yusuke1997/dblp-id-title huggingface dataset:
Infominer: mining surprising periodic patterns
Pattern-based similarity search for microarray data
Mutual Distillation Extracting Spatial-temporal Knowledge for Lightweight Multi-channel Sleep Stage Classification
Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective
CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning
Multimodal Learning with Incomplete Modalities by Knowledge Distillation
A hazard based approach to user return time prediction
Multimedia Data Mining Framework for Raw Video Sequences
AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2018
MobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructions
Recurrent Neural Networks for Stochastic Control in Real-Time Bidding
Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer
Inside the atoms: ranking on a network of networks
Predicting Voice Elicited Emotions
Looking for Great Ideas: Analyzing the Innovation Jam
Mining rank-correlated sets of numerical attributes
Pairwise Adversarial Training for Unsupervised Class-imbalanced Domain Adaptation
Automated Discovery of Active Motifs in Three Dimensional Molecules
GuardFGL: Similarity-driven Federated Graph Learning with Adversarial Robustness and Membership Privacy
RankExpert: A Mixture of Textual-and-Behavioral Experts for Multi-Objective Learning-to-Rank in Web Search
Mining Implicit Relevance Feedback from User Behavior for Web Question Answering
Latent topic feedback for information retrieval
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
Mining Audit Data to Build Intrusion Detection Models
Optimized Risk Scores
Multiple-Instance Learning from Similar and Dissimilar Bags
DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation
Heterogeneous source consensus learning via decision propagation and negotiation
Preference Amplification in Recommender Systems
Large-Scale Inference of Network-Service Disruption upon Natural Disasters
Keynote Speaker: Alessandro Vespignani
Meaning Error Rate: ASR domain-specific metric framework
Cost-sensitive online active learning with application to malicious URL detection
A Customer Purchase Incidence Model Applied to Recommender Services
Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD, August 15, 1999, San Diego, CA, USA, revised papers
Nimble GNN Embedding with Tensor-Train Decomposition
Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta
Targeting direct cash transfers to the extremely poor
A concept-based model for enhancing text categorization
Bilateral Dependency Optimization: Defending Against Model-inversion Attacks
Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks
KDD Cup 2013: author disambiguation
Reasoning and Planning with Large Language Models in Code Development
A New Generation of Perspective API: Efficient Multilingual Character-level Transformers
The 4th KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial'24)
LinE: Logical Query Reasoning over Hierarchical Knowledge Graphs
EARS (earthquake alert and report system): a real time decision support system for earthquake crisis management
Breaking the Top- K Barrier: Advancing Top- K Ranking Metrics Optimization in Recommender Systems
Approximate kernel k-means: solution to large scale kernel clustering
Measuring the effects of preprocessing decisions and network forces in dynamic network analysis
Anonymizing sequential releases
An integrated machine learning approach to stroke prediction
Local peculiarity factor and its application in outlier detection
Tensorized Determinantal Point Processes for Recommendation
LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture
Regularization paths and coordinate descent
Fast and Accurate Partial Fourier Transform for Time Series Data
Estimating the Percolation Centrality of Large Networks through Pseudo-dimension Theory
Analyzing patterns of user content generation in online social networks
R 2 MR: Review and Rewrite Modality for Recommendation
Multi-objective Learning to Rank by Model Distillation
Proceedings of the 2nd ACM SIGKDD Workshop on Data Mining using Matrices and Tensors, Paris, France, June 28, 2009
ECGrecover: A Deep Learning Approach for Electrocardiogram Signal Completion
SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis
Explainable Artificial Intelligence on Biosignals for Clinical Decision Support
Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study
Multi Datasource LTV User Representation (MDLUR)
Augmenting Log-based Anomaly Detection Models to Reduce False Anomalies with Human Feedback
Graphical models of residue coupling in protein families
DeepSinger: Singing Voice Synthesis with Data Mined From the Web
Harm Mitigation in Recommender Systems under User Preference Dynamics
