Learning
Mining emerging patterns by streaming feature selection
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications
"The Leicester City Fairytale?": Utilizing New Soccer Analytics Tools to Compare Performance in the 15/16 & 16/17 EPL Seasons
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
Septor: Seismic Depth Estimation Using Hierarchical Neural Networks
Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont
Multi-User Mobile Sequential Recommendation: An Efficient Parallel Computing Paradigm
From Law-Like Knowledge to Concept Hierarchies in Data
Improve User Retention with Causal Learning
Structural and temporal analysis of the blogosphere through community factorization
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
DeepTriage: Automated Transfer Assistance for Incidents in Cloud Services
Optimization Beyond Prediction: Prescriptive Price Optimization
A Deep Prediction Framework for Multi-Source Information via Heterogeneous GNN
A Novel Multi-View Clustering Method for Unknown Mapping Relationships Between Cross-View Samples
The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022)
Dual beta process priors for latent cluster discovery in chronic obstructive pulmonary disease
Panel: a data scientist's guide to making money from start-ups
A Minimal Variance Estimator for the Cardinality of Big Data Set Intersection
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
Probabilistic latent semantic visualization: topic model for visualizing documents
Tutorial notes of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, San Francisco, CA, USA, August 26-29, 2001
A Graph Learning Based Framework for Billion-Scale Offline User Identification
An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery
Cross channel optimized marketing by reinforcement learning
AI for Intelligent Financial Services: Examples and Discussion
Fragments of order
Data mining platform for database developers
Multi-Task Learning for Spatio-Temporal Event Forecasting
Semi-supervised learning with mixed knowledge information
Streaming graph partitioning for large distributed graphs
Twitter under crisis: can we trust what we RT?
DyPS: Dynamic Parameter Sharing in Multi-Agent Reinforcement Learning for Spatio-Temporal Resource Allocation
SketchPolymer: Estimate Per-item Tail Quantile Using One Sketch
Multi-Horizon Time Series Forecasting with Temporal Attention Learning
Multi-Touch Attribution Based Budget Allocation in Online Advertising
An information theoretic framework for data mining
Sleeved coclustering
Leveraging Label Distributions as Anchors to Enhance Video Recommendation
On the permanence of vertices in network communities
Privacy-preserving k -means clustering over vertically partitioned data
Efficient Continuous Space Policy Optimization for High-frequency Trading
Extracting semantic relations from query logs
Data-Driven Metric Development for Online Controlled Experiments: Seven Lessons Learned
A Stagewise Hyperparameter Scheduler to Improve Generalization
Adaptive Graph Guided Disambiguation for Partial Label Learning
IDR/QR: an incremental dimension reduction algorithm via QR decomposition
Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy
2021 KDD Workshop on Understanding Public Perceptions for Applied Data Science: How Important is it to Engage Society in Technology Development?
Frequent regular itemset mining
New perspectives and methods in link prediction
Generalizing Personalized Federated Graph Augmentation via Min-max Adversarial Learning
An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files
Variational Flow Graphical Model
Low-rank Nonnegative Tensor Decomposition in Hyperbolic Space
Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation
Diversity driven Query Rewriting in Search Advertising
Adaptive Graph Contrastive Learning for Recommendation
Transfer Learning based Search Space Design for Hyperparameter Tuning
SSumM: Sparse Summarization of Massive Graphs
Partial Multi-Label Learning with Meta Disambiguation
A Data Science Approach to Understanding Residential Water Contamination in Flint
Prediction and Profiling of Audience Competition for Online Television Series
Improving classification accuracy using automatically extracted training data
A microeconomic data mining problem: customer-oriented catalog segmentation
Modeling and Applications for Temporal Point Processes
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning
Learning Process-consistent Knowledge Tracing
Estimating Graphlet Statistics via Lifting
Preserving the Privacy of Sensitive Relationships in Graph Data
ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual Restoration
Improving Group Robustness on Spurious Correlation via Evidential Alignment
Contextual Intent Tracking for Personal Assistants
MiLeTS'21: 7th KDD Workshop on Mining and Learning from Time Series
A Simple Dense Pixel Visualization for Mobile Sensor Data Mining
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units
Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression
Embed Progressive Implicit Preference in Unified Space for Deep Collaborative Filtering
Nonnegative shared subspace learning and its application to social media retrieval
Estimating the Robustness of Discovered Knowledge
Data-Driven Never-Ending Learning Question Answering Systems
TSMO 2025: Two-sided Marketplace Optimization: Search, Discovery, Matching, Pricing & Growth
Explicit and Implicit Modeling via Dual-Path Transformer for Behavior Set-informed Sequential Recommendation
Feature shaping for linear SVM classifiers
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023)
Local Algorithm for User Action Prediction Towards Display Ads
WikiRAG: Revisiting Wikidata KGC Datasets with Community Updates and Retrieval-Augmented Generation
Parallel Lasso Screening for Big Data Optimization
Fast nonlinear regression via eigenimages applied to galactic morphology
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand
Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems
Scalable Blocking for Privacy Preserving Record Linkage
Rebalancing Bike Sharing Systems: A Multi-source Data Smart Optimization
Predicting Winning Price in Real Time Bidding with Censored Data
Transportation: A Data Driven Approach