yusuke1997/dblp-id-title huggingface dataset:
Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency Perspective
Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck
Scenario Shared Instance Modeling for Click-through Rate Prediction
De-duping URLs via rewrite rules
Hyperparametric Influence Minimization: Feature-Driven Intervention Beyond Blocking
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2013, Chicago, IL, USA, August 11, 2013
Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting
Range-limited Augmentation for Few-shot Learning in Tabular Data with Comprehensive Benchmark
GEO: Generative Engine Optimization
ADMIRE: ADaptive method to enhance Multiple Image REsolutions in text-rich multi-image understanding
The anatomy of a multimodal information filter
Approaches to Online Learning and Concept Drift for User Identification in Computer Security
Subspace Clustering Using Log-determinant Rank Approximation
Improving the Quality of Explanations with Local Embedding Perturbations
Dynamically Modeling Patient's Health State from Electronic Medical Records: A Time Series Approach
A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation
Absolute Fused Lasso and Its Application to Genome-Wide Association Studies
Understanding the Role of Style in E-commerce Shopping
Understanding Inter-Session Intentions via Complex Logical Reasoning
DeepInf: Social Influence Prediction with Deep Learning
Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication
On the tradeoff between privacy and utility in data publishing
Unsupervised transfer classification: application to text categorization
A Transformer-based Framework for Multivariate Time Series Representation Learning
Cross-sell: a fast promotion-tunable customer-item recommendation method based on conditionally independent probabilities
Web-Scale Academic Name Disambiguation: The WhoIsWho Benchmark, Leaderboard, and Toolkit
Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts
Latent association analysis of document pairs
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem
Recurrent Networks for Guided Multi-Attention Classification
A Free Energy Based Approach for Distance Metric Learning
EGM: Enhanced Graph-based Model for Large-scale Video Advertisement Search
RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning
Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models
Learning-to-Ask: Knowledge Acquisition via 20 Questions
Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach
Real-time On-Device Troubleshooting Recommendation for Smartphones
Stabilising Job Survival Analysis for Disability Employment Services in Unseen Environments
Graph Convolutional Networks with EigenPooling
Optimizing web traffic via the media scheduling problem
Missing Value Imputation for Mixed Data via Gaussian Copula
Active collaborative permutation learning
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation
Evaluating U.S. Electoral Representation with a Joint Statistical Model of Congressional Roll-Calls, Legislative Text, and Voter Registration Data
Debiasing Grid-based Product Search in E-commerce
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023
Learning Class-Conditional GANs with Active Sampling
Identifying graphs from noisy and incomplete data
Gibbs Collapsed Sampling for Latent Dirichlet Allocation on Spark
The Hitchhikers Guide to Production-ready Trustworthy Foundation Model Powered Software (FMware)
Parallel Sequence Mining on Shared-Memory Machines
Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments
Maximum inner-product search using cone trees
Model-based kernel for efficient time series analysis
A fast kernel-based multilevel algorithm for graph clustering
Community detection in graphs through correlation
Structured entity identification and document categorization: two tasks with one joint model
Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers
A Fraudulent Blind Shipment Detection Framework in Logistics
Machine Learning Software in Practice: Quo Vadis?