Mining traffic incidents to forecast impact
The battle for the future of data mining
The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis
MetaFac: community discovery via relational hypergraph factorization
Sylvester Tensor Equation for Multi-Way Association
TreeDT: gene mapping by tree disequilibrium test
Improving Search Clarification with Structured Information Extracted from Search Results
Structured Hedging for Resource Allocations with Leverage
Anonymization Techniques for Knowledge Discovery in Databases
Optimized Cost Per Click in Online Advertising: A Theoretical Analysis
Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU
Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms
Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction
Scalable Query N-Gram Embedding for Improving Matching and Relevance in Sponsored Search
Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding
Modeling mass protest adoption in social network communities using geometric brownian motion
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data
RapidScorer: Fast Tree Ensemble Evaluation by Maximizing Compactness in Data Level Parallelization
Mining microarray expression data for classifier gene-cores
Towards a Scalable k NN CF Algorithm: Exploring Effective Applications of Clustering
Saliency-Regularized Deep Multi-Task Learning
Bayesian analysis of massive datasets via particle filters
An Experimental Study of Quantitative Evaluations on Saliency Methods
AdKDD 2024
Non-transitive Hashing with Latent Similarity Components
Diffmv: A Unified Diffusion Framework for Healthcare Predictions with Random Missing Views and View Laziness
A scalable two-stage approach for a class of dimensionality reduction techniques
An Audio-centric Multi-task Learning Framework for Streaming Ads Targeting on Spotify
Improving management of aquatic invasions by integrating shipping network, ecological, and environmental data: data mining for social good
Task-optimized User Clustering based on Mobile App Usage for Cold-start Recommendations
Anomaly Detection in Finance: Editors' Introduction
Predictive modeling in practice: a case study from sprint
Context-aware query suggestion by mining click-through and session data
Accelerating Online CP Decompositions for Higher Order Tensors
Algorithms for discovering bucket orders from data
CompressGNN: Accelerating Graph Neural Network Training via Hierarchical Compression
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI
Blacklisting the Blacklist in Online Advertising: Improving Delivery by Bidding for What You Can Win
Neurophysiologically Realistic Environment for Comparing Adaptive Deep Brain Stimulation Algorithms in Parkinson's Disease
Squashing Flat Files Flatter
Uncertainty in online experiments with dependent data: an evaluation of bootstrap methods
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems
Breiman meets Bellman: Non-Greedy Decision Trees with MDPs
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Few-shot Low-resource Knowledge Graph Completion with Multi-view Task Representation Generation
Scalable, Distributed Data Mining - An Agent Architecture
Facets: Fast Comprehensive Mining of Coevolving High-order Time Series
Quantifying and Addressing Ranking Disparity in Human-Powered Data Acquisition
Topic-conditioned novelty detection
Fighting Opinion Control in Social Networks via Link Recommendation
Structured learning for non-smooth ranking losses
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Integrating community matching and outlier detection for mining evolutionary community outliers
CoupledLP: Link Prediction in Coupled Networks
'Beating the news' with EMBERS: forecasting civil unrest using open source indicators
Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness
An efficient ADMM algorithm for multidimensional anisotropic total variation regularization problems
Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series
MSHTrans: Multi-Scale Hypergraph Transformer with Time-Series Decomposition for Temporal Anomaly Detection
LIEGE: : link entities in web lists with knowledge base
Corroborate and learn facts from the web
Artificial Intelligence for Healthcare
Knowledge discovery in biological domains (tutorial AM-3)
Mining Cinematic Knowledge Work in Progress [An Extended Abstract]
Towards systematic design of distance functions for data mining applications
Efficient Join Order Selection Learning with Graph-based Representation
Multi-domain active learning for text classification
Using Optimal Embeddings to Learn New Intents with Few Examples: An Application in the Insurance Domain
Enhanced Emotion-aware Music Recommendation via Large Language Models
Data mining: are we there yet?
