yusuke1997/dblp-id-title huggingface dataset:
Spectral Ensemble Clustering
The Third International Workshop on Smart Data for Blockchain and Distributed Ledger (SDBD2021): Joint Workshop with SIGKDD 2021 Trust Day
Discovering Models from Structural and Behavioral Brain Imaging Data
Fastanova: an efficient algorithm for genome-wide association study
Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language Models
A highly-usable projected clustering algorithm for gene expression profiles
Fully automatic cross-associations
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting
Does social good justify risking personal privacy?
Planning and Learning under Uncertainty: Theory and Practice
Randomly sampling maximal itemsets
Revisiting Synthetic Human Trajectories: Imitative Generation and Benchmarks Beyond Datasaurus
City-scale traffic simulation from digital footprints
Cracking the Black Box: Distilling Deep Sports Analytics
DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation
TiVo: making show recommendations using a distributed collaborative filtering architecture
DiMA: An LLM-Powered Ride-Hailing Assistant at DiDi
Geometric Graph Representation Learning on Protein Structure Prediction
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
Mining of Switching Sparse Networks for Missing Value Imputation in Multivariate Time Series
From run-time behavior to usage scenarios: an interaction-pattern mining approach
Training linear SVMs in linear time
AutoLoss: Automated Loss Function Search in Recommendations
A Universal Model for Human Mobility Prediction
HiMacMic: Hierarchical Multi-Agent Deep Reinforcement Learning with Dynamic Asynchronous Macro Strategy
OmniSage: Large Scale, Multi-Entity Heterogeneous Graph Representation Learning
PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph
Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit
Efficiently Solving the Practical Vehicle Routing Problem: A Novel Joint Learning Approach
Mining Large Quasi-cliques with Quality Guarantees from Vertex Neighborhoods
Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition
Statistically Significant Pattern Mining with Ordinal Utility
Exception Dags as Knowledge Structures
Collusion-resistant privacy-preserving data mining
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages
Smart Broadcasting: Do You Want to be Seen?
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
Detecting privacy leaks using corpus-based association rules
Unsupervised Differentiable Multi-aspect Network Embedding
Communication-efficient Multi-service Mobile Traffic Prediction by Leveraging Cross-service Correlations
Compass: Spatio Temporal Sentiment Analysis of US Election What Twitter Says!
The user's communication patterns on a mobile social network site
VQNE: Variational Quantum Network Embedding with Application to Network Alignment
Accurate Graph-based Multi-Positive Unlabeled Learning via Disentangled Multi-view Feature Propagation
Graph Adversarial Attack via Rewiring
Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
RBEM: a rule based approach to polarity detection
Counterfactual Evaluation and Learning for Interactive Systems: Foundations, Implementations, and Recent Advances
We know what you want to buy: a demographic-based system for product recommendation on microblogs
Privileged Knowledge State Distillation for Reinforcement Learning-based Educational Path Recommendation
Targeting the right students using data mining
Learning to match and cluster large high-dimensional data sets for data integration
Online Few-Shot Time Series Classification for Aftershock Detection
Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information
A new efficient probabilistic model for mining labeled ordered trees
Making holistic schema matching robust: an ensemble approach
Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery
Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS
AutoML: A Perspective where Industry Meets Academy
M-Mix: Generating Hard Negatives via Multi-sample Mixing for Contrastive Learning
Efficient social network approximate analysis on blogosphere based on network structure characteristics
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea
Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering
HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou
A fast algorithm for finding frequent episodes in event streams
Graph Triple Attention Networks: A Decoupled Perspective
Fast and Intuitive Clustering of Web Documents
Local sparsity control for naive Bayes with extreme misclassification costs
Efficient Parallel Classification Using Dimensional Aggregates
Generating English summaries of time series data using the Gricean maxims
Active Feature Acquisition with Supervised Matrix Completion
Efficient Incremental Computation of Aggregations over Sliding Windows
Mining for geographically disperse communities in social networks by leveraging distance modularity
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration
Active learning with direct query construction
Neural Bandit with Arm Group Graph
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery
Anytime Concurrent Clustering of Multiple Streams with an Indexing Tree
Applying Deep Learning Based Probabilistic Forecasting to Food Preparation Time for On-Demand Delivery Service
Zero-shot Node Classification with Decomposed Graph Prototype Network
