yusuke1997/dblp-id-title huggingface dataset:
Disentangled Ontology Embedding for Zero-shot Learning
Aligning and Balancing ID and Multimodal Representations for Recommendation
Large Language Model Enhanced Recommender Systems: Methods, Applications and Trends
Models of Data Governance and Advancing Indigenous Genomic Data Sovereignty
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Relational Message Passing for Knowledge Graph Completion
Data Mining of User Navigation Patterns
Generalized Deep Mixed Models
Task-Adversarial Co-Generative Nets
Gender and Interest Targeting for Sponsored Post Advertising at Tumblr
Accelerating DNA sequencing-by-hybridization with noise
Trajectory pattern mining
ILRoute: A Graph-based Imitation Learning Method to Unveil Riders' Routing Strategies in Food Delivery Service
Structural Patterns and Generative Models of Real-world Hypergraphs
ISIS: a networked-epidemiology based pervasive web app for infectious disease pandemic planning and response
Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks
Fast Categorization of Web Documents Represented by Graphs
Learning with cost intervals
Confluence: conformity influence in large social networks
External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters
Ensemble-index: a new approach to indexing large databases
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
RUSH!: Targeted Time-limited Coupons via Purchase Forecasts
Detecting Interference in Online Controlled Experiments with Increasing Allocation
User oriented trajectory similarity search
PASS: Personalized Advertiser-aware Sponsored Search
Content to Node: Self-Translation Network Embedding
Availability Attacks Create Shortcuts
Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport
Meta-Learning for Query Conceptualization at Web Scale
Who Supported Obama in 2012?: Ecological Inference through Distribution Regression
Learning First Order Logic Rules with a Genetic Algorithm
Clustering time series from ARMA models with clipped data
Practical Counterfactual Policy Learning for Top-K Recommendations
AdaAX: Explaining Recurrent Neural Networks by Learning Automata with Adaptive States
TDGIA: Effective Injection Attacks on Graph Neural Networks
A Novel Prompt Tuning for Graph Transformers: Tailoring Prompts to Graph Topologies
Meme-tracking and the dynamics of the news cycle
ACM KDD AI4Cyber: The 1st Workshop on Artificial Intelligence-enabled Cybersecurity Analytics
Controllable Multi-Interest Framework for Recommendation
Analysis and Visualization of Metrics for Online Merchandising
Learning by Exploration: New Challenges in Real-World Environments
Realistic but Non-Identifiable Synthetic User Data Generation
Learning Temporal State of Diabetes Patients via Combining Behavioral and Demographic Data
When Social Influence Meets Item Inference
A Scalable Solution for Rule-Based Part-of-Speech Tagging on Novel Hardware Accelerators
Reducing the sampling complexity of topic models
Sequences of Sets
Graph Attention Multi-Layer Perceptron
Perioperative Predictions with Interpretable Latent Representation
Network Connectivity Optimization: Fundamental Limits and Effective Algorithms
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
Fast and Memory-Efficient Tucker Decomposition for Answering Diverse Time Range Queries
2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making
Carpenter: finding closed patterns in long biological datasets
Supervised Learning-enhanced Multi-Group Actor Critic for Live Stream Allocation in Feed
Learning to combine discriminative classifiers: confidence based
TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems
Fairness-Aware Online Meta-learning
Identifying Earmarks in Congressional Bills
Matching unstructured product offers to structured product specifications
Generalized Discords for Time Series Anomaly Detection with Flexible Subsequence Lengths
MLHat: Deployable Machine Learning for Security Defense
Querywise Fair Learning to Rank through Multi-Objective Optimization
Structure and attributes community detection: comparative analysis of composite, ensemble and selection methods
Blurring the Distinction between Command and Data in Scientific KDD
Deep Embedding Forest: Forest-based Serving with Deep Embedding Features
Reducing large diagonals in kernel matrices through semidefinite programming
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
Weighted graphs and disconnected components: patterns and a generator
An analysis of perspectives in interactive settings
Contextual Generative Auction with Permutation-level Externalities for Online Advertising
Application of Data Mining Techniques for Medical Image Classification
Improving Scalability in a Scientific Discovery System by Exploiting Parallelism
Learning Multi-view Molecular Representations with Structured and Unstructured Knowledge
Differentially private data release for data mining
SciSoc LLM Workshop: Large Language Models for Scientific and Societal Advances
A pattern discovery approach to retail fraud detection
Urban Foundation Models: A Survey
Model mining for robust feature selection
Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest
Balancing Bias and Variance for Active Weakly Supervised Learning
Fast In-Memory Triangle Listing for Large Real-World Graphs
A frequent pattern based framework for event detection in sensor network stream data
The missing models: a data-driven approach for learning how networks grow
Fast Newton Hard Thresholding Pursuit for Sparsity Constrained Nonconvex Optimization
FoodSIS: a text mining system to improve the state of food safety in singapore
Anomaly localization for network data streams with graph joint sparse PCA
Relational learning via collective matrix factorization
Linear-Time Rule Induction
On nested palindromes in clickstream data
λOpt: Learn to Regularize Recommender Models in Finer Levels
Simplicial SMOTE: Oversampling Solution to the Imbalanced Learning Problem
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
Incentive networks
MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi-task Learning
Daily travel behavior: lessons from a week-long survey for the extraction of human mobility motifs related information
Fates of Microscopic Social Ecosystems: Keep Alive or Dead?
