yusuke1997/dblp-id-title huggingface dataset:
Bolt: Accelerated Data Mining with Fast Vector Compression
Land cover change detection: a case study
Effective Retrieval of Audio Information from Annotated Text Using Ontologies
An association analysis approach to biclustering
Unsupervised feature selection for multi-cluster data
Graph Neural Networks with Node-wise Architecture
Chainer: A Deep Learning Framework for Accelerating the Research Cycle
Unifying Adversarial Multi-Deconfounded Learning Paradigm for Fake News Detection
Ranking Relevance in Yahoo Search
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks
Classification of software behaviors for failure detection: a discriminative pattern mining approach
MMRate: inferring multi-aspect diffusion networks with multi-pattern cascades
Isolation Kernel and Its Effect on SVM
The Impact of Changing Populations on Classifier Performance
A Bayesian network framework for reject inference
A latent mixed membership model for relational data
Sampling hidden objects using nearest-neighbor oracles
Predicting Economic Development using Geolocated Wikipedia Articles
Conceptual Clustering in Structured Databases: A Practical Approach
On computing, storing and querying frequent patterns
Deep Landscape Forecasting for Real-time Bidding Advertising
Discovering Dynamic Causal Space for DAG Structure Learning
Learning to Generate Personalized Query Auto-Completions via a Multi-View Multi-Task Attentive Approach
Identifying purpose behind electoral tweets
Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection
Provable deterministic leverage score sampling
LASTA: large scale topic assignment on multiple social networks
Social Recommendation with Optimal Limited Attention
Applying data mining techniques to address critical process optimization needs in advanced manufacturing
KiL 2023 : 3rd International Workshop on Knowledge-infused Learning
Supervised learning for provenance-similarity of binaries
When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery
Combinational collaborative filtering for personalized community recommendation
Constraint-driven clustering
Permu-pattern: discovery of mutable permutation patterns with proximity constraint
Mixed Method Development of Evaluation Metrics
Online debate summarization using topic directed sentiment analysis
Quantifying sentiment and influence in blogspaces
Graph Neural Networks: Foundation, Frontiers and Applications
Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation
Primal sparse Max-margin Markov networks
Convex optimization: from embedded real-time to large-scale distributed
MentorPDM: Learning Data-Driven Curriculum for Multi-Modal Predictive Maintenance
Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising
Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks
xStream: Outlier Detection in Feature-Evolving Data Streams
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
Argo: intelligent advertising by mining a user's interest from his photo collections
Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor
Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks
A two-way visualization method for clustered data
PERT-GNN: Latency Prediction for Microservice-based Cloud-Native Applications via Graph Neural Networks
Structured metric learning for high dimensional problems
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
Detecting Atmospheric Regimes Using Cross-Validated Clustering
Learning-Based Ad Auction Design with Externalities: The Framework and A Matching-Based Approach
Decoupled Learning for Factorial Marked Temporal Point Processes
Indexed block coordinate descent for large-scale linear classification with limited memory
Learning domain-independent string transformation weights for high accuracy object identification
Controllable Generation from Pre-trained Language Models via Inverse Prompting
V-Miner: using enhanced parallel coordinates to mine product design and test data
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy
Workshop on Discovering Drift Phenomena in Evolving Data Landscape (DELTA)
Incorporating Usage Information into Average-Clicks Algorithm
Interpretable nonnegative matrix decompositions
Singapore in Motion: Insights on Public Transport Service Level Through Farecard and Mobile Data Analytics
TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction
DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
Explicit-Implicit Entity Alignment Method in Multi-modal Knowledge Graphs
Design Domain Specific Neural Network via Symbolic Testing
Using uncertain chemical and thermal data to predict product quality in a casting process
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation
The structure of information pathways in a social communication network
Efficient anomaly monitoring over moving object trajectory streams
Hypergraph spectral learning for multi-label classification
Multi-task Representation Learning for Travel Time Estimation
A Structure-aware Invariant Learning Framework for Node-level Graph OOD Generalization
Who is repinning?: predicting a brand's user interactions using social media retrieval
POVE: A Preoptimized Vault of Expressions for Symbolic Regression Research and Benchmarking
Fast structure learning in generalized stochastic processes with latent factors
Mining e-commerce data: the good, the bad, and the ugly
Nostalgin: Extracting 3D City Models from Historical Image Data
A Practical Algorithm for Solving the Incoherence Problem of Topic Models In Industrial Applications
EmbedJoin: Efficient Edit Similarity Joins via Embeddings
Transfer Knowledge between Cities
Expander Hierarchies for Normalized Cuts on Graphs
Fast ordering of large categorical datasets for better visualization
The KDD 2021 Workshop on Causal Discovery (CD2021)
Popularity Bias in Dynamic Recommendation
Learning Instrument Invariant Characteristics for Generating High-resolution Global Coral Reef Maps
GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation
A Real Linear and Parallel Multiple Longest Common Subsequences (MLCS) Algorithm
A Taxi Order Dispatch Model based On Combinatorial Optimization
FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation
SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting
ODD: Outlier Detection and Description
SensitiveHUE: Multivariate Time Series Anomaly Detection by Enhancing the Sensitivity to Normal Patterns
Put Deep Learning to Work: Accelerate Deep Learning through Amazon SageMaker and ML Services
How Can Data Mining Help Bio-Data Analysis?