The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver
The Power of (Statistical) Relational Thinking
Nomograms for visualizing support vector machines
S3GA: Towards Scalable Self-Supervised Learning for Large Scale Graph Alignment
Which Tweets Will Be Headlines? A Hierarchical Bayesian Model for Bridging Social Media and Traditional Media
Modeling and predicting user behavior in sponsored search
SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping
Towards Universal Sequence Representation Learning for Recommender Systems
OLAP on search logs: an infrastructure supporting data-driven applications in search engines
Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature
Efficient semi-streaming algorithms for local triangle counting in massive graphs
Rank aggregation via nuclear norm minimization
LiRank: Industrial Large Scale Ranking Models at LinkedIn
Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification
New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine
Fraud Detection with Density Estimation Trees
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance
Sequential Scenario-Specific Meta Learner for Online Recommendation
TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation
Data mining at the crossroads: successes, failures and learning from them
Proceedings of the 5th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2016, San Francisco, CA, USA, August 14, 2016
Skills Explorer: A Human+AI Approach to Data Capture for Skills
Maximizing return and minimizing cost with the right decision management systems
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression
Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation
PVA: a self-adaptive personal view agent system
A mixture model for contextual text mining
A Perspective on Databases and Data Mining
Generative AI meets Responsible AI: Practical Challenges and Opportunities
A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks
Scalable Learning of Graphical Models
Active learning for online bayesian matrix factorization
Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA
Statistics and Data Mining Techniques for Lifetime Value Modeling
Ask me better questions: active learning queries based on rule induction
Source Localization for Cross Network Information Diffusion
Unified Low-rank Compression Framework for Click-through Rate Prediction
Verification of Incomplete Graph Unlearning through Adversarial Perturbations
Rover: An Online Spark SQL Tuning Service via Generalized Transfer Learning
Empirical bayes screening for multi-item associations
Discovery and Maintenance of Functional Dependencies by Independencies
Transfer metric learning by learning task relationships
KDD 2025 Workshop on Inference Optimization for Generative AI
Representing documents through their readers
Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness
Deep Recursive Network Embedding with Regular Equivalence
Streaming Session-based Recommendation
Improving clustering stability with combinatorial MRFs
Data Mining: Crossing the Chasm (Invited talk, Abstract only)
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
Towards Representation Alignment and Uniformity in Collaborative Filtering
Mining high dimensional data for classifier knowledge
CoLiDR: Concept Learning using Aggregated Disentangled Representations
Inductive Link Prediction on N-ary Relational Facts via Semantic Hypergraph Reasoning
Temporal Uplift Modeling for Online Marketing
Compressed fisher linear discriminant analysis: classification of randomly projected data
Constructing Web User Profiles: A non-invasive Learning Approach
Multi-Type Itemset Embedding for Learning Behavior Success
Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), San Diego, CA, USA, 24 August 2020
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection
Deep Transfer Learning for City-scale Cellular Traffic Generation through Urban Knowledge Graph
Fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams
Spotting opinion spammers using behavioral footprints
DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview
FoodPuzzle: Toward Developing Large Language Model Agents as Autonomous Flavor Scientists
Octet: Online Catalog Taxonomy Enrichment with Self-Supervision
SIGEM: A Simple yet Effective Similarity based Graph Embedding Method
Multi-modal Network Representation Learning
An Empirical Evaluation of Sketching for Numerical Linear Algebra
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients
Leveraging Structural Knowledge for Hierarchically-Informed Keyword Weight Propagation in the Web
Friend Recommendations with Self-Rescaling Graph Neural Networks
Online Optimization Methods for the Quantification Problem
TDNetGen: Empowering Complex Network Resilience Prediction with Generative Augmentation of Topology and Dynamics
Dynamic Generation and Refinement of Concept Hierarchies for Knowledge Discovery in Databases
PROSE: Graph Structure Learning via Progressive Strategy
Banded structure in binary matrices
RLogic: Recursive Logical Rule Learning from Knowledge Graphs
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation
Data-Driven Oracle Bone Rejoining: A Dataset and Practical Self-Supervised Learning Scheme
Pattern discovery in sequences under a Markov assumption
Clinical and financial outcomes analysis with existing hospital patient records
One click mining: interactive local pattern discovery through implicit preference and performance learning
