yusuke1997/dblp-id-title huggingface dataset:
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem
Quick Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms
Debiasing Crowdsourced Batches
A Personalized Automated Bidding Framework for Fairness-aware Online Advertising
Model-based overlapping clustering
Customer Lifetime Value Prediction Using Embeddings
Interestingness of frequent itemsets using Bayesian networks as background knowledge
Beyond Locations: A Motion Range-Aware Similarity Join
Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods
Exploring the community structure of newsgroups
Embedding-based Product Retrieval in Taobao Search
Training structural svms with kernels using sampled cuts
SHALE: an efficient algorithm for allocation of guaranteed display advertising
A simple statistical model and association rule filtering for classification
Disease Propagation in Social Networks: A Novel Study of Infection Genesis and Spread on Twitter
Deep & Cross Network for Ad Click Predictions
Next-generation Intelligent Assistants for Wearable Devices
Handling very large numbers of association rules in the analysis of microarray data
Proxy-Validated Importance-Aware Federated Sample Selection with Meta Learning
Balanced graph edge partition
Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads
Characterizing individual communication patterns
Brain Effective Connectivity Estimation via Fourier Spatiotemporal Attention
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models
Spinning the AI Pinwheel
Detecting Cash-out Users via Dense Subgraphs
Determining an author's native language by mining a text for errors
Local Evaluation of Time Series Anomaly Detection Algorithms
Scalable k -Means Clustering via Lightweight Coresets
Social Skill Validation at LinkedIn
Fast Computation of Kemeny's Constant for Directed Graphs
Online Outlier Exploration Over Large Datasets
CrossLight: Offline-to-Online Reinforcement Learning for Cross-City Traffic Signal Control
EventCube: multi-dimensional search and mining of structured and text data
Multiscale topic tomography
Local Higher-Order Graph Clustering
Topic-level social network search
Inferring Air Quality for Station Location Recommendation Based on Urban Big Data
EFO k -CQA: Towards Knowledge Graph Complex Query Answering beyond Set Operation
An Overview of Issues in Developing Industrial Data Mining and Knowledge Discovery Applications
Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction
The Expressibility of Polynomial based Attention Scheme
Mining optimal decision trees from itemset lattices
Metric@CustomerN: Evaluating Metrics at a Customer Level in E-Commerce
Mobile Access Record Resolution on Large-Scale Identifier-Linkage Graphs
FedGuCci: Making Local Models More Connected in Landscape for Federated Learning
KDD 2024 Special Day - AI for Environment
A Markov chain model for integrating behavioral targeting into contextual advertising
Non-redundant clustering with conditional ensembles
Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization
Doing in One Go: Delivery Time Inference Based on Couriers' Trajectories
The KDD'23 Workshop on Causal Discovery, Prediction and Decision (CDPD 2023)
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models
Modeling User Retention through Generative Flow Networks
TM-LDA: efficient online modeling of latent topic transitions in social media
Towards Robust Prediction on Tail Labels
SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction
Time Critic Policy Gradient Methods for Traffic Signal Control in Complex and Congested Scenarios
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
LLMLight: Large Language Models as Traffic Signal Control Agents
Optimizing Impression Counts for Outdoor Advertising
Sampling of Attributed Networks from Hierarchical Generative Models
Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning
ROLAND: Graph Learning Framework for Dynamic Graphs
Experimenting, Fast and Slow: Bayesian Optimization of Long-term Outcomes with Online Experiments
Tackling Concept Shift in Text Classification using Entailment-style Modeling
Pre-training on Large-Scale Heterogeneous Graph
Polynomial association rules with applications to logistic regression
Bandit based Optimization of Multiple Objectives on a Music Streaming Platform
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising
EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens
Contextual Bandit Applications in a Customer Support Bot
Recent Advances on Graph Analytics and Its Applications in Healthcare
AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space
RayS: A Ray Searching Method for Hard-label Adversarial Attack
Visual Search at eBay
The Fifth International Workshop on Automation in Machine Learning
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space
Debiasing Learning based Cross-domain Recommendation
Understanding captions in biomedical publications
Estimating building simulation parameters via Bayesian structure learning
Data Mining for Typhoon Image Collection
Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing
3D-IDS: Doubly Disentangled Dynamic Intrusion Detection
Xinyu: An Efficient LLM-based System for Commentary Generation
Automated Mining of Structured Knowledge from Text in the Era of Large Language Models