Optimization in learning and data analysis
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing, UrbComp@KDD 2013, Chicago, Illinois, USA, August 11, 2013
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data
Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks
Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals
More than the Sum of its Parts: Building Domino Data Lab
23 rd International Workshop on Data Mining in Bioinformatics (BIOKDD 2024)
Adaptive duplicate detection using learnable string similarity measures
AI for Supply Chain: Today and Future
Assessing team strategy using spatiotemporal data
Predicting the product purchase patterns of corporate customers
ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019
Mining closed relational graphs with connectivity constraints
RES: A Robust Framework for Guiding Visual Explanation
On perturbation theory and an algorithm for maximal clique enumeration in uncertain and noisy graphs
Methods for Linking and Mining Massive Heterogeneous Databases
Brute-Force Mining of High-Confidence Classification Rules
A Context based Personalized Deep Network for Nearby Flight Recommendation
AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data
Can we learn a template-independent wrapper for news article extraction from a single training site?
Rise and fall patterns of information diffusion: model and implications
Visualization Techniques to Explore Data Mining Results for Document Collections
OpenBox: A Generalized Black-box Optimization Service
An Efficient Approach to Clustering in Large Multimedia Databases with Noise
Retrospective Higher-Order Markov Processes for User Trails
Network-Wide Traffic States Imputation Using Self-interested Coalitional Learning
Combined regression and ranking
Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design
End-to-End Semi-Supervised Ordinal Regression AUC Maximization with Convolutional Kernel Networks
On compressing social networks
FedDefender: Client-Side Attack-Tolerant Federated Learning
Document preprocessing for naive Bayes classification and clustering with mixture of multinomials
(alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Robust Multimodal Failure Detection for Microservice Systems
Conformal prediction for distribution-independent anomaly detection in streaming vessel data
Efficient anonymity-preserving data collection
The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014
Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM
Counterfactual Graphs for Explainable Classification of Brain Networks
RCTD: Reputation-Constrained Truth Discovery in Sybil Attack Crowdsourcing Environment
Efficient distributed computation of human mobility aggregates through user mobility profiles
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating
Gaussian Process with Graph Convolutional Kernel for Relational Learning
Disclosing Actual Controller based on Equity Knowledge Graph Learning
Using Rough Sets as Tools for Knowledge Discovery
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models
Knowledge Discovery in Integrated Call Centers: A Framework for Effective Customer-Driven Marketing
Proceedings of the 1st ACM Workshop on Medical Informatics and Healthcare, MIH 2017, Halifax, Nova Scotia, Canada, August 14, 2017
Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models
Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks
Financial incentives and the "performance of crowds"
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism
Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space
Localised Adaptive Spatial-Temporal Graph Neural Network
Information-theoretic co-clustering
Knowledge base maintenance using knowledge gap analysis
Mutual Information-aware Knowledge Distillation for Short Video Recommendation
Learning Latent Causal Structures with a Redundant Input Neural Network
Analyzing expert behaviors in collaborative networks
Public Health Implications of a delay differential equation model for COVID 19
The 12th International Workshop on Urban Computing
Effective and Efficient Sports Play Retrieval with Deep Representation Learning
Multiple Relational Attention Network for Multi-task Learning
Discovering Enterprise Concepts Using Spreadsheet Tables
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation
Defending Privacy Against More Knowledgeable Membership Inference Attackers
Modeling User Mobility for Location Promotion in Location-based Social Networks
REA: Robust Cross-lingual Entity Alignment Between Knowledge Graphs
Mobile app recommendations with security and privacy awareness
FlexiMine - A Flexible Platform for KDD Research and Application Construction
Evaluating classifiers' performance in a constrained environment
Anomaly Detection for an E-commerce Pricing System
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing
Comparing apples to oranges: a scalable solution with heterogeneous hashing
EVI N ET: Towards Open-World Graph Learning via Evidential Reasoning Network
Learning spatially variant dissimilarity (SVaD) measures
Variance Reduction Using In-Experiment Data: Efficient and Targeted Online Measurement for Sparse and Delayed Outcomes
