yusuke1997/dblp-id-title huggingface dataset:
STARLINE: Contrastive Learning with Modality-Aware Graph Refinement for Effective Multimedia Recommendation
Cluster-Reduce: Compressing Sketches for Distributed Data Streams
Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications
Real-Time Rideshare Driver Supply Values Using Online Reinforcement Learning
Improving Task-Oriented Dialogue Systems In Production with Conversation Logs
Device-Cloud Collaborative Learning for Recommendation
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring
Attentive Heterogeneous Graph Embedding for Job Mobility Prediction
Exact-K Recommendation via Maximal Clique Optimization
Graph Foundation Models: Challenges, Methods, and Open Questions
Wind Farm Layout Optimization with Diffusion Models
GPT-GNN: Generative Pre-Training of Graph Neural Networks
A tool for collecting provenance data in social media
MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance
DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection
Almost linear-time algorithms for adaptive betweenness centrality using hypergraph sketches
Personalized Federated Learning with Parameter Propagation
Enabling Collaborative Test-Time Adaptation in Dynamic Environment via Federated Learning
Graph Cross Supervised Learning via Generalized Knowledge
Online Influence Maximization
Multi-view Denoising Graph Auto-Encoders on Heterogeneous Information Networks for Cold-start Recommendation
Evaluating Decision Rules Across Many Weak Experiments
Using structure indices for efficient approximation of network properties
Log-based predictive maintenance
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection
Estimating individual-level optimal causal interventions combining causal models and machine learning models
Reducing the Friction for Building Recommender Systems with Merlin
Node Similarity with q -Grams for Real-World Labeled Networks
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
Style in the long tail: discovering unique interests with latent variable models in large scale social E-commerce
Addressing Challenges with Big Data for Media Measurement
Algorithmic Decision Making with Conditional Fairness
Network Lasso: Clustering and Optimization in Large Graphs
Real-time risk control system for CNP (card not present)
PEMBOT: Pareto-Ensembled Multi-task Boosted Trees
Variations on Multimedia Data Mining
Independence Diagrams: A Technique for Visual Data Mining
Sparx: Distributed Outlier Detection at Scale
A Data-Clustering Algorithm on Distributed Memory Multiprocessors
Extracting Relevant Information from User's Utterances in Conversational Search and Recommendation
Three-Stage Root Cause Analysis for Logistics Time Efficiency via Explainable Machine Learning
Utilizing Strategic Pre-training to Reduce Overfitting: Baguan - A Pre-trained Weather Forecasting Model
User-tag Profile Modeling in Recommendation System via Contrast Weighted Tag Masking
Network structural analysis via core-tree-decomposition Publication of this article pending inquiry
Identifying Knowledge Editing Types in Large Language Models
epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery
Causal and Interpretable Rules for Time Series Analysis
Doubly Robust AUC Optimization against Noisy and Adversarial Samples
RT-VeD: Real-Time VoI Detection on Edge Nodes with an Adaptive Model Selection Framework
Stable Representation Learning on Graphs from Multiple Environments with Structure Distribution Shift
Offline Imitation Learning with Model-based Reverse Augmentation
Discovering Invariant and Changing Mechanisms from Data
AliCoCo2: Commonsense Knowledge Extraction, Representation and Application in E-commerce
PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks
XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation
Proceedings of the 3rd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2014, New York City, USA, August 24, 2014
Seeing the Unseen in Micro-Video Popularity Prediction: Self-Correlation Retrieval for Missing Modality Generation
Certified Edge Unlearning for Graph Neural Networks
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations
Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information
GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems
Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search
Overview of ACM SIGKDD 2024 AI4Science4AI Special Day
LPFormer: An Adaptive Graph Transformer for Link Prediction
Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems
Simulating the Impact of Hospital Capacity and Social Isolation to Minimize the Propagation of Infectious Diseases
Proceedings of the 2nd ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2002), July 23rd, 2002, Edmonton, Alberta, Canada
Topology-aware Embedding Memory for Continual Learning on Expanding Networks
Hierarchical Taxonomy Aware Network Embedding
CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution
20th International Workshop on Data Mining in Bioinformatics (BIOKDD 2021)
Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression
Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training?