On-Device Learning for Model Personalization with Large-Scale Cloud-Coordinated Domain Adaption
A/B Test and Online Experiment Under Diminishing Marginal Effects: Regret Minimization and Statistical Inference
Discovering Knowledge in Commercial Databases Using Modern Heuristic Techniques
AGODE: Adaptive Graph ODE for Grid-free Fluid Modeling and Domain Adaptation
Interactive training of advanced classifiers for mining remote sensing image archives
Association analysis-based transformations for protein interaction networks: a function prediction case study
An Efficient Local Search Algorithm for Large GD Advertising Inventory Allocation with Multilinear Constraints
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams
UQABench: Evaluating User Embedding for Prompting LLMs in Personalized Question Answering
Resolving the Bias in Electronic Medical Records
Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping
On updates that constrain the features' connections during learning
The 13th International Workshop on Urban Computing
Variable Selection and Task Grouping for Multi-Task Learning
Data Mining for Loan Evaluation at ABN AMRO: A Case Study
Learning the unified kernel machines for classification
Understanding users' satisfaction for search engine evaluation
Preface: The 2021 ACM SIGKDD Workshop on Causal Discovery
Abstraction of High Level Concepts from Numerical Values in Databases
TextTruth: An Unsupervised Approach to Discover Trustworthy Information from Multi-Sourced Text Data
Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks
Evaluating Usefulness for Dynamic Classification
Q&R: A Two-Stage Approach toward Interactive Recommendation
Collecting and Analyzing Millions of mHealth Data Streams
Activity ranking in LinkedIn feed
Arbitrary Distribution Modeling with Censorship in Real-Time Bidding Advertising
Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction
A data driven approach to diagnosing and treating disease
Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation
Geometric View of Soft Decorrelation in Self-Supervised Learning
Evaluating a Class of Distance-Mapping Algorithms for Data Mining and Clustering
Mining closed episodes with simultaneous events
How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study
Proceedings of 2018 ACM SIGKDD Workshop on Causal Discovery, CD@KDD 2018, London, UK, 20 August 2018
PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation
RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams
Click-through Prediction for Advertising in Twitter Timeline
Privacy-preservation for gradient descent methods
Handling Feature Heterogeneity with Learnable Graph Patches
Parallel field ranking
Can we improve on the identification of transcription factor binding sites?
Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat
LibAUC: A Deep Learning Library for X-Risk Optimization
Efficient influence maximization in social networks
Noisy Label Removal for Partial Multi-Label Learning
Learning to Slice: Self-Supervised Interpretable Hierarchical Representation Learning with Graph Auto-Encoder Tree
A Novel Deep Learning Model by Stacking Conditional Restricted Boltzmann Machine and Deep Neural Network
CODA: Temporal Domain Generalization via Concept Drift Simulator
Effective multi-label active learning for text classification
Belief state approaches to signaling alarms in surveillance systems
Hybrid Poisson process
Fast algorithms for comprehensive n-point correlation estimates
Creating social networks to improve peer-to-peer networking
Characterizing Covid Waves via Spatio-Temporal Decomposition
Profiling Users from Online Social Behaviors with Applications for Tencent Social Ads
PD-Net: Quantitative Motor Function Evaluation for Parkinson's Disease via Automated Hand Gesture Analysis
An Embedded Feature Selection Framework for Control
Graph Recurrent Networks With Attributed Random Walks
On the quality of inferring interests from social neighbors
Truthful Bandit Mechanisms for Repeated Two-stage Ad Auctions
Topics in 0--1 data
Direct mining of discriminative patterns for classifying uncertain data
Efficient Online Evaluation of Big Data Stream Classifiers
Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting
Knowledge-Aligned Domain Shift Tuning for Efficient Adaptation in Large Language Models
Deep Clustering based Fair Outlier Detection
Accelerating Bayesian network parameter learning using Hadoop and MapReduce
Cross-Platform Online Team Formation in Spatial Crowdsourcing
EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration
AdaFS: Adaptive Feature Selection in Deep Recommender System
Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation
Center-piece subgraphs: problem definition and fast solutions
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling
Multi-label relational neighbor classification using social context features
Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition
Learning Based Distributed Tracking
Large-Scale Data-Driven Airline Market Influence Maximization
Leveraging Latent Features for Local Explanations
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection
Extracting discriminative concepts for domain adaptation in text mining
Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations
Logical Anomaly Detection with Text-based Logic via Component-Aware Contrastive Language-Image Training
Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes
The power of analysis and data
Regularized multi--task learning
Retrieval Augmented Cross-Domain LifeLong Behavior Modeling for Enhancing Click-through Rate Prediction
Understanding the Effect of Loss Functions on the Generalization of Recommendations
Robust detection of hyper-local events from geotagged social media data
New cached-sufficient statistics algorithms for quickly answering statistical questions
Selective Hashing: Closing the Gap between Radius Search and k-NN Search
Exploration of ground truth from raw GPS data