Interleaved Sequence RNNs for Fraud Detection
Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation
Multi-modal Siamese Network for Entity Alignment
Using Recon for Data Cleaning
DynaMMo: mining and summarization of coevolving sequences with missing values
Finding Precursors to Anomalous Drop in Airspeed During a Flight's Takeoff
SympGraph: a framework for mining clinical notes through symptom relation graphs
Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features
ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps
Network flows and the link prediction problem
Triangle listing in massive networks and its applications
Squish: Near-Optimal Compression for Archival of Relational Datasets
SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Predicting Company Quitting From Online Social Enterprise Activity
STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts
Judge Anything: MLLM as a Judge Across Any Modality
Investor-Imitator: A Framework for Trading Knowledge Extraction
Annotation-guided Protein Design with Multi-Level Domain Alignment
Minimizing seed set selection with probabilistic coverage guarantee in a social network
Predicting Disk Replacement towards Reliable Data Centers
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition
Tree based Progressive Regression Model for Watch-Time Prediction in Short-video Recommendation
Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term
Finding effectors in social networks
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
Binary Classifier Evaluation on Unlabeled Segments using Inverse Distance Weighting with Distance Learning
An Efficient and Scalable Algorithm for Estimating Kemeny's Constant of a Markov Chain on Large Graphs
Aggregating Complex Annotations via Merging and Matching
Data-Driven Reserve Prices for Social Advertising Auctions at LinkedIn
Measuring an LLM's Proficiency at using APIs: A Query Generation Strategy
Explaining GNN Explanations with Edge Gradients
SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce
EDISKCO: energy efficient distributed in-sensor-network k-center clustering with outliers
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory
Dirac Delta Regression: Conditional Density Estimation with Clinical Trials
MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories
TrustWalker : a random walk model for combining trust-based and item-based recommendation
A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances
Analyzing the composition of cities using spatial clustering
Scalable Graph Learning for your Enterprise
MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
Compression-Based Evaluation of Partial Determinations
SurfCon: Synonym Discovery on Privacy-Aware Clinical Data
0-Bit Consistent Weighted Sampling
EdgeWatch: Collaborative Investigation of Data Integrity at the Edge based on Blockchain
DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation
Representative Routes Discovery from Massive Trajectories
Do Simpler Models Exist and How Can We Find Them?
A data mining driven risk profiling method for road asset management
Feature selection in unsupervised learning via evolutionary search
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
Coactive Learning for Distributed Data Mining
From Group to Individual Labels Using Deep Features
Spatiotemporal periodical pattern mining in traffic data
Active learning for node classification in assortative and disassortative networks
Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization
TARNet: Task-Aware Reconstruction for Time-Series Transformer
What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?
Trinity: Syncretizing Multi-/Long-Tail/Long-Term Interests All in One
Human Performance on Clustering Web Pages: A Preliminary Study
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data
On Structural Explanation of Bias in Graph Neural Networks
Predicting Path Failure In Time-Evolving Graphs
Generative AI Day
On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions
Active Deep Learning for Activity Recognition with Context Aware Annotator Selection
Estimating rates of rare events with multiple hierarchies through scalable log-linear models
MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge
Certifying and Removing Disparate Impact
TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest
Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization
Stream prediction using a generative model based on frequent episodes in event sequences
Algorithmic techniques for modeling and mining large graphs (AMAzING)
Community-based greedy algorithm for mining top-K influential nodes in mobile social networks
Nonlinear adaptive distance metric learning for clustering
Composing Miners to Develop an Intrusion Detection Solution
FNSPID: A Comprehensive Financial News Dataset in Time Series
HyperLogLogLog: Cardinality Estimation With One Log More
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data
Mining risk patterns in medical data
Environment Agnostic Invariant Risk Minimization for Classification of Sequential Datasets
Maintenance of Discovered Knowledge: A Case in Multi-Level Association Rules
PD-FDS: Purchase Density based Online Credit Card Fraud Detection System
Data-driven text features for sponsored search click prediction