A Guided Tour through the Data Mining Jungle
Fairness-Aware Graph Learning: A Benchmark
Revenue optimization with relevance constraint in sponsored search
An improved GLMNET for l1-regularized logistic regression
2D-interval predictions for time series
Scalable robust covariance and correlation estimates for data mining
CAT: Interpretable Concept-based Taylor Additive Models
Designing Neural Networks from Statistical Models: A New Approach to Data Exploration
Estimating entity importance via counting set covers
A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior
TUTA: Tree-based Transformers for Generally Structured Table Pre-training
Fast query execution for retrieval models based on path-constrained random walks
Learning to trade off between exploration and exploitation in multiclass bandit prediction
Online allocation of display ads with smooth delivery
Leveraging Model Inherent Variable Importance for Stable Online Feature Selection
Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction
Geography-Aware Sequential Location Recommendation
Towards Learning from User Feedback for Ontology-based Information Extraction
Towards the Personalization of Algorithms Evaluation in Data Mining
Analytical view of business data
Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19
Frontiers in E-commerce personalization
GROOT: Effective Design of Biological Sequences with Limited Experimental Data
Semantic representation: search and mining of multimedia content
An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems
A Recommender System Based on Local Random Walks and Spectral Methods
EvaPlanner: an evacuation planner with social-based flocking kinetics
Refining Labeling Functions with Limited Labeled Data
AutoWebGLM: A Large Language Model-based Web Navigating Agent
ReasoNet: Learning to Stop Reading in Machine Comprehension
Data Science and Artificial Intelligence for Responsible Recommendations
Cracking Tabular Presentation Diversity for Automatic Cross-Checking over Numerical Facts
Unsupervised Clinical Language Translation
It Takes More than Math and Engineering to Hit the Bullseye with Data
Mining WWW Access Sequence by Matrix Clustering
SIPF: Sampling Method for Inverse Protein Folding
SimRank: a measure of structural-context similarity
Beimingwu: A Learnware Dock System
Internal Logical Induction for Pixel-Symbolic Reinforcement Learning
A probabilistic model for multimodal hash function learning
User position measures in social networks
The 4 th Workshop on Artificial Intelligence-enabled Cybersecurity Analytics
Gaussian multiple instance learning approach for mapping the slums of the world using very high resolution imagery
A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection
Detecting bots via incremental LS-SVM learning with dynamic feature adaptation
Classifying and Counting with Recurrent Contexts
E-commerce in Your Inbox: Product Recommendations at Scale
Shallow and Deep Non-IID Learning on Complex Data
Connecting Low-Loss Subspace for Personalized Federated Learning
Mining Significant Usage Patterns from Clickstream Data
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
UrbanFM: Inferring Fine-Grained Urban Flows
FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs
An architecture for detecting events in real-time using massive heterogeneous data sources
Deriving quantitative models for correlation clusters
Graph Learning with Distributional Edge Layouts
GEA: A Toolkit for Gene Expression Analysis
Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias
AutoShard: Automated Embedding Table Sharding for Recommender Systems
Mining multi-faceted overviews of arbitrary topics in a text collection
Task Relation-aware Continual User Representation Learning
Text classification, business intelligence, and interactivity: automating C-Sat analysis for services industry
Bringing Multimodality to Amazon Visual Search System
Classification with partial labels
Off-policy Bandits with Deficient Support
Deriving Queries from Results Using Genetic Programming
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning
RAPT: Pre-training of Time-Aware Transformer for Learning Robust Healthcare Representation
Handling missing values and censored data in PCA of pharmacological matrices
CLARA: Confidence of Labels and Raters
From Deep Learning to Deep Reasoning
Generative AI in E-Commerce: What Can We Expect?
