yusuke1997/dblp-id-title huggingface dataset:
Top-Down Bayesian Posterior Sampling for Sum-Product Networks
GBPNet: Universal Geometric Representation Learning on Protein Structures
Privacy, Security, and Trust in KDD, First ACM SIGKDD International Workshop, PinKDD 2007, San Jose, CA, USA, August 12, 2007, Revised Selected Papers
Burstiness Scale: A Parsimonious Model for Characterizing Random Series of Events
MathWriting: A Dataset For Handwritten Mathematical Expression Recognition
Local Community Detection in Multiple Networks
SPIRAL: efficient and exact model identification for hidden Markov models
A Clustering-Based Framework to Control Block Sizes for Entity Resolution
Fast Committee Machines for Regression and Classification
Learning in non-stationary environments with class imbalance
Automated Categorization of Onion Sites for Analyzing the Darkweb Ecosystem
Video analytics solution for tracking customer locations in retail shopping malls
Fragile Earth: Innovative AI For Climate Risk Mitigation
Probabilistic topic models with biased propagation on heterogeneous information networks
Scale Space Exploration For Mining Image Information Content
Data Science at Flipkart - An Indian E-Commerce company
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning
Mining time-changing data streams
Large-Scale Subspace Clustering via k-Factorization
AI for Education (AI4EDU): Advancing Personalized Education with LLM and Adaptive Learning
Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio - Episode 1: Machine Transcription of the Manuscripts
PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data
Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features
Situation-Aware Adaptive Visualization for Sensory Data Stream Mining
The k -Trine Cohesive Subgraph and Its Efficient Algorithms
Scalable hands-free transfer learning for online advertising
Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding
Lightweight Auto-bidding based on Traffic Prediction in Live Advertising
The long and the short of it: summarising event sequences with serial episodes
Scientific Text Mining and Knowledge Graphs
Locally Densest Subgraph Discovery
THEMES: An Offline Apprenticeship Learning Framework for Evolving Reward Functions
Graph Similarity Description: How Are These Graphs Similar?
Effective Clustering on Large Attributed Bipartite Graphs
LaSEWeb: automating search strategies over semi-structured web data
Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web
siRNA off-target search: a hybrid q-gram based filtering approach
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017
Streaming submodular maximization: massive data summarization on the fly
Inside Jokes: Identifying Humorous Cartoon Captions
Robust Large-Scale Machine Learning in the Cloud
No Computation without Representation: Avoiding Data and Algorithm Biases through Diversity
Algorithmic Decision Making and the Cost of Fairness
Towards Automatic Evaluation for LLMs' Clinical Capabilities: Metric, Data, and Algorithm
MDL-Based Decision Tree Pruning
On the need for time series data mining benchmarks: a survey and empirical demonstration
Breaker: Removing Shortcut Cues with User Clustering for Single-slot Recommendation System
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
Improving Box Office Result Predictions for Movies Using Consumer-Centric Models
OCRS: an Interactive Object-based Image Clustering and Retrieval System
Workplace Recommendation with Temporal Network Objectives
Fast coordinate descent methods with variable selection for non-negative matrix factorization
Prototype-based learning on concept-drifting data streams
AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction
K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction
Parallel SimRank computation on large graphs with iterative aggregation
Fast Mining and Forecasting of Co-evolving Epidemiological Data Streams
DeGNN: Improving Graph Neural Networks with Graph Decomposition
MultiRank: co-ranking for objects and relations in multi-relational data
IVMR suite: An Industrial-scale Virtual Machine Rescheduling Dataset and Benchmark for Elastic Cloud Service
Bridging and Compressing Feature and Semantic Spaces for Robust Graph Neural Networks: An Information Theory Perspective
Societal Impact of Data Science and Artificial Intelligence
Learning to Solve Grouped 2D Bin Packing Problems in the Manufacturing Industry
Identifying authoritative actors in question-answering forums: the case of Yahoo! answers
Boosted Second Price Auctions: Revenue Optimization for Heterogeneous Bidders
Large-Scale Acoustic Automobile Fault Detection: Diagnosing Engines Through Sound
ACM KDD AI4Cyber/MLHat: Workshop on AI-enabled Cybersecurity Analytics and Deployable Defense
High-Dimensional Similarity Query Processing for Data Science
The U.S. Census Bureau Adopts Differential Privacy
Model-based document clustering with a collapsed gibbs sampler
Residual Correlation in Graph Neural Network Regression
On certain rigorous approaches to data mining (invited talk, abstract only)
Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions
Self-Paced Network Embedding
Benchmarks and Process Management in Data Science: Will We Ever Get Over the Mess?
Making generative classifiers robust to selection bias
Lost in Sequence: Do Large Language Models Understand Sequential Recommendation?
22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023)
Machine Learning on Graphs in the Era of Generative Artificial Intelligence
Visual Search at Alibaba
Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation
IQ-Net: A DNN Model for Estimating Interaction-level Dialogue Quality with Conversational Agents
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications
Context Pooling: Query-specific Graph Pooling for Generic Inductive Link Prediction in Knowledge Graphs
Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning?
Proactive Network Maintenance Using Machine Learning
Distributed data mining in a chain store database of short transactions
Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach
Automatic Synonym Discovery with Knowledge Bases
Fair Diversity Maximization with Few Representatives
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding
Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation
Temporal skeletonization on sequential data: patterns, categorization, and visualization
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Mining advisor-advisee relationships from research publication networks
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data
KiL 2024: 4th International Workshop on Knowledge-infused Learning (Towards Consistent, Reliable, Explainable, and Safe LLMs)
Privacy-Preserving Federated Learning using Flower Framework
Spectral Subspace Clustering for Attributed Graphs
Monitoring a Newsfeed for Hot Topics
Ranking and Calibrating Click-Attributed Purchases in Performance Display Advertising
Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model
Estimating Local Intrinsic Dimensionality
Probabilistic Community and Role Model for Social Networks
Classifying large data sets using SVMs with hierarchical clusters
UnG-MoCha: Neural Motif Counting in Uncertain Graphs
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition
Partial Label Learning with Semantic Label Representations
Enhancing investment decisions in P2P lending: an investor composition perspective
High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates
A Fast Distributed Stochastic Gradient Descent Algorithm for Matrix Factorization
Utility-based anonymization using local recoding
FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
Reducing gang violence through network influence based targeting of social programs
Learning Joint Relational Co-evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction
GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting
KompaRe: A Knowledge Graph Comparative Reasoning System
Interpretable Decision Sets: A Joint Framework for Description and Prediction
Data-centric AI: Techniques and Future Perspectives
A graph-theoretic approach to extract storylines from search results
UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation
Theory Instead of Experiment (TIE): A Creator Valuation System at Tencent
Maximum Degree-Based Quasi-Clique Search via an Iterative Framework
Transforming data to satisfy privacy constraints
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
SKnow-LLM Workshop: Structured Knowledge for Large Language Models
SimClusters: Community-Based Representations for Heterogeneous Recommendations at Twitter
Active Model Adaptation Under Unknown Shift
FPGASVM: A Framework for Accelerating Kernelized Support Vector Machine
Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach
Learning personal + social latent factor model for social recommendation
Sliding Spectrum Decomposition for Diversified Recommendation
Player-Team Heterogeneous Interaction Graph Transformer for Soccer Outcome Prediction
Capturing best practice for microarray gene expression data analysis
ESCFD: Probabilistic Flow Diffusion Model for Accelerated High-Quality Single-Cell RNA-seq Data Synthesis
Robust boosting and its relation to bagging
Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings
The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs
Automatic Dialogue Summary Generation for Customer Service
Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation
Mining for Causal Relationships: A Data-Driven Study of the Islamic State
Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations
Partition Cardinality Estimation in Image Repositories
Privacy, Security, and Trust in KDD, Second ACM SIGKDD International Workshop, PinKDD 2008, Las Vegas, NV, USA, August 24, 2008, Revised Selected Papers
On Reasoning LLMs: Myths, Merits, and How to Move Forward
Anonymizing set-valued data by nonreciprocal recoding
Evading Community Detection via Counterfactual Neighborhood Search
Stability and Generalization of Graph Convolutional Neural Networks
From Expansion to Retraction: Long-tailed Machine Unlearning via Boundary Manipulation
Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions
Proceedings of the 3rd international workshop on Link discovery, LinkKDD 2005, Chicago, Illinois, USA, August 21-25, 2005
Mass collaboration and data mining
Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens
Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification
CoRE Lab - An Effort to Engage College Hispanic Students in STEM
Amplifying the voice of youth in Africa via text analytics
A Comparison of Approaches for Maximizing Business Payoff of Prediction Models
Capturing Homogeneous Influence among Students: Hypergraph Cognitive Diagnosis for Intelligent Education Systems
Efficient mining of iterative patterns for software specification discovery
Latent Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model
Entity-aware Multi-task Learning for Query Understanding at Walmart
Learning Cumulatively to Become More Knowledgeable
An Iterative Global Structure-Assisted Labeled Network Aligner
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning
USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments
Quantification and semi-supervised classification methods for handling changes in class distribution