Boosting with structure information in the functional space: an application to graph classification
Friends Don't Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning
NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
Domain-oriented Language Modeling with Adaptive Hybrid Masking and Optimal Transport Alignment
Gemini: A Novel and Universal Heterogeneous Graph Information Fusing Framework for Online Recommendations
Construct robust rule sets for classification
Self-supervised Classification of Clinical Multivariate Time Series using Time Series Dynamics
Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms
Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization
Discovering frequent topological structures from graph datasets
A LRT framework for fast spatial anomaly detection
Collusion-resistant anonymous data collection method
Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability
Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022
Personalized Chit-Chat Generation for Recommendation Using External Chat Corpora
Modeling Persuasion Factor of User Decision for Recommendation
Learning to Embed Categorical Features without Embedding Tables for Recommendation
Accelerating Set Intersections over Graphs by Reducing-Merging
A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020
Whole Page Optimization with Global Constraints
Development of NeuroElectroMagnetic ontologies(NEMO): a framework for mining brainwave ontologies
Searching and mining trillions of time series subsequences under dynamic time warping
Clinical risk prediction with multilinear sparse logistic regression
Unsupervised Key Event Detection from Massive Text Corpora
A Real-time Framework for Detecting Efficiency Regressions in a Globally Distributed Codebase
Integration of semantic-based bipartite graph representation and mutual refinement strategy for biomedical literature clustering
PCA by Determinant Optimisation has no Spurious Local Optima
Efficient Machine Learning on Large-Scale Graphs
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning
Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning
An Innovative Concept For Image Information Mining
TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection
Solving combinatorial optimization problems using relaxed linear programming: a high performance computing perspective
Network sampling
RainMon: an integrated approach to mining bursty timeseries monitoring data
BioSnowball: automated population of Wikis
Algorithms for Hiring and Outsourcing in the Online Labor Market
ZooplanktonBench: A Geo-Aware Zooplankton Recognition and Classification Dataset from Marine Observations
Learning Backward Compatible Embeddings
A general model for clustering binary data
An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut
Price Investment using Prescriptive Analytics and Optimization in Retail
Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates
Sketched Follow-The-Regularized-Leader for Online Factorization Machine
Mining high utility episodes in complex event sequences
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning
Identifying Police Officers at Risk of Adverse Events
GLS-SOD: a generalized local statistical approach for spatial outlier detection
Performative Time-Series Forecasting
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting
Off-Policy Evaluation and Learning for the Future under Non-Stationarity
Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier
IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method Mapping
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices
LSRP: A Leader-Subordinate Retrieval Framework for Privacy-Preserving Cloud-Device Collaboration
Adversarial Detection with Model Interpretation
Scaling Up Graph Neural Networks Via Graph Coarsening
Statistical Emerging Pattern Mining with Multiple Testing Correction
Giga-Mining
ComSoc: adaptive transfer of user behaviors over composite social network
Unsupervised Classification of Sound for Multimedia Indexing
DIPS: Optimal Dynamic Index for Poisson πps Sampling
Online discovery and maintenance of time series motifs
CityGPT: Empowering Urban Spatial Cognition of Large Language Models
Fast collapsed gibbs sampling for latent dirichlet allocation
A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices
Build the State-of-the-Art Machine Learning Technology for the Crypto Economy
Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications
OAG-BERT: Towards a Unified Backbone Language Model for Academic Knowledge Services
Graph Neural Networks in Life Sciences: Opportunities and Solutions
Efficient Algorithms for Attribute-Oriented Induction
Business Policy Experiments using Fractional Factorial Designs: Consumer Retention on DoorDash
Diffusion-Inspired Cold Start with Sufficient Prior in Computerized Adaptive Testing
Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data
Domain Specific Knowledge Graphs as a Service to the Public: Powering Social-Impact Funding in the US
KGAT: Knowledge Graph Attention Network for Recommendation
Large-scale sparse logistic regression
A Model-Agnostic Approach to Differentially Private Topic Mining
Combining clustering and co-training to enhance text classification using unlabelled data
LungCAD: a clinically approved, machine learning system for lung cancer detection
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions
Mining Protein Contact Maps
Amazon Shop the Look: A Visual Search System for Fashion and Home
Semi-supervised learning with data calibration for long-term time series forecasting
Mutually Beneficial Collaborations to Broaden Participation of Hispanics in Data Science
Influence and correlation in social networks
Latent aspect rating analysis without aspect keyword supervision
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Webpage understanding: an integrated approach
Towards a Better Understanding of Linear Models for Recommendation
Improved Question Answering using Domain Prediction
Learning subspace kernels for classification