yusuke1997/dblp-id-title huggingface dataset:
Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)
Active exploration for learning rankings from clickthrough data
Voltage Correlations in Smart Meter Data
An iterated graph laplacian approach for ranking on manifolds
UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models
Querying discriminative and representative samples for batch mode active learning
Meta-classification: Combining Multimodal Classifiers
Taming Pretrained Transformers for Extreme Multi-label Text Classification
Leveraging user libraries to bootstrap collaborative filtering
Multi-Modality Disease Modeling via Collective Deep Matrix Factorization
Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach
Streaming Graph Neural Networks with Generative Replay
Fast influence-based coarsening for large networks
Pre-training Time Series Models with Stock Data Customization
QSketch: An Efficient Sketch for Weighted Cardinality Estimation in Streams
Learning High-dimensional Directed Acyclic Graphs with Mixed Data-types
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
The Sixth International Workshop on Automation in Machine Learning
Lion: A GPU-Accelerated Online Serving System for Web-Scale Recommendation at Baidu
Graph Summarization with Controlled Utility Loss
Contrastive Text-enhanced Transformer for Cross-Domain Sequential Recommendation
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes
Learning optimal ranking with tensor factorization for tag recommendation
Deep Learning for Search and Recommender Systems in Practice
Dense Representation Learning and Retrieval for Tabular Data Prediction
Efficient Shift-Invariant Dictionary Learning
Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs
EdMot: An Edge Enhancement Approach for Motif-aware Community Detection
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 15-18, 1999
A space efficient streaming algorithm for triangle counting using the birthday paradox
PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction
PATE: Proximity-Aware Time Series Anomaly Evaluation
Coherent closed quasi-clique discovery from large dense graph databases
Benchmarking and Defending against Indirect Prompt Injection Attacks on Large Language Models
Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial
KDD for Science Data Analysis: Issues and Examples
Scaling Multi-Armed Bandit Algorithms
Spatial Clustering Regression of Count Value Data via Bayesian Mixture of Finite Mixtures
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks
The PERSEUS Project: Creating Personalized Multimedia News Portal
Spatial scan statistics: approximations and performance study
Scalable Algorithm for Finding Balanced Subgraphs with Tolerance in Signed Networks
Unsupervised P2P Rental Recommendations via Integer Programming
Proximal support vector machine classifiers
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks
Online Level-wise Hierarchical Clustering
Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework
TranSlider: Transfer Ensemble Learning from Exploitation to Exploration
Web image prediction using multivariate point processes
Analysis of protein-protein interaction networks using random walks
Efficient and Effective Edge-wise Graph Representation Learning
Maximum profit mining and its application in software development
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition
ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation
Truss-based Why-not Community Search
Seven pitfalls to avoid when running controlled experiments on the web
Exploiting Relevance Feedback in Knowledge Graph Search
GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization
Grouping students in educational settings
DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction
MicroAdapt: Self-Evolutionary Dynamic Modeling Algorithms for Time-evolving Data Streams
PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense
Composition attacks and auxiliary information in data privacy
EXACTA: Explainable Column Annotation
Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment
Interactive Interpretation of Kohonen Maps Applied to Curves
Analyzing customer behavior at Amazon.com
Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System
Improve Learning from Crowds via Generative Augmentation
Ad click prediction: a view from the trenches
Multitask Mixture of Sequential Experts for User Activity Streams
Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank
The Fourth International Workshop on Smart Data for Blockchain and Distributed Ledger (SDBD'24)
Efficient Mixture of Experts based on Large Language Models for Low-Resource Data Preprocessing
Fully Quanvolutional Networks for Time Series Classification
Allowing Privacy Protection Algorithms to Jump Out of Local Optimums: An Ordered Greed Framework
Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions
Improving Learning Efficacy on Duolingo via Generative AI and the Learner Feedback Loop
Geometric Comparison of Clarifications and Rule Sets
Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems
A Generalized Framework for Population Based Training
Estimated Judge Reliabilities for Weighted Bradley-Terry-Luce Are Not Reliable
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments
Scaling the Vocabulary of Non-autoregressive Models for Fast Generative Retrieval
A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation
Large Language Model with Curriculum Reasoning for Visual Concept Recognition
Learning with Limited Labels via Momentum Damped & Differentially Weighted Optimization
Simple Yet Efficient Algorithms for Maximum Inner Product Search via Extreme Order Statistics
Data Mining and Tree-Based Optimization
Extracting redundancy-aware top-k patterns
Fake News, Disinformation, Propaganda, Media Bias, and Flattening the Curve of the COVID-19 Infodemic
A hierarchical information theoretic technique for the discovery of non linear alternative clusterings
Towards Evolutionary Compression
Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics
FlowGEN: A Generative Model for Flow Graphs
Capital One's statistical problems: our top ten list
Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction
Online spatial data analysis and visualization system
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain
Molecular feature mining in HIV data
Clustering of power quality event data collected via monitoring systems installed on the electricity network
Physics-informed Neural ODE for Post-disaster Mobility Recovery
Conformalized Link Prediction on Graph Neural Networks
Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets
FAHES: A Robust Disguised Missing Values Detector
Randomization methods in data mining
Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping
Reconstructing chemical reaction networks: data mining meets system identification
Transfer Learning for Bilingual Content Classification
Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning
Dual Structure-guided Contrastive Network for Incomplete Multi-view Partial Multi-label Classification
PrivPy: General and Scalable Privacy-Preserving Data Mining
U-Air: when urban air quality inference meets big data
Biomedical text categorization with concept graph representations using a controlled vocabulary
Social User Interest Mining: Methods and Applications
MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation
Clustering pair-wise dissimilarity data into partially ordered sets
Adversarial Learning on Heterogeneous Information Networks
Probabilistic Modeling of a Sales Funnel to Prioritize Leads
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model
Collaborative multi-strategy classification: application to per-pixel analysis of images
MULTIVERSE: Mining Collective Data Science Knowledge from Code on the Web to Suggest Alternative Analysis Approaches
ComputAgeBench: Epigenetic Aging Clocks Benchmark
PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators
ClusCite: effective citation recommendation by information network-based clustering
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem
A Nearly-Linear Time Algorithm for Minimizing Risk of Conflict in Social Networks
HySAD: a semi-supervised hybrid shilling attack detector for trustworthy product recommendation
Hierarchical Reinforcement Learning for Dynamic Autonomous Vehicle Navigation at Intelligent Intersections
Multimedia Data Mining Using P-Trees
Disentangling the Performance Puzzle of Multimodal-aware Recommender Systems
Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction
Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling
The IGrid index: reversing the dimensionality curse for similarity indexing in high dimensional space
Formative Essay Feedback Using Predictive Scoring Models
Discovering unexpected information from your competitors' web sites
On community outliers and their efficient detection in information networks
Optimizing debt collections using constrained reinforcement learning
Metric Decomposition in A/B Tests
Textual data mining of service center call records
The "DGX" distribution for mining massive, skewed data
Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning
Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks
A generalized framework for mining spatio-temporal patterns in scientific data
4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation
Learning from Biased Data Using Mixture Models
Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Leveraging candidate popularity on Twitter to predict election outcome
Context-to-Session Matching: Utilizing Whole Session for Response Selection in Information-Seeking Dialogue Systems
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021)
A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis
Structural Graphical Lasso for Learning Mouse Brain Connectivity
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices
IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
Dynamic Learnware Filtering for Efficient Learnware Identification and System Slimming
Deep Computational Phenotyping
CASH via Optimal Diversity for Ensemble Learning
Extremely Fast Decision Tree
Mining reference tables for automatic text segmentation
Empirical Bayesian data mining for discovering patterns in post-marketing drug safety
XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques
Nonlinearity Encoding for Extrapolation of Neural Networks
Challenges for knowledge discovery in biology
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance
Enhancing Asymmetric Web Search through Question-Answer Generation and Ranking
Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning
Deep State-Space Generative Model For Correlated Time-to-Event Predictions
SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations
Scalable misbehavior detection in online video chat services
Aggregating web offers to determine product prices
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus
Causality quantification and its applications: structuring and modeling of multivariate time series
Genesis of postal address reading, current state and future prospects: thirty years of pattern recognition on duty of postal services
Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits
Restreaming graph partitioning: simple versatile algorithms for advanced balancing
ProST: Prompt Future Snapshot on Dynamic Graphs for Spatio-Temporal Prediction
Finding cliques in protein interaction networks via transitive closure of a weighted graph
Trajectory-driven Influential Billboard Placement
Learning incoherent sparse and low-rank patterns from multiple tasks
Recurrent Marked Temporal Point Processes: Embedding Event History to Vector
Optimal recommendations under attraction, aversion, and social influence
Effective string processing and matching for author disambiguation
Passenger-based predictive modeling of airline no-show rates
Joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters
Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases
Mastering Stock Markets with Efficient Mixture of Diversified Trading Experts
The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs
Names Don't Fly: Smart Filters for Profanity Detection and Classification in User-Generated Content
Towards Robust and Versatile Causal Discovery for Business Applications
Provable Adaptivity of Adam under Non-uniform Smoothness
Subspace Selection based Prompt Tuning with Nonconvex Nonsmooth Black-Box Optimization
Text Mining: Finding Nuggets in Mountains of Textual Data
Inferring user demographics and social strategies in mobile social networks
Optimizing Smartphone App Usage Prediction: A Click-Through Rate Ranking Approach
Handling outliers and concept drift in online mass flow prediction in CFB boilers
Scalable clustering and keyword suggestion for online advertisements
Learn to Refine: Synergistic Multi-Agent Path Optimization for Lifelong Conflict-Free Navigation of Autonomous Vehicles
2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)
People on drugs: credibility of user statements in health communities
Practical Single Domain Generalization via Training-time and Test-time Learning
Initialization of Iterative Refinement Clustering Algorithms
Distance-enhanced association rules for gene expression
Knowledge-Based Scientific Discovery in Geological Databases
OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
A Uniformly Bounded Correlation Function for Spatial Point Patterns
Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2015, Sydney, Australia, August 10, 2015
Mining frequent item sets by opportunistic projection
Analyzing user's behavior on a video database
Axiomatic Interpretability for Multiclass Additive Models
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach
The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web
Multiple Uses of Frequent Sets and Condensed Representations (Extended Abstract)
Balanced allocation with succinct representation
Towards Computing a Near-Maximum Weighted Independent Set on Massive Graphs
Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations
Predictive model performance: offline and online evaluations
MPCSL - A Modular Pipeline for Causal Structure Learning
The KDD 2022 Workshop on Causal Discovery (CD2022)
Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth
M3PT: A Multi-Modal Model for POI Tagging
Substucture Discovery in the SUBDUE System
Trajectory Clustering with Mixtures of Regression Models
Using tagflake for condensing navigable tag hierarchies from tag clouds
Cracking White-box DNN Watermarks via Invariant Neuron Transforms
CausalGeD: Blending Causality and Diffusion for Spatial Gene Expression Generation
Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition
Agglomerative clustering of a search engine query log
The role of information diffusion in the evolution of social networks
Sequential latent semantic indexing
Forecasting building occupancy using sensor network data
Learning Dynamic Context Graphs for Predicting Social Events
Adversarial support vector machine learning
A Generalization-Based Approach to Clustering of Web Usage Sessions
DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
Efficient PageRank Tracking in Evolving Networks
Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems
A scalable algorithm for clustering protein sequences
Low Rank Multi-Dictionary Selection at Scale
Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity
Biological Pathway Guided Gene Selection Through Collaborative Reinforcement Learning
CE-RCFR: Robust Counterfactual Regression for Consensus-Enabled Treatment Effect Estimation
Laplacian Change Point Detection for Dynamic Graphs
Bayesian relational data analysis
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes
Learning methods for lung tumor markerless gating in image-guided radiotherapy
Why people hate your app: making sense of user feedback in a mobile app store
New unsupervised clustering algorithm for large datasets
Unsupervised Paraphrasing via Deep Reinforcement Learning
Task-Adaptive Few-shot Node Classification
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning
The Fake vs Real Goods Problem: Microscopy and Machine Learning to the Rescue
Communication Efficient Distributed Kernel Principal Component Analysis
Algorithms for interpretable machine learning
Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors
Deep r -th Root of Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval
Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations
Training Big Random Forests with Little Resources
Neural Dynamics on Complex Networks
Bayesian Optimization and Embedded Learning Systems
On the semantic annotation of places in location-based social networks
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
Active spectral clustering via iterative uncertainty reduction
Explainable AI in Industry
Developing Tightly-Coupled Data Mining Applications on a Relational Database System
Handling missing values in GPS surveys using survival analysis: a GPS case study of outdoor advertising
TANGENT: a novel, 'Surprise me', recommendation algorithm
JobMiner: a real-time system for mining job-related patterns from social media
A generalized Co-HITS algorithm and its application to bipartite graphs
Direct mining of discriminative and essential frequent patterns via model-based search tree
Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems
Using random forests to uncover bivariate interactions in high dimensional small data sets
Buy It Again: Modeling Repeat Purchase Recommendations
Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate
Learnable Prompt as Pseudo-Imputation: Rethinking the Necessity of Traditional EHR Data Imputation in Downstream Clinical Prediction
Unsupervised learning of disease progression models
Mining quantitative correlated patterns using an information-theoretic approach
DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness
Temporal causal modeling with graphical granger methods
A Practical Introduction to Federated Learning
Hyperbolic Deep Learning for Foundation Models: A Survey
Pattern Discovery in Temporal Databases: A Temporal Logic Approach
Prediction of user location using the radiation model and social check-ins
ProfileRank: finding relevant content and influential users based on information diffusion
Measures and Best Practices for Responsible AI
BoKA: Bayesian Optimization based Knowledge Amalgamation for Multi-unknown-domain Text Classification
Towards scalable support vector machines using squashing
Discovering Trends in Text Databases
Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
Improving the Effectiveness of a Web Site with Web Usage Mining
Engagement-Driven Content Generation with Large Language Models
Picture this: preferences for image search
Foundations of Large-Scale Sequential Experimentation
Learning classifiers from only positive and unlabeled data
MONIC: modeling and monitoring cluster transitions
Decomposed Attention Segment Recurrent Neural Network for Orbit Prediction
Off-Policy Learning-to-Bid with AuctionGym
Convolutional Neural Networks for Steady Flow Approximation
A Self-boosted Framework for Calibrated Ranking
Distance metric learning using dropout: a structured regularization approach
Scalable Optimization for Embedding Highly-Dynamic and Recency-Sensitive Data
Knowledge Intensive Learning of Generative Adversarial Networks
3rd Workshop on Data Science with Human in the Loop, DaSH@KDD, Virtual Conference, August 15, 2021
Joint optimization of bid and budget allocation in sponsored search
TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou
Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification
Tax Fraud Detection for Under-Reporting Declarations Using an Unsupervised Machine Learning Approach
Informed knowledge discovery: using prior knowledge in discovery programs (invited talk, abstract only)
Turn Waste into Wealth: On Simultaneous Clustering and Cleaning over Dirty Data
Intention-aware Heterogeneous Graph Attention Networks for Fraud Transactions Detection
Interpreting Advertiser Intent in Sponsored Search
Chainlet Orbits: Topological Address Embedding for Blockchain
Shallow semantic parsing of product offering titles (for better automatic hyperlink insertion)
Toward autonomic grids: analyzing the job flow with affinity streaming
Matrix Completion with Queries
Data Pricing and Data Asset Governance in the AI Era
Aligning Dual Disentangled User Representations from Ratings and Textual Content
A Practical Framework of Conversion Rate Prediction for Online Display Advertising
LASCA: A Large-Scale Stable Customer Segmentation Approach to Credit Risk Assessment
Towards social user profiling: unified and discriminative influence model for inferring home locations
Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning
Online Ranking with Constraints: A Primal-Dual Algorithm and Applications to Web Traffic-Shaping
Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs
Causal Discovery from Temporal Data
Trustworthy online controlled experiments: five puzzling outcomes explained
A software system for buzz-based recommendations
Adaptive Domain Inference Attack with Concept Hierarchy
Extracting targeted data from the web