Semi-supervised classification with hybrid generative/discriminative methods
Stream Sampling for Frequency Cap Statistics
Improved Accuracy, Declining Orders: Uncovering the Vicious Competition Trap in Multi-Domain Recommendation
Learning to question: leveraging user preferences for shopping advice
Mining massively incomplete data sets by conceptual reconstruction
Malicious Code Detection Using Active Learning
Choice Set Confounding in Discrete Choice
Auditing Data Provenance in Text-Generation Models
Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation
Correlating synchronous and asynchronous data streams
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank
Multiview Clustering via Adaptively Weighted Procrustes
Maintaining connected components for infinite graph streams
Defining diff as a Data Mining Primitive
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning
RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks
An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
Efficient Exploration of the Rashomon Set of Rule-Set Models
GradMask: Gradient-Guided Token Masking for Textual Adversarial Example Detection
Open-domain quantity queries on web tables: annotation, response, and consensus models
Towards Deeper Graph Neural Networks
Efficient computations via scalable sparse kernel partial least squares and boosted latent features
XAI for Predictive Maintenance
Mining concept-drifting data streams using ensemble classifiers
On the Scalability of Temporal Relative Positional Encoding for Dynamic Link Prediction
Constructing popular routes from uncertain trajectories
Enterprise Cooperation and Competition Analysis with a Sign-Oriented Preference Network
Preemptive Detection of Fake Accounts on Social Networks via Multi-Class Preferential Attachment Classifiers
TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme
Mining Research Communities in Bibliographical Data
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications
Deep Adversarial Learning for Multi-Modality Missing Data Completion
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense Evaluation
TUBE: Embedding Behavior Outcomes for Predicting Success
CURE: A dataset for Clinical Understanding & Retrieval Evaluation
PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering
Partial Label Dimensionality Reduction via Confidence-Based Dependence Maximization
Balancing Approach for Causal Inference at Scale
AntAkso: Claims Management System for Health Insurance in Alipay
Mining evolutionary multi-branch trees from text streams
SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation
Exploring human movements in Singapore: a comparative analysis based on mobile phone and taxicab usages
InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity
Identifying Distinctive Subsequences in Multivariate Time Series by Clustering
Asymmetric Transitivity Preserving Graph Embedding
Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment
MEDS: Building Models and Tools in a Reproducible Health AI Ecosystem
Predictive modeling in automotive direct marketing: tools, experiences and open issues
GeoMix: Towards Geometry-Aware Data Augmentation
Driving with knowledge from the physical world
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021
Coresets for Kernel Regression
LeapAttack: Hard-Label Adversarial Attack on Text via Gradient-Based Optimization
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
Review spam detection via temporal pattern discovery
FEMA: flexible evolutionary multi-faceted analysis for dynamic behavioral pattern discovery
Towards the D-Optimal Online Experiment Design for Recommender Selection
Achieving a Better Tradeoff in Multi-stage Recommender Systems through Personalization
Extending Naïve Bayes Classifiers Using Long Itemsets
Continuous Treatment Effect Estimation via Generative Adversarial De-confounding
Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation
GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
Large-scale learning of word relatedness with constraints
Stochastic Diffusion: A Diffusion Based Model for Stochastic Time Series Forecasting
Crime Rate Inference with Big Data
Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction
Embedding Two-View Knowledge Graphs with Class Inheritance and Structural Similarity
Global Self-Attention as a Replacement for Graph Convolution
Sketch-Based Replay Projection for Continual Learning
TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer
Using retrieval measures to assess similarity in mining dynamic web clickstreams
Learning to Bid the Interest Rate in Online Unsecured Personal Loans
Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series
DPHGNN: A Dual Perspective Hypergraph Neural Networks
A Truth Discovery Approach with Theoretical Guarantee
From Large to Huge: A Statistician's Reactions to KDD & DM
Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones
Clustering Labeled Data and Cross-Validation for Classification with Few Positives in Yeast
VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection
Predicting the Political Sentiment of Web Log Posts Using Supervised Machine Learning Techniques Coupled with Feature Selection
Exploiting Relation-aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning
Monitoring Robustness and Individual Fairness