Factorized sparse learning models with interpretable high order feature interactions
Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution
DIRT @SBT@discovery of inference rules from text
Multi-Grained Multimodal Interaction Network for Entity Linking
AGS-GNN: Attribute-guided Sampling for Graph Neural Networks
ProCom: A Few-shot Targeted Community Detection Algorithm
A principled and flexible framework for finding alternative clusterings
Online Transfer Learning for Concept Drifting Data Streams
Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs
Exploiting user clicks for automatic seed set generation for entity matching
MGS3: A Multi-Granularity Self-Supervised Code Search Framework
Learning from Labeled and Unlabeled Vertices in Networks
Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks
Automatic mining of fruit fly embryo images
Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework
Individual Fairness for Graph Neural Networks: A Ranking based Approach
Temporal Graph Learning Workshop
A Causal Look at Statistical Definitions of Discrimination
Factoring past exposure in display advertising targeting
Dual Averaging Method for Online Graph-structured Sparsity
CompanyDepot: Employer Name Normalization in the Online Recruitment Industry
Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors - Algorithm and Application
On community detection in real-world networks and the importance of degree assortativity
Context-aware Event Forecasting via Graph Disentanglement
Active Mining in a Distributed Setting
Advances in Cost-sensitive Multiclass and Multilabel Classification
Multi-view transfer learning with a large margin approach
Mining web logs for prediction models in WWW caching and prefetching
DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation
Compact and Scalable Graph Neighborhood Sketching
Dense itemsets
Efficient mining of weighted association rules (WAR)
Explaining Potentially Unfair Clauses to the Consumer with the CLAUDETTE tool
Bridging Offline-Online Evaluation with a Time-dependent and Popularity Bias-free Offline Metric for Recommenders
Causal Attention for Interpretable and Generalizable Graph Classification
Unsupervised Graph Clustering with Deep Structural Entropy
Predicting Locations Using Map Similarity(PLUMS): A Framework for Spatial Data Mining
VisRel: Media Search at Scale
Graph and Geometry Generative Modeling for Drug Discovery
HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records
Interpretable Knowledge Discovery Reinforced by Visual Methods
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy
Collaborative topic modeling for recommending scientific articles
Textual Evidence for the Perfunctoriness of Independent Medical Reviews
Deep Pipeline Embeddings for AutoML
Learning from crowds in the presence of schools of thought
concept2code: Deep Reinforcement Learning for Conversational AI
Motif Prediction with Graph Neural Networks
Interactive Causal Structure Discovery in Earth System Sciences
Cleaning disguised missing data: a heuristic approach
Mining Association Rules in Hypertext Databases
LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?
Adaptive event detection with time-varying poisson processes
A Scalable and Plug-in Based System to Construct A Production-Level Knowledge Base
Hardness-aware Privileged Features Distillation with Latent Alignment for CVR Prediction
CrowdQuake: A Networked System of Low-Cost Sensors for Earthquake Detection via Deep Learning
Genome scale prediction of protein functional class from sequence using data mining
Defection detection: using activity profiles to predict ISP customer vulnerability
Effective label acquisition for collective classification
Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay
Real-Time Optimization of Web Publisher RTB Revenues
A framework to support multiple query optimization for complex mining tasks
Roadside Multi-LiDAR Data Fusion for Enhanced Traffic Safety
Detecting Network Effects: Randomizing Over Randomized Experiments
Domain-Specific Risk Minimization for Domain Generalization
Causal Subgraph Learning for Generalizable Inductive Relation Prediction
Up next: retrieval methods for large scale related video suggestion
Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques
Suppressing model overfitting in mining concept-drifting data streams
Can complex network metrics predict the behavior of NBA teams?
Time-Aware Attention-Based Transformer (TAAT) for Cloud Computing System Failure Prediction
Discovering additive structure in black box functions
Adaptive Query Processing for Time-Series Data
A unified approach for schema matching, coreference and canonicalization
Graph Classification using Structural Attention
SQR: Balancing Speed, Quality and Risk in Online Experiments
MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning
PraFFL: A Preference-Aware Scheme in Fair Federated Learning
Carousel Ads Optimization in Yahoo Gemini Native
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
The Limits of Popularity-Based Recommendations, and the Role of Social Ties
BacktrackSTL: Ultra-Fast Online Seasonal-Trend Decomposition with Backtrack Technique
Towards Privacy-Preserving Model Selection
AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba
DI-2021: The Second Document Intelligence Workshop
When Graph Meets Multimodal: Benchmarking and Meditating on Multimodal Attributed Graph Learning
Fast One-class Classification using Class Boundary-preserving Random Projections
Theory meets Practice at the Median: A Worst Case Comparison of Relative Error Quantile Algorithms
Condensing Graphs via One-Step Gradient Matching
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma
Towards Explanation of DNN-based Prediction with Guided Feature Inversion
Deep Learning for Network Traffic Data
On the Generative Discovery of Structured Medical Knowledge
Classification of functional magnetic resonance imaging data using informative pattern features
Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation
Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks
KDD Workshop on Machine Learning in Finance
Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering
Scaling out big data missing value imputations: pythia vs. godzilla