KDD 2021 Tutorial on Systemic Challenges and Solutions on Bias and Unfairness in Peer Review
Fire: An Optimization Approach for Fast Interpretable Rule Extraction
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2012, Beijing, China, August 12, 2012
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels
SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding
Fairness in Graph Machine Learning: Recent Advances and Future Prospectives
Salience and Market-aware Skill Extraction for Job Targeting
Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data
Dependence and Model Selection in LLP: The Problem of Variants
Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix
Applying General Bayesian Techniques to Improve TAN Induction
Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization
RuleViz : a model for visualizing knowledge discovery process
Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing
Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues
Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud
SAInf: Stay Area Inference of Vehicles using Surveillance Camera Records
Building blocks for exploratory data analysis tools
ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations
Reimagining Graph Classification from a Prototype View with Optimal Transport: Algorithm and Theorem
DiffusionE: Reasoning on Knowledge Graphs via Diffusion-based Graph Neural Networks
Learning Stable Graphs from Multiple Environments with Selection Bias
ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences
HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline
Deep Weakly-supervised Anomaly Detection
Fast and Accurate Temporal Hypergraph Representation for Hyperedge Prediction
When do data mining results violate privacy?
A fast and scalable clustering-based approach for constructing reliable radiation hybrid maps
An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints
Knowledge Discovery and the Interface of Computing and Statistics
TTGL: Large-scale Multi-scenario Universal Graph Learning at TikTok
Experiments with random projections for machine learning
Mining progressive confident rules
CS-RAD: Conditional Member Status Refinement and Ability Discovery for Social Network Applications
Interactive Audience Expansion On Large Scale Online Visitor Data
Tutorial on Human-Centered Explainability for Healthcare
Mini-Game Lifetime Value Prediction in WeChat
Data Poisoning Attacks Against Outcome Interpretations of Predictive Models
USAD: UnSupervised Anomaly Detection on Multivariate Time Series
Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts
Model-Agnostic Random Weighting for Out-of-Distribution Generalization
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project
Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks
Neural-Answering Logical Queries on Knowledge Graphs
Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features
ForTune: Running Offline Scenarios to Estimate Impact on Business Metrics
Geodemographic Influence Maximization
Signal detection in genome sequences using complexity based features
Learning and Transferring IDs Representation in E-commerce
Clustering and projected clustering with adaptive neighbors
A Study of Situational Reasoning for Traffic Understanding
Going Where, by Whom, and at What Time: Next Location Prediction Considering User Preference and Temporal Regularity
A Fast Exact Algorithm to Enumerate Maximal Pseudo-cliques in Large Sparse Graphs
Causal Effect Estimation on Hierarchical Spatial Graph Data
Data mining "to go": ubiquitous KDD for mobile and distributed environments
Metro maps of science
Towards parameter-free data mining
A New Approach to Protein Structure Mining and Alignment
Aircraft Trajectory Prediction Made Easy with Predictive Analytics
Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation
HOPS: Probabilistic Subtree Mining for Small and Large Graphs
Effective and efficient itemset pattern summarization: regression-based approaches
Fast and Accurate Domain Adaptation for Irregular Tensor Decomposition
Shop The Look: Building a Large Scale Visual Shopping System at Pinterest
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Causal Discovery from Shifted Multiple Environments
Contextual Embedding for Distributed Representations of Entities in a Text Corpus
Predictive and Causal Implications of using Shapley Value for Model Interpretation
Geodesic Forests
Web usage mining based on probabilistic latent semantic analysis
Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products
MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm
Spoken English Grading: Machine Learning with Crowd Intelligence
What Do You See?: Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors
Fast Rotation Kernel Density Estimation over Data Streams
On-board analysis of uncalibrated data for a spacecraft at mars
Uni-Retriever: Towards Learning the Unified Embedding Based Retriever in Bing Sponsored Search
Deep Sequence Learning with Auxiliary Information for Traffic Prediction
An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy
Grid and Road Expressions Are Complementary for Trajectory Representation Learning
Active learning using on-line algorithms
Category-Specific CNN for Visual-aware CTR Prediction at JD.com
Mobile call graphs: beyond power-law and lognormal distributions
Probabilistic latent network visualization: inferring and embedding diffusion networks
A probabilistic approach to sequence assembly validation
Graph Neural Networks for Multimodal Single-Cell Data Integration
A Diffusion-Based Method for Learning the Multi-Outcome Distribution of Medical Treatments
Support envelopes: a technique for exploring the structure of association patterns
Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation
Restructuring Databases for Knowledge Discovery by Consolidation and Link Formation
Online Generation of Profile Association Rules
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay
Shrinkage estimator generalizations of Proximal Support Vector Machines
Tight Sensitivity Bounds For Smaller Coresets
Prominent streak discovery in sequence data
Getting an h-Index of 100 in 20 Years or Less!