Large scale predictive modeling for micro-simulation of 3G air interface load
Abstractive Summarization of Spoken and Written Instructions with BERT
Scalable Algorithms for Mining Large Databases
Mining from open answers in questionnaire data
Redundancy-Free Computation for Graph Neural Networks
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Intrinsic-Motivated Sensor Management: Exploring with Physical Surprise
Activity-edge centric multi-label classification for mining heterogeneous information networks
EventSearch: a system for event discovery and retrieval on multi-type historical data
MFMS: maximal frequent module set mining from multiple human gene expression data sets
Finding tribes: identifying close-knit individuals from employment patterns
Adaptation Algorithm and Theory Based on Generalized Discrepancy
Modern Theoretical Tools for Designing Information Retrieval System
LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models
Time-varying learning and content analytics via sparse factor analysis
Optuna: A Next-generation Hyperparameter Optimization Framework
Structural Neighborhood Based Classification of Nodes in a Network
Dynamic Hotel Pricing at Online Travel Platforms: A Popularity and Competitiveness Aware Demand Learning Approach
Mining distance-based outliers from large databases in any metric space
AI for Small Businesses and Consumers: Applications and Innovations
FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks
Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling
Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure
Disturbance Grassmann Kernels for Subspace-Based Learning
Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction
Data Science from the Lab to the Field to the Enterprise
Directional Multivariate Ranking
Adaptive collective routing using gaussian process dynamic congestion models
Empowering authors to diagnose comprehension burden in textbooks
Ranking-based clustering of heterogeneous information networks with star network schema
Fine-grained Urban Heat Island Effect Forecasting: A Context-aware Thermodynamic Modeling Framework
Predictive Data Mining with Finite Mixtures
Anytime Algorithms for Approximate Functional Dependencies
GPE: Global Position Embedding for Trajectory Similarity Computation
Towards bounding sequential patterns
Analytical Techniques for Anomaly Detection Through Features, Signal-Noise Separation and Partial-Value Association
Making Web Servers Pushier
NetTrans: Neural Cross-Network Transformation
Optimal Action Extraction for Random Forests and Boosted Trees
Supervised deep learning with auxiliary networks
Real-time bidding algorithms for performance-based display ad allocation
Robust sparse estimation of multiresponse regression and inverse covariance matrix via the L2 distance
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning
Contrastive Multi-View Multiplex Network Embedding with Applications to Robust Network Alignment
The complexity of mining maximal frequent itemsets and maximal frequent patterns
Paper Matching with Local Fairness Constraints
Monitoring Incremental Histogram Distribution for Change Detection in Data Streams
Learning to Schedule in Diffusion Probabilistic Models
Semantic search and a new moore's law effect in knowledge engineering
Cartesian contour: a concise representation for a collection of frequent sets
Scaling up dynamic time warping for datamining applications
Detail and Context in Web Usage Mining: Coarsening and Visualizing Sequences
Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution
A dirichlet multinomial mixture model-based approach for short text clustering
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting
LLMs Are Noisy Oracles! LLM-based Noise-aware Graph Active Learning for Node Classification
Online multiscale dynamic topic models
Towards exploratory test instance specific algorithms for high dimensional classification
Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations
In and Out: Optimizing Overall Interaction in Probabilistic Graphs under Clustering Constraints
AntiPhish: lessons learnt
Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-level Anomaly Detection
Mining broad latent query aspects from search sessions
Numerical Tuple Extraction from Tables with Pre-training
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction
Budget pacing for targeted online advertisements at LinkedIn
Interaction and collective intelligence in internet computing
On Dynamic Network Models and Application to Causal Impact
Using relational knowledge discovery to prevent securities fraud
A Process-Aware Decision Support System for Business Processes
Information diffusion and external influence in networks
Compressive Meta-Learning
Reinforcement Learning-based Placement of Charging Stations in Urban Road Networks
Predicting the present with search engine data
Query clustering based on bid landscape for sponsored search auction optimization
MetaEformer: Unveiling and Leveraging Meta-Patterns for Complex and Dynamic Systems Load Forecasting
Fair and Interpretable Models for Survival Analysis
Loss or Gain: Hierarchical Conditional Information Bottleneck Approach for Incomplete Time Series Classification
Interpretable Drug Response Prediction using a Knowledge-based Neural Network
H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks
Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time
An inductive database prototype based on virtual mining views
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations
Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning
Reducing the human overhead in text categorization
User Concept Pattern Discovery Using Relevance Feedback And Multiple Instance Learning For Content-Based Image Retrieval
Toast: Task-Oriented Multi-dimensional Augmentation for Spatio-Temporal Trajectory Data
Diagnosing memory leaks using graph mining on heap dumps
Empirical study of topic modeling in Twitter
Raising the baseline for high-precision text classifiers
Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation
On Sampled Metrics for Item Recommendation
Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking
Linear prediction models with graph regularization for web-page categorization
Representation Learning on Knowledge Graphs for Node Importance Estimation
Not All Passes Are Created Equal: Objectively Measuring the Risk and Reward of Passes in Soccer from Tracking Data
Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection
Controllable Multi-Objective Re-ranking with Policy Hypernetworks
Graph Evidential Learning for Anomaly Detection
MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data
Bayes net graphs to understand co-authorship networks?