A Decision Tree Framework for Spatiotemporal Sequence Prediction
Filling context-ad vocabulary gaps with click logs
A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation and Segment Labeling
Outlier detection by active learning
Deep Design: Product Aesthetics for Heterogeneous Markets
Interpreting Trajectories from Multiple Views: A Hierarchical Self-Attention Network for Estimating the Time of Arrival
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records
Semi-Supervised Generative Adversarial Network for Gene Expression Inference
Causal Estimation of Exposure Shifts with Neural Networks and an Application to Inform Air Quality Standards in the US
Large-Scale Graph Neural Networks: The Past and New Frontiers
HiBench: Benchmarking LLMs Capability on Hierarchical Structure Reasoning
Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts
Energy-Based Models for Predicting Mutational Effects on Proteins
Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics
BigIN4: Instant, Interactive Insight Identification for Multi-Dimensional Big Data
Designing AI at Scale to Power Everyday Life
Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering
Identifying domain expertise of developers from source code
Social sampling
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification
Let's See Your Digits: Anomalous-State Detection using Benford's Law
An Intelligent Customer Care Assistant System for Large-Scale Cellular Network Diagnosis
Cancer genomics
Position-Aware Neighbor Aggregation for Dynamic Link Prediction
metapath2vec: Scalable Representation Learning for Heterogeneous Networks
Triangle-aware Spectral Sparsifiers and Community Detection
Optimizing Marketing Impact through Data Driven Decisioning
PyHealth: A Deep Learning Toolkit for Healthcare Applications
Interactive Analysis of Gene Interactions Using Graphical gaussian model
Randomized Experimental Design via Geographic Clustering
Analysis of Faces in a Decade of US Cable TV News
Enhancing Text-Based Hierarchical Multilabel Classification for Mobile Applications via Contrastive Learning
Assessing Human Error Against a Benchmark of Perfection
Recommender systems in commerce and community
Active Deep Learning to Tune Down the Noise in Labels
Latent Space Model for Road Networks to Predict Time-Varying Traffic
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors
Morpheus: interactive exploration of subspace clustering
Joint Auction in the Online Advertising Market
A data mining approach to modeling relationships among categories in image collection
Broadening Participation in Technology Policy
Visualizing multi-dimensional clusters, trends, and outliers using star coordinates
PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement
Feature engineering and tree modeling for author-paper identification challenge
Tac-Valuer: Knowledge-based Stroke Evaluation in Table Tennis
Causal Inference from Network Data
Message correlation in automated communication surveillance through singular value decomposition and word frequency association
Storygraph: extracting patterns from spatio-temporal data
Accuracy of distance metric learning algorithms
Hexagon-Net: Heterogeneous Cross-View Aligned Graph Attention Networks for Implied Volatility Surface Prediction
Fast approximate spectral clustering
Diagnosing extrapolation: tree-based density estimation
Finding minimum representative pattern sets
Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification
Methods for exploring and mining tables on Wikipedia
Capacitated team formation problem on social networks
Second Workshop on Generative AI for Recommender Systems and Personalization
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Discovering Valuable items from Massive Data
CryptoMixer: Fine-grained market information-aware MLP Networks for Individual Cryptocurrency Trading Prediction
Unsupervised Discovery of Drug Side-Effects from Heterogeneous Data Sources
Backpage and Bitcoin: Uncovering Human Traffickers
Two-locus association mapping in subquadratic time
Generative model-based clustering of directional data
Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach
Curriculum Meta-Learning for Next POI Recommendation
Dynamic Clustering of Streaming Short Documents
The 4th Artificial Intelligence of Things (AIoT) Workshop
Task-Equivariant Graph Few-shot Learning
Multimedia features for click prediction of new ads in display advertising
Cross-lingual polarity detection with machine translation
Efficient human computation: the distributed labeling problem
Accelerated Stochastic Block Coordinate Descent with Optimal Sampling
Data filtering for automatic classification of rocks from reflectance spectra
Improved Degree Bounds and Full Spectrum Power Laws in Preferential Attachment Networks
Joint Optimization of Multiple Performance Metrics in Online Video Advertising
Graph Bottlenecked Social Recommendation
Depth first generation of long patterns
Predicting bounce rates in sponsored search advertisements
Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis
A unified search federation system based on online user feedback
Constructing comprehensive summaries of large event sequences
Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches
Predicting Clinical Outcomes Across Changing Electronic Health Record Systems
Learning Effective Road Network Representation with Hierarchical Graph Neural Networks
Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering
Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop, Seattle, Washington, USA, July 1994. Technical Report WS-94-03
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams
New ensemble methods for evolving data streams
Accelerated singular value thresholding for matrix completion
SPOT: Sparse Optimal Transformations for High Dimensional Variable Selection and Exploratory Regression Analysis
Graph Neural Bandits
Graph cluster randomization: network exposure to multiple universes
Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach
Mining traffic data from probe-car system for travel time prediction
AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting
Succinct Interaction-Aware Explanations
Modeling Dwell Time Engagement on Visual Multimedia
Mining the digital universe of data to develop personalized cancer therapies