Rule Discovery from Time Series
Recommendation method for extending subscription periods
Clustering Using Monte Carlo Cross-Validation
Promotheus: An End-to-End Machine Learning Framework for Optimizing Markdown in Online Fashion E-commerce
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
Interestingness-Based Interval Merger for Numeric Association Rules
1st Workshop on Data Science with Human in the Loop, DaSH@KDD 2020, San Diego, California, USA, August 24, 2020
Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data
FedSC: Federated Learning with Semantic-Aware Collaboration
Learning from multi-topic web documents for contextual advertisement
Mining and Model Understanding on Medical Data
GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models
KissKissBan: a competitive human computation game for image annotation
Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement
Building Recommender Systems with PyTorch
Graph-Based User Behavior Modeling: From Prediction to Fraud Detection
Incorporating site-level knowledge for incremental crawling of web forums: a list-wise strategy
Machine learning for online query relaxation
Leveraging the Power of Conversations: Optimal Key Term Selection in Conversational Contextual Bandits
Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
R-Mixup: Riemannian Mixup for Biological Networks
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport
Partial least squares regression for graph mining
Interpretable Personalized Experimentation
Structural Event Detection from Log Messages
Addressing the attack attribution problem using knowledge discovery and multi-criteria fuzzy decision-making
Attackability Characterization of Adversarial Evasion Attack on Discrete Data
Compressing Graphs and Indexes with Recursive Graph Bisection
Detection of Apathy in Alzheimer Patients by Analysing Visual Scanning Behaviour with RNNs
Frontex real-time news event extraction framework
The 2nd Workshop on Large Language Models for E-Commerce
Automatic malware categorization using cluster ensemble
Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information
Adaptive Graph Encoder for Attributed Graph Embedding
Formulating distance functions via the kernel trick
Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data
Safe Online Bid Optimization with Return on Investment and Budget Constraints
iHR: an online recruiting system for Xiamen Talent Service Center
Hi-PNG: Efficient Interval-Filtering ANNS via Hierarchical Interval Partition Navigating Graph
Industrial Machine Learning
UrbanGPT: Spatio-Temporal Large Language Models
Selecting the right interestingness measure for association patterns
A Dual Heterogeneous Graph Attention Network to Improve Long-Tail Performance for Shop Search in E-Commerce
Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction
Propagation Structure-Aware Graph Transformer for Robust and Interpretable Fake News Detection
GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
A Hybrid Framework for Text Modeling with Convolutional RNN
node2vec: Scalable Feature Learning for Networks
FRT: Flow-based Reconcile Transformer for Hierarchical Time Series
Can Television Advertising Impact Be Measured on the Web? Web Spike Response as a Possible Conversion Tracking System for Television
Random projection in dimensionality reduction: applications to image and text data
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning
The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms
Extremely Fast Decision Tree Mining for Evolving Data Streams
Accurate intelligible models with pairwise interactions
MonoDeMB: Comprehensive Monocular DepthMap Benchmark
Proceedings of KDD Cup 2011 competition, San Diego, CA, USA, 2011