Notification Volume Control and Optimization System at Pinterest
MultiSage: Empowering GCN with Contextualized Multi-Embeddings on Web-Scale Multipartite Networks
DisenQNet: Disentangled Representation Learning for Educational Questions
Comparing graph-based representations of protein for mining purposes
Boosting for Text Classification with Semantic Features
WhereNext: a location predictor on trajectory pattern mining
A Hands-on Introduction to Time Series Classification and Regression
High performance data mining (tutorial PM-3)
Mining High-Level User Concepts with Multiple Instance Learning and Relevance Feedback for Content-Based Image Retrieval
Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling
The community-search problem and how to plan a successful cocktail party
CoCo: coding cost for parameter-free outlier detection
Neighbor query friendly compression of social networks
Smoothing techniques for adaptive online language models: topic tracking in tweet streams
Packet Representation Learning for Traffic Classification
Web-Scale Generic Object Detection at Microsoft Bing
Evolutionary spectral clustering by incorporating temporal smoothness
The future of image search
Interpretable Boosted Naïve Bayes Classification
TIARA: a visual exploratory text analytic system
Knowledge Graph Reasoning over Entities and Numerical Values
Reconstructing an Epidemic Over Time
Multi-Task Learning via Generalized Tensor Trace Norm
Building semantic kernels for text classification using wikipedia
The PlaceIQ Analytic Platform: Location Oriented Approaches to Mobile Audiences
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
Non-autoregressive Generative Models for Reranking Recommendation
Process-Based Database Support for the Early Indicator Method
Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation
Maximizing Cumulative User Engagement in Sequential Recommendation: An Online Optimization Perspective
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms
Using Metagueries to Integrate Inductive Learning and Deductive Database Technology
Robust Influence Maximization
Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph
Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
DAG: Deep Adaptive and Generative K -Free Community Detection on Attributed Graphs
FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation
Revisiting Clustering of Neural Bandits: Selective Reinitialization for Mitigating Loss of Plasticity
An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs
Labeled topic detection of open source software from mining mass textual project profiles
Surface-based Molecular Design with Multi-modal Flow Matching
Analysing Rock Samples for the Mars Lander
Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding with LLMs
Partial example acquisition in cost-sensitive learning
A Tutorial on Multi-Armed Bandit Applications for Large Language Models
Filtration Curves for Graph Representation
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision
The cost of privacy: destruction of data-mining utility in anonymized data publishing
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
Toward the Integration of Exploration and Modeling in a Planning Framework
Model-Based Counterfactual Synthesizer for Interpretation
Hierarchical Invariant Learning for Domain Generalization Recommendation
Advances in Web Mining and Web Usage Analysis, 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers
Transitive Transfer Learning
Entropy in Legal Language
Personalized search result diversification via structured learning
150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com
Semi-supervised approach to rapid and reliable labeling of large data sets
Experimental design for solicitation campaigns
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology
A review of urban computing for mobile phone traces: current methods, challenges and opportunities
Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance
Retrieving Intent-covering Demonstrations for Clarification Generation in Conversational Search Systems
PageRank on an evolving graph
Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization
Days on Market: Measuring Liquidity in Real Estate Markets
Planning Tasks for Knowledge Discovery in Databases; Performing Task-Oriented User-Guidance
Network science: an introduction to recent statistical approaches
Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints
Undiscovered Public Knowledge: A Ten-Year Update
Efficiently mining frequent trees in a forest
Extraction of Spatial Proximity Patterns by Concept Generalization
Dimension induced clustering
k-Support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining
Mining top-n local outliers in large databases
Evaluating the novelty of text-mined rules using lexical knowledge
Topics over time: a non-Markov continuous-time model of topical trends
Mining the stock market (extended abstract): which measure is best?