Mining in a Data-Flow Environment: Experience in Network Intrusion Detection
Community Detection on Large Complex Attribute Network
Stabilizing Modality Gap & Lowering Gradient Norms Improve Zero-Shot Adversarial Robustness of VLMs
Domain-Guided Spatio-Temporal Self-Attention for Egocentric 3D Pose Estimation
Resilient k-Clustering
Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents
Capital and benefit in social networks
Adversarial Infidelity Learning for Model Interpretation
Temporal multi-hierarchy smoothing for estimating rates of rare events
Higher-order Clustering in Complex Heterogeneous Networks
Weather Knows What Will Occur: Urban Public Nuisance Events Prediction and Control with Meteorological Assistance
From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks
Extreme Multi-label Learning for Semantic Matching in Product Search
An Energy-centric Framework for Category-free Out-of-distribution Node Detection in Graphs
A robust and efficient clustering algorithm based on cohesion self-merging
Robust Event Forecasting with Spatiotemporal Confounder Learning
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks
Predicting student risks through longitudinal analysis
Visual exploration of collaboration networks based on graph degeneracy
Feature Reconstruction for Anomaly Detection on Directed Multigraphs: A Preprocessing Framework for GNNs
Random Decision Hashing for Massive Data Learning
Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs
User Behavior Pre-training for Online Fraud Detection
Combining Denoised Neural Network and Genetic Symbolic Regression for Memory Behavior Modeling via Dynamic Asynchronous Optimization
Mixing bandits: a recipe for improved cold-start recommendations in a social network
Boosting Explainability through Selective Rationalization in Pre-trained Language Models
Challenges in the Evaluation of Conversational Search Systems
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
From Prediction to Action: A Closed-Loop Approach for Data-Guided Network Resource Allocation
Spatio-temporal Event Forecasting and Precursor Identification
Medical Symptom Detection in Intelligent Pre-Consultation Using Bi-directional Hard-Negative Noise Contrastive Estimation
Empirical bayes model to combine signals of adverse drug reactions
AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification
Early Identification of Violent Criminal Gang Members
Numerical Formula Recognition from Tables
Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning
eTrust: understanding trust evolution in an online world
Data Driven Science: SIGKDD Panel
Grammatically Recognizing Images with Tree Convolution
A lung cancer outcome calculator using ensemble data mining on SEER data
Discovering Approximate Functional Dependencies using Smoothed Mutual Information
Trial and error in influential social networks
International Workshop on Data-driven Science of Science
Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews
Network discovery via constrained tensor analysis of fMRI data
FoodGPT: Reinforcement Post-Training of Large Language Models in the Food Delivery Domain
Community Detection Using a Measure of Global Influence
Issues in evaluation of stream learning algorithms
Identifying Decision Makers from Professional Social Networks
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms
Error-Based and Entropy-Based Discretization of Continuous Features
Your Neighbor Matters: Towards Fair Decisions Under Networked Interference
Revisiting Local PageRank Estimation on Undirected Graphs: Simple and Optimal
Mining frequent neighboring class sets in spatial databases
Data, Knowledge and Discovery: Machine Learning meets Natural Science
On Finding Socially Tenuous Groups for Online Social Networks
Finding trending local topics in search queries for personalization of a recommendation system
Efficient computation of personal aggregate queries on blogs
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading
SCE: Scalable Network Embedding from Sparsest Cut
Bridging the Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systems
TransformerLight: A Novel Sequence Modeling Based Traffic Signaling Mechanism via Gated Transformer
Occam's Two Razors: The Sharp and the Blunt
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning
Visualizing changes in the structure of data for exploratory feature selection
Mining Algorithm Roadmap in Scientific Publications
Fairness and Explanation in Clustering and Outlier Detection
Future Matters for Present: Towards Effective Physical Simulation over Meshes
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning
LARC: Learning Activity-Regularized Overlapping Communities Across Time
ClimateIQA: A New Dataset and Benchmark to Advance Vision-Language Models in Meteorology Anomalies Analysis
Conceptual and statistical footprints for social networks' characterization
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
VEWS: A Wikipedia Vandal Early Warning System
Linking named entities in Tweets with knowledge base via user interest modeling
On privacy preservation against adversarial data mining
A Hierarchical Context Augmentation Method to Improve Retrieval-Augmented LLMs on Scientific Papers