Open question answering over curated and extracted knowledge bases
Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging
SPIN: mining maximal frequent subgraphs from graph databases
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data
GraphWorld: Fake Graphs Bring Real Insights for GNNs
Machine Learning in Finance
Intelligible and Explainable Machine Learning: Best Practices and Practical Challenges
Predictive client-side profiles for personalized advertising
CAPER: Enhancing Career Trajectory Prediction using Temporal Knowledge Graph and Ternary Relationship
ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving
Combining strengths, emotions and polarities for boosting Twitter sentiment analysis
Affective Signals in a Social Media Recommender System
Real-time Event Detection on Social Data Streams
A Probabilistic Approach to Fast Pattern Matching in Time Series Databases
Ameliorating buyer's remorse
CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies
Co-evolution of social and affiliation networks
Nantonac collaborative filtering: recommendation based on order responses
B-EM: a classifier incorporating bootstrap with EM approach for data mining
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks
Exploiting Intent Evolution in E-commercial Query Recommendation
Automated Approaches for Classifying Structures
Multi-Task Combinatorial Bandits for Budget Allocation
Graph-based anomaly detection
An Efficient Algorithm to Update Large Itemsets with Early Pruning
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
Minimizing Congestion for Balanced Dominators
Robust Top- k Multiclass SVM for Visual Category Recognition
Smart Pacing for Effective Online Ad Campaign Optimization
Efficient Bi-Level Optimization for Recommendation Denoising
Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures
Playing hide-and-seek with correlations
COEF-VQ: Cost-Efficient Video Quality Understanding through a Cascaded Multimodal LLM Framework
On the efficacy of data mining for security applications
Machine Learning for Clinical Management: From the Lab to the Hospital
p-Meta: Towards On-device Deep Model Adaptation
Auto-Split: A General Framework of Collaborative Edge-Cloud AI
Competitive Analysis for Points of Interest
Enhanced word clustering for hierarchical text classification
Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion
Evaluating and Generating Query Workloads for High Dimensional Vector Similarity Search
Seeker: Real-Time Interactive Search
A multi-task learning formulation for predicting disease progression
Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation
Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence
Sequential cost-sensitive decision making with reinforcement learning
State Space Models for Forecasting Water Quality Variables: An Application in Aquaculture Prawn Farming
List-wise Fairness Criterion for Point Processes
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition
GHashing: Semantic Graph Hashing for Approximate Similarity Search in Graph Databases
Scalable Heterogeneous Transfer Ranking
Device Graphing by Example
Practical Guidance and Tutorial on Incentivizing Reasoning in LLMs using Distillation and Reinforcement Learning
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Structured Noise Detection: Application on Well Test Pressure Derivative Data
FairCDR: Transferring Fairness and User Preferences for Cross-Domain Recommendation
Tracking dynamics of topic trends using a finite mixture model
Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration
Fast Computation of 2-Dimensional Depth Contours
Detection of emerging space-time clusters
International Workshop on Federated Learning for Distributed Data Mining
Reducing Data Loading Bottleneck with Coarse Feature Vectors for Large Scale Learning
Categorizing and mining concept drifting data streams
Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification
Sparse Binary Transformers for Multivariate Time Series Modeling
Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey
Modeling and predicting personal information dissemination behavior
Feature bagging for outlier detection
Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference
A data-driven method for in-game decision making in MLB: when to pull a starting pitcher
Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
struc2vec : Learning Node Representations from Structural Identity
FinBERT2: A Specialized Bidirectional Encoder for Bridging the Gap in Finance-Specific Deployment of Large Language Models
Inferring local synonyms for improving keyword suggestion in an on-line advertisement system
Discovery of Interesting Usage Patterns from Web Data
Urban Region Representation Learning with OpenStreetMap Building Footprints
GraphMAE: Self-Supervised Masked Graph Autoencoders
Coupled Graph ODE for Learning Interacting System Dynamics
Pushing constraints into data streams
Regularized discriminant analysis for high dimensional, low sample size data
Deep Learning for Prognosis Using Task-fMRI: A Novel Architecture and Training Scheme
Discovering latent influence in online social activities via shared cascade poisson processes
Effective Two-Stage Knowledge Transfer for Multi-Entity Cross-Domain Recommendation
MWCC: A Corpus of Malawi Criminal Cases
Feature selection methods for text classification
FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics
Comparing Massive High-Dimensional Data Sets
Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years
Programming the K-means clustering algorithm in SQL
Greykite: Deploying Flexible Forecasting at Scale at LinkedIn
Parallel Generalized Association Rule Mining on Large Scale PC Cluster
8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications
Towards Automated Synthesis of Data Mining Programs
Fairness of Exposure in Rankings
Automated cyclone discovery and tracking using knowledge sharing in multiple heterogeneous satellite data
A framework for simultaneous co-clustering and learning from complex data
A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations
Collaborative crawling: mining user experiences for topical resource discovery
Generative Thinking, Corrective Action: User-Friendly Composed Image Retrieval via Automatic Multi-Agent Collaboration
ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations
Enhanced Subgraph Learning in 2-FWL GNNs via Local Connectivity, Spectral, and Distance Encodings
Efficient methods for topic model inference on streaming document collections
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
The Good, the Bad, and the Outliers: A Testing Framework for Decision Optimization Model Learning
Visualizing Deep Learning Activations for Improved Malaria Cell Classification
GRAND : Graph Reconstruction from Potential Partial Adjacency and Neighborhood Data
Experience with discovering knowledge by acquiring it
GAS: Large-Scale Heterogeneous Personalization in Social Network Applications at Meta
MeLL: Large-scale Extensible User Intent Classification for Dialogue Systems with Meta Lifelong Learning
YaART: Yet Another ART Rendering Technology
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling
Interactive path analysis of web site traffic
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
A Genetic Algorithm-Based Approach to Data Mining
A visual-analytic toolkit for dynamic interaction graphs
CognitionNet: A Collaborative Neural Network for Play Style Discovery in Online Skill Gaming Platform
Knowledge Graph Completion with FAMER (DI2KG Challenge Winner)
Dynamic Language Models for Continuously Evolving Content
Finding Users Who Act Alike: Transfer Learning for Expanding Advertiser Audiences
Optimal real-time bidding for display advertising
Clouded Intelligence
BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization
Identifying "best bet" web search results by mining past user behavior
A Belief-Driven Method for Discovering Unexpected Patterns
Scalable histograms on large probabilistic data
Dual Channel Hypergraph Collaborative Filtering
Detecting and Correcting Typing Errors in DBpedia
Recovering latent time-series from their observed sums: network tomography with particle filters
Mining Association Rules with Item Constraints
Disease progression modeling from historical clinical databases
Heidegger: Interpretable Temporal Causal Discovery
Collective annotation of Wikipedia entities in web text
Why Attentions May Not Be Interpretable?
A sequential dual method for large scale multi-class linear svms
ADMM for Efficient Deep Learning with Global Convergence
A Robust Framework for Accelerated Outcome-driven Risk Factor Identification from EHR
un-xPass: Measuring Soccer Player's Creativity
Paper-Level Computerized Adaptive Testing for High-Stakes Examination via Multi-Objective Optimization
Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users
FedDiAL: Adaptive Federated Learning with Hierarchical Discriminative Network for Large Pre-trained Models
Balanced Confidence Calibration for Graph Neural Networks
MinSearch: An Efficient Algorithm for Similarity Search under Edit Distance
BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
FAT: Frequency-Aware Pretraining for Enhanced Time-Series Representation Learning
Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics
Fine-Grained System Identification of Nonlinear Neural Circuits
Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction
Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey
PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks
Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs
Statistical quality estimation for general crowdsourcing tasks
Data Reduction Based on Hyper Relations
Beyond Binary Preference: Leveraging Bayesian Approaches for Joint Optimization of Ranking and Calibration
Residual Multi-Task Learner for Applied Ranking
Joins that Generalize: Text Classification Using WHIRL
Locality sensitive hash functions based on concomitant rank order statistics
Solar: Science of Entity Loss Attribution
EEG2Rep: Enhancing Self-supervised EEG Representation Through Informative Masked Inputs
A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization
Linearized GMM Kernels and Normalized Random Fourier Features
Debiasing Learning for Membership Inference Attacks Against Recommender Systems
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21)
Maximal Association Rules: A New Tool for Mining for Keyword Co-Occurrences in Document Collections
DivRank: the interplay of prestige and diversity in information networks
Toward Domain-Guided Controllable Summarization of Privacy Policies
Data Paucity and Low Resource Scenarios: Challenges and Opportunities
MLDGG: Meta-Learning for Domain Generalization on Graphs
Understanding Cross-site Linking in Online Social Networks