Forecasting Big Time Series: Theory and Practice
Exploiting Upper Approximation in the Rough Set Methodology
Group Bitmap Index: A Structure for Association Rules Retrieval
Discrimination-aware data mining
Overview and Importance of Data Quality for Machine Learning Tasks
UP-Bench: A Benchmark for Underwater Path Planning Algorithms
GraphTool-Instruction: Revolutionizing Graph Reasoning in LLMs through Decomposed Subtask Instruction
Tumor cell identification using features rules
On the Generalization and Adaptation Ability of Machine-Generated Text Detectors in Academic Writing
AssocExplorer: an association rule visualization system for exploratory data analysis
Generic Outlier Detection in Multi-Armed Bandit
FlanS: A Foundation Model for Free-Form Language-based Segmentation in Medical Images
EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis
Hidden POI Ranking with Spatial Crowdsourcing
Detection of unique temporal segments by information theoretic meta-clustering
Epidemiological modeling of news and rumors on Twitter
Rethinking the Learning of Belief Network Probabilities
SEAL: Learning Heuristics for Community Detection with Generative Adversarial Networks
BitLINK: Temporal Linkage of Address Clusters in Bitcoin Blockchain
When Interpretability Meets Generalization: Delta-GAM for Robust Extrapolation in Out-of-Distribution Settings
On the Hyperparameter Loss Landscapes of Machine Learning Models: An Exploratory Study
Joint latent topic models for text and citations
FLEXIS: FLEXible Frequent Subgraph Mining using Maximal Independent Sets
Contextual Feature Analysis to Improve Link Prediction for Location Based Social Networks
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution
Modeling and probabilistic reasoning of population evacuation during large-scale disaster
A Subsequence Interleaving Model for Sequential Pattern Mining
Scalable Graph Building from Text Data
User-click modeling for understanding and predicting search-behavior
Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction
STIFF: A Forecasting Framework for SpatioTemporal Data
Towards an effective cooperation of the user and the computer for classification
STRIP: stream learning of influence probabilities
Multi-Task Learning with Neural Networks for Voice Query Understanding on an Entertainment Platform
Partial Label Learning via Feature-Aware Disambiguation
Bivariate Decision Trees: Smaller, Interpretable, More Accurate
Learning Data Trend Regularities From Databases in a Dynamic Environment
Clustering without Over-Representation
Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence
Email Volume Optimization at LinkedIn
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks
Bi-Dynamic Graph ODE for Opinion Evolution
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks
Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries
OAG: Toward Linking Large-scale Heterogeneous Entity Graphs
Locally-scaled spectral clustering using empty region graphs
Customizing Graph Neural Network for CAD Assembly Recommendation
A Multiscale Scan Statistic for Adaptive Submatrix Localization
Big data analytics for healthcare
Efficient clustering of high-dimensional data sets with application to reference matching
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data
Recursive regularization for large-scale classification with hierarchical and graphical dependencies
Demystify Hyperparameters for Stochastic Optimization with Transferable Representations
A "semi-lazy" approach to probabilistic path prediction
Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control
Defining the Goals to Optimise Data Mining Performance
Information Theoretic Criteria for Community Detection
Active learning and search on low-rank matrices
Active Search of Connections for Case Building and Combating Human Trafficking
DUST: a generalized notion of similarity between uncertain time series
Discovering Generalized Episodes Using Minimal Occurrences
Financing lead triggers: empowering sales reps through knowledge discovery and fusion
Bringing Inclusive Diversity to Data Science: Opportunities and Challenges
Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning
Data-driven validation, completion and construction of event relationship networks
Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint
Mining the space of graph properties
A viewpoint-based approach for interaction graph analysis
Applications of AI/ML in Established and New Industries
Automatic multimedia cross-modal correlation discovery
Domain Adaptation in Physical Systems via Graph Kernel
End-to-End Query Term Weighting
Market Design and Computerized Marketplaces
Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Autonomous Discovery of Reliable Exception Rules
Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions
Learning Fair Representation via Distributional Contrastive Disentanglement
FpViz: a visualizer for frequent pattern mining
Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining
Evaluating similarity measures: a large-scale study in the orkut social network
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity
Applications of sampling and fractional factorial designs to model-free data squashing
Privacy-preserving cox regression for survival analysis
Paths2Pair: Meta-path Based Link Prediction in Billion-Scale Commercial Heterogeneous Graphs
Approximating a collection of frequent sets
Tornado Forecasting with Multiple Markov Boundaries
What is the Most Effective Intervention to Increase Job Retention for this Disabled Worker?
A Statistical Theory for Quantitative Association Rules
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Proceedings of the ACM SIGKDD Workshop on Human Computation, Paris, France, June 28, 2009
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data
Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN
Feature selection in scientific applications
Privacy preserving regression modelling via distributed computation
Probabilistic Hypergraph Recurrent Neural Networks for Time-series Forecasting
Quantifying Assimilate-Contrast Effects in Online Rating Systems: Modeling, Analysis and Application
Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data
Optimization and Simplification of Hierarchical Clusterings
Proceedings of the ADKDD'17, Halifax, NS, Canada, August 13 - 17, 2017
Characterizing large-scale population's indoor spatio-temporal interactive behaviors
Metric forensics: a multi-level approach for mining volatile graphs
Mining relational data through correlation-based multiple view validation
Mining favorable facets
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks
Spending Programmed Bidding: Privacy-friendly Bid Optimization with ROI Constraint in Online Advertising
AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks
Unsupervised link prediction using aggregative statistics on heterogeneous social networks
Origami: A New Data Visualization Tool
ELITE: Robust Deep Anomaly Detection with Meta Gradient
Deformable Markov model templates for time-series pattern matching
MetroGAN: Simulating Urban Morphology with Generative Adversarial Network
Fuzzy Interpretation of Induction Results
Talent Demand Forecasting with Attentive Neural Sequential Model
Catalysis Clustering with GAN by Incorporating Domain Knowledge
A Transferable Spatio-temporal Learning Framework for Cross-city Logistics Demand Prediction
Efficient Orthogonal Multi-view Subspace Clustering
A cross-collection mixture model for comparative text mining
Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-turn Conversations
From user comments to on-line conversations
Adapting to Generalized Online Label Shift by Invariant Representation Learning
Mapping search relevance to social networks
Sequential Anomaly Detection using Inverse Reinforcement Learning
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
Data quality through knowledge engineering
The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation
Improved Bounds on the Dot Product under Random Projection and Random Sign Projection
User Welfare Optimization in Recommender Systems with Competing Content Creators
TAG2M- A Task-Agnostic Knowledge Distillation Framework for Distilling GNN to MLP
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning
Fairness-Aware Continuous Predictions of Multiple Analytics Targets in Dynamic Networks
Text mining (workshop session - title only)
Finding low-entropy sets and trees from binary data
Ad Serving with Multiple KPIs
Automated Mechanism Design for Strategic Classification: Abstract for KDD'21 Keynote Talk
Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data
Learning relational probability trees
A phrase mining framework for recursive construction of a topical hierarchy
New algorithms for parking demand management and a city-scale deployment
Subset Node Anomaly Tracking over Large Dynamic Graphs
Evaluating Generative Models via Cubical Homology based Persistent Entropy
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications
The political blogosphere and the 2004 U.S. election: divided they blog
Sliding Sketches: A Framework using Time Zones for Data Stream Processing in Sliding Windows
Learning, indexing, and diagnosing network faults
Characterising the difference
Mining Entity-Identification Rules for Database Integration
FuzzyLight: A Robust Two-Stage Fuzzy Approach for Traffic Signal Control Works in Real Cities
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction
Mining Administrative Data to Spur Urban Revitalization
Towards Reliable Detection of Dielectric Hotspots in Thermal Images of the Underground Distribution Network
Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
Make Fairness More Fair: Fair Item Utility Estimation and Exposure Re-Distribution
COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching
Automated detection of frontal systems from numerical model-generated data
Neural Subgraph Isomorphism Counting
Similarity Forests
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024, Barcelona, Spain, August 25-29, 2024
Automated hypothesis generation based on mining scientific literature
Cross-training: learning probabilistic mappings between topics
SAMCNet: Towards a Spatially Explainable AI Approach for Classifying MxIF Oncology Data
TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size
Mining heterogeneous gene expression data with time lagged recurrent neural networks
KDD Cup 2013 - author-paper identification challenge: second place team
Feedback effects between similarity and social influence in online communities
Analysis of obligate and non-obligate complexes using desolvation energies in domain-domain interactions
FeaFiner: biomarker identification from medical data through feature generalization and selection
EMBER2024 - A Benchmark Dataset for Holistic Evaluation of Malware Classifiers
Rethinking Learner Modeling: A Feedback-Centric Cognitive Disentanglement Perspective
Approximate Personalized PageRank on Dynamic Graphs
Learning Metrics that Maximise Power for Accelerated A/B-Tests
Onboard classifiers for science event detection on a remote sensing spacecraft
Modeling Time-evolving Causality over Data Streams
Graph Intelligence with Large Language Models and Prompt Learning
Large margin distribution machine
Du-Parking: Spatio-Temporal Big Data Tells You Realtime Parking Availability
Cluster-Wide Task Slowdown Detection in Cloud System
CUT: community update and tracking in dynamic social networks
RetroGraph: Retrosynthetic Planning with Graph Search
Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity
Semi-supervised feature selection for graph classification
Temporal Multimodal Multivariate Learning
Explainable Classification of Brain Networks via Contrast Subgraphs
Lightweight Monitoring of Distributed Streams
FedNLR: Federated Learning with Neuron-wise Learning Rates
Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set
Contrastive Learning of Stress-specific Word Embedding for Social Media based Stress Detection
The Error is the Feature: How to Forecast Lightning using a Model Prediction Error
Efficient incremental constrained clustering
Enhancing Graph Representations Learning with Decorrelated Propagation
An Empirical Study of Selection Bias in Pinterest Ads Retrieval
On the Discovery of Evolving Truth
Mining Temporal Networks
Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability
Why collective inference improves relational classification
FINAL: Fast Attributed Network Alignment
Scalable mining of large disk-based graph databases
A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps
Mining heterogeneous information networks: the next frontier
Real Time Recommendations from Connoisseurs
Multimedia Data Mining for Traffic Video Sequences
An approach to spacecraft anomaly detection problem using kernel feature space
Learning from All Types of Experiences: A Unifying Machine Learning Perspective
A Logic Aware Neural Generation Method for Explainable Data-to-text
IMDS: intelligent malware detection system
PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network
Towards Adversarial Learning: From Evasion Attacks to Poisoning Attacks
Graph Reasoning with LLMs (GReaL)
Learning Attribute as Explicit Relation for Sequential Recommendation
Learning Interpretable Feature Context Effects in Discrete Choice
Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma
Virtual Node Tuning for Few-shot Node Classification
Unsupervised Feature Selection with Adaptive Structure Learning
Auctions with LLM Summaries
LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values
S-LIME: Stabilized-LIME for Model Explanation
Geo-spotting: mining online location-based services for optimal retail store placement
Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation
A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components
Discovering Spatial Relationships Between Approximately Equivalent Patterns in Contact Maps
Weakly Supervised Spatial Deep Learning based on Imperfect Vector Labels with Registration Errors
How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs
An energy-efficient mobile recommender system
Generic and Scalable Framework for Automated Time-series Anomaly Detection
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
Conditional topical coding: an efficient topic model conditioned on rich features
An integrated framework for suicide risk prediction
KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022
Geographical Hidden Markov Tree for Flood Extent Mapping
Finding frequent sub-trajectories with time constraints
Hierarchical Linear Symbolized Tree-Structured Neural Processes
Enhancing Black-Box Adversarial Attacks on Discrete Sequential Data via Bilevel Bayesian Optimization in Hybrid Spaces
Colibri: fast mining of large static and dynamic graphs
Neural Optimization with Adaptive Heuristics for Intelligent Marketing System
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud
A new scheme on privacy-preserving data classification
Heterogeneous Network Embedding via Deep Architectures
Mining for the most certain predictions from dyadic data
Whose "city of tomorrow" is it?: on urban computing, utopianism, and ethics
Whither Social Networks for Web Search?
Consensus group stable feature selection