Computational epidemiology
CVS: a Correlation-Verification based Smoothing technique on information retrieval and term clustering
What is that Building?: An End-to-end System for Building Recognition from Streetside Images
Local Induction of Decision Trees: Towards Interactive Data Mining
Fast direction-aware proximity for graph mining
Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration
Extracting information from text and images for location proteomics
'Oh LLM, I'm Asking Thee, Please Give Me a Decision Tree': Zero-Shot Decision Tree Induction and Embedding with Large Language Models
Exploiting Wikipedia as external knowledge for document clustering
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation
Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models
Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking
Relational data pre-processing techniques for improved securities fraud detection
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding
M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining
Joint optimization of wrapper generation and template detection
Incremental all pairs similarity search for varying similarity thresholds
Building Discriminative User Profiles for Large-scale Content Recommendation
Valuing an Engagement Surface using a Large Scale Dynamic Causal Model
Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment
Effective image and video mining: an overview of model-based approaches
NFT-Based Data Marketplace with Digital Watermarking
Context-aware Academic Collaborator Recommendation
Know in AdVance: Linear-Complexity Forecasting of Ad Campaign Performance with Evolving User Interest
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors
Learning a Unified Embedding for Visual Search at Pinterest
Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights
Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting
Mining Knowledge in Noisy Audio Data
Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network
FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering
Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis
Sparsification of influence networks
Prediction of Hourly Earnings and Completion Time on a Crowdsourcing Platform
Cuts3vm: a fast semi-supervised svm algorithm
Generalized Additive Neural Networks
E.T.-RNN: Applying Deep Learning to Credit Loan Applications
Truth discovery with multiple conflicting information providers on the web
TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data
Life-stage Prediction for Product Recommendation in E-commerce
Mining evidences for named entity disambiguation
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent
Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks
Using and Learning Semantics in Frequent Subgraph Mining
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
Meta-Learned Metrics over Multi-Evolution Temporal Graphs
Heidi matrix: nearest neighbor driven high dimensional data visualization
Cyber security: how visual analytics unlock insight
Horting Hatches an Egg: A New Graph-Theoretic Approach to Collaborative Filtering
Adaptive Transfer Learning on Graph Neural Networks
From Swath to Full-Disc: Advancing Precipitation Retrieval with Multimodal Knowledge Expansion
Discovering Frequent Episodes in Sequences
Learn Together Stop Apart: An Inclusive Approach to Ensemble Pruning
Generative Causal Interpretation Model for Spatio-Temporal Representation Learning
Reverse Engineering Databases for Knowledge Discovery
On detecting space-time clusters
Lambda Learner: Fast Incremental Learning on Data Streams
Incorporating prior knowledge with weighted margin support vector machines
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning
Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages
Graph-in-Graph Network for Automatic Gene Ontology Description Generation
Kernel k-means: spectral clustering and normalized cuts
Evaluation of an algorithm for aspect-based opinion mining using a lexicon-based approach
Maximizing acceptance probability for active friending in online social networks
SURE: Robust, Explainable, and Fair Classification without Sensitive Attributes
Mining tree queries in a graph
SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning
Risk-O-Meter: an intelligent clinical risk calculator
Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation
Incremental and decremental training for linear classification
Activity Monitoring: Noticing Interesting Changes in Behavior
Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation
Efficient evaluation of large sequence kernels
Cross-domain collaboration recommendation
A Framework for Evaluating AI Agents in Open-Ended Conversations via Scripted Simulation
Screening and interpreting multi-item associations based on log-linear modeling
LLM4HAR: Generalizable On-device Human Activity Recognition with Pretrained LLMs
Hyperparameter Importance Across Datasets
LATTE: A Framework for Learning Item-Features to Make a Domain-Expert for Effective Conversational Recommendation
Incremental Mobile User Profiling: Reinforcement Learning with Spatial Knowledge Graph for Modeling Event Streams