Clustering based large margin classification: a scalable approach using SOCP formulation
Data-driven Simulation and Optimization for Covid-19 Exit Strategies
Data Mining for Diagnostic Debugging in Sensor Networks: Preliminary Evidence and Lessons Learned
Online Asymmetric Active Learning with Imbalanced Data
GiveALink: mining a semantic network of bookmarks for web search and recommendation
Preference Ontologies based on Social Media for compensating the Cold Start Problem
Data mining at NASA: from theory to applications
Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance
Pretraining Representations of Multi-modal Multi-query E-commerce Search
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
Robustness Certification for Structured Prediction with General Inputs via Safe Region Modeling in the Semimetric Output Space
A multi-relational approach to spatial classification
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
CLOPE: a fast and effective clustering algorithm for transactional data
SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking
3DGraphX: Explaining 3D Molecular Graph Models via Incorporating Chemical Priors
Cascading outbreak prediction in networks: a data-driven approach
Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction
FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents
A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
Unsupervised clustering of multidimensional distributions using earth mover distance
Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters
Embedding-based News Recommendation for Millions of Users
Unveiling Fake Accounts at the Time of Registration: An Unsupervised Approach
LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models
Signed Graph Neural Network with Latent Groups
OPORP: One Permutation + One Random Projection
A Quasi-experimental Estimate of the Impact of P2P Transportation Platforms on Urban Consumer Patterns
MetricPrompt: Prompting Model as a Relevance Metric for Few-shot Text Classification
ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM
Inferring Networks of Substitutable and Complementary Products
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
Extracting relevant named entities for automated expense reimbursement
VertiMRF: Differentially Private Vertical Federated Data Synthesis
Personalized PageRank to a Target Node, Revisited
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs
Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis
Bayesian Optimization for Simultaneous Selection of Machine Learning Algorithms and Hyperparameters on Shared Latent Space
Active search on graphs
LikeMiner: a system for mining the power of 'like' in social media networks
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback
Tensorized Unaligned Multi-view Clustering with Multi-scale Representation Learning
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, Boston, MA, USA, August 20-23, 2000
Tutorial Notes for ACM SIGKDD 1999 International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 15-18, 1999
Maximizing Influence of Leaders in Social Networks
Workshop on Model Mining
SatHealth: A Multimodal Public Health Dataset with Satellite-based Environmental Factors
Efficient and effective explanation of change in hierarchical summaries
Exploring the Potential of Foundation Models as Reliable AI Contact Centers
ANF: a fast and scalable tool for data mining in massive graphs
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
Towards Controllable Hybrid Fairness in Graph Neural Networks
Massively parallel expectation maximization using graphics processing units
Multimedia Support for Complex Multidimensional Data Mining
Multimodal AutoML for Image, Text and Tabular Data
Multimodal Sentiment Analysis To Explore the Structure of Emotions
Unsupervised deduplication using cross-field dependencies
Next-Step Suggestions for Modern Interactive Data Analysis Platforms
MT-FlowFormer: A Semi-Supervised Flow Transformer for Encrypted Traffic Classification
Solving regression problems with rule-based ensemble classifiers
Multimodal Machine Learning for Video and Image Analysis
GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing
Diversified Temporal Subgraph Pattern Mining
New Frontiers of Scientific Text Mining: Tasks, Data, and Tools
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction
Hypothesis Testing and Statistically-sound Pattern Mining
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
Heterogeneous Contrastive Learning for Foundation Models and Beyond
Visual Classification: An Interactive Approach to Decision Tree Construction
Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data
A Predict-Then-Optimize Couriers Allocation Framework for Emergency Last-mile Logistics
Modern MDL meets Data Mining Insights, Theory, and Practice
Co-clustering documents and words using bipartite spectral graph partitioning
Actions Speak Louder than Goals: Valuing Player Actions in Soccer
RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads
Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree
Modeling disease progression via fused sparse group lasso
Stable feature selection via dense feature groups
Distributed classification in peer-to-peer networks