MetaPAD: Meta Pattern Discovery from Massive Text Corpora
EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs
Computational Drug Repositioning Using Continuous Self-Controlled Case Series
OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning
Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks
XRules: an effective structural classifier for XML data
Asynchronous Vertical Federated Learning for Kernelized AUC Maximization
TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding
An Embedding Learning Framework for Numerical Features in CTR Prediction
Applications of generalized support vector machines to predictive modeling
Natural Language Explainable Recommendation with Robustness Enhancement
Low rank modeling of signed networks
Proceedings of the ACM SIGKDD Workshop on Statistical and Relational Learning in Bioinformatics, Paris, France, June 28, 2009
Big data, big business: bridging the gap
Classify By Representative Or Associations (CBROA): a hybrid approach for image classification
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries
Practical Machine Learning for Streaming Data
Integrity Authentication in Tree Models
Detecting abnormal coupled sequences and sequence changes in group-based manipulative trading behaviors
Tuning representations of dynamic network data
GeoTS: A TSC Framework for Estimating Geological Formation to Model Carbon Storage Reservoirs
Dispatch with Confidence: Integration of Machine Learning, Optimization and Simulation for Open Pit Mines
User Modeling in Telecommunications and Internet Industry
Breeding-aware Revenue Maximization for NFT Viral Marketing on Social Networks
Forex-foreteller: currency trend modeling using news articles
Mining correlated bursty topic patterns from coordinated text streams
INCONCO: interpretable clustering of numerical and categorical objects
Network anomaly detection based on Eigen equation compression
Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification
Information resonance on Twitter: watching Iran
Improving Conversational Recommendation Systems via Counterfactual Data Simulation
Advancing Graph Foundation Models: A Data-Centric Perspective
WhyFlow: Explaining Errors in Data Flows Interactively
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings
HUGE: Huge Unsupervised Graph Embeddings with TPUs
Query-driven discovery of semantically similar substructures in heterogeneous networks
Big & personal: data and models behind netflix recommendations
MicroscopeSketch: Accurate Sliding Estimation Using Adaptive Zooming
MOLIERE: Automatic Biomedical Hypothesis Generation System
Fast and Robust Parallel SGD Matrix Factorization
ROMA: Recommendation-Oriented Language Model Adaptation Using Multi-Modal Multi-Domain Item Sequences
Constrained optimization for validation-guided conditional random field learning
Hierarchical Gating Networks for Sequential Recommendation
Privacy preserving mining of association rules
Multiple sensor integration for indoor surveillance
Deep Learning for Industrial AI: Challenges, New Methods and Best Practices
Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena
Applications of data mining and machine learning in online customer care
UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs
Unbiased online active learning in data streams
Expertise modeling for matching papers with reviewers
Understanding evolution of research themes: a probabilistic generative model for citations
GREAT: Guiding Query Generation with a Trie for Recommending Related Search about Video at Kuaishou
Local Algorithms for Estimating Effective Resistance
Customized reviews for small user-databases using iterative SVD and content based filtering
A Neuro-Symbolic Approach to Symbol Grounding for ALC-Ontologies
SVM pAUC tight : a new support vector method for optimizing partial AUC based on a tight convex upper bound
Detecting Interpretable Subgroup Drifts
Smart Roles: Inferring Professional Roles in Email Networks
HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback
Ads Allocation in Feed via Constrained Optimization
Democrats, republicans and starbucks afficionados: user classification in twitter
Multi-Scale Detection of Anomalous Spatio-Temporal Trajectories in Evolving Trajectory Datasets
Deep Learning Embeddings for Data Series Similarity Search
Proceedings of the ACM SIGKDD Workshop on Knowledge-infused Mining and Learning for Social Impact co-located with 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Virtual) (SIGKDD 2020), San Diego, California, USA, August 24, 2020
Utilizing temporal patterns for estimating uncertainty in interpretable early decision making
Experience Speaks Louder: Black-box Hard-label Adversarial Attack through Reinforcement Learning
Privileged Features Distillation at Taobao Recommendations
Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks
Discovering Roll-Up Dependencies
Probabilistic query models for transaction data
Mining complex models from arbitrarily large databases in constant time
Improving Recommendation Quality in Google Drive
Tagmark: reliable estimations of RFID tags for business processes
Fairness in Networks: Social Capital, Information Access, and Interventions
Click shaping to optimize multiple objectives
Domain Adaptation with Dynamic Open-Set Targets
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks