Xing-quan Zhu
#147,272
Most Influential Person Now
Xing-quan Zhu's AcademicInfluence.com Rankings
Xing-quan Zhucomputer-science Degrees
Computer Science
#7487
World Rank
#7884
Historical Rank
Big Data
#20
World Rank
#20
Historical Rank
Data Mining
#179
World Rank
#180
Historical Rank
Database
#4537
World Rank
#4716
Historical Rank

Download Badge
Computer Science
Xing-quan Zhu's Degrees
- PhD Computer Science University of California, Riverside
- Masters Computer Science University of California, Riverside
- Bachelors Computer Science Zhejiang University
Similar Degrees You Can Earn
Why Is Xing-quan Zhu Influential?
(Suggest an Edit or Addition)Xing-quan Zhu's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Data mining with big data (2014) (1380)
- Class Noise vs. Attribute Noise: A Quantitative Study (2003) (748)
- Network Representation Learning: A Survey (2017) (456)
- Tri-Party Deep Network Representation (2016) (364)
- Machine Learning for Android Malware Detection Using Permission and API Calls (2013) (302)
- A survey on instance selection for active learning (2012) (301)
- Eliminating Class Noise in Large Datasets (2003) (268)
- MGAE: Marginalized Graph Autoencoder for Graph Clustering (2017) (248)
- Online Feature Selection with Streaming Features (2013) (224)
- Knowledge Discovery and Data Mining: Challenges and Realities (2007) (181)
- Dropout vs. batch normalization: an empirical study of their impact to deep learning (2020) (162)
- Bag Constrained Structure Pattern Mining for Multi-Graph Classification (2014) (160)
- Video data mining: semantic indexing and event detection from the association perspective (2005) (153)
- Active Learning From Stream Data Using Optimal Weight Classifier Ensemble (2010) (135)
- Combining proactive and reactive predictions for data streams (2005) (119)
- Active Learning from Data Streams (2007) (117)
- Mining in Anticipation for Concept Change: Proactive-Reactive Prediction in Data Streams (2006) (108)
- Mining With Noise Knowledge: Error-Aware Data Mining (2007) (108)
- Boosting for Multi-Graph Classification (2015) (106)
- Categorizing and mining concept drifting data streams (2008) (105)
- Ensemble pruning via individual contribution ordering (2010) (97)
- InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval (2005) (94)
- User Profile Preserving Social Network Embedding (2017) (91)
- Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams (2010) (91)
- Homophily, Structure, and Content Augmented Network Representation Learning (2016) (91)
- Exploring video content structure for hierarchical summarization (2004) (89)
- MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding (2018) (88)
- Self-adaptive attribute weighting for Naive Bayes classification (2015) (88)
- Robust ensemble learning for mining noisy data streams (2011) (84)
- Cross-Domain Collaborative Filtering over Time (2011) (84)
- Dynamic classifier selection for effective mining from noisy data streams (2004) (83)
- Imputation-boosted collaborative filtering using machine learning classifiers (2008) (80)
- Mining Data Streams with Labeled and Unlabeled Training Examples (2009) (75)
- UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks (2013) (74)
- E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams (2015) (74)
- Unsupervised Domain Adaptive Graph Convolutional Networks (2020) (71)
- Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification (2015) (70)
- Deep Learning for User Interest and Response Prediction in Online Display Advertising (2020) (69)
- Multi-Class Imbalanced Graph Convolutional Network Learning (2020) (68)
- Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets (2004) (67)
- Multi-Instance Learning with Discriminative Bag Mapping (2018) (65)
- Multiple Structure-View Learning for Graph Classification (2018) (64)
- Sequential pattern mining in multiple streams (2005) (60)
- Task Sensitive Feature Exploration and Learning for Multitask Graph Classification (2017) (59)
- Efficient string matching with wildcards and length constraints (2006) (57)
- A Novel Consistent Random Forest Framework: Bernoulli Random Forests (2018) (57)
- Efficient sequential pattern mining with wildcards for keyphrase extraction (2017) (56)
- Graph stream classification using labeled and unlabeled graphs (2013) (55)
- Hashing Techniques (2017) (54)
- Rating Knowledge Sharing in Cross-Domain Collaborative Filtering (2015) (54)
- Hashing Techniques: A Survey and Taxonomy (2017) (54)
- Positive and Unlabeled Multi-Graph Learning (2017) (52)
- Mining maximal frequent itemsets from data streams (2007) (51)
- Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification (2016) (50)
- Bridging Local and Global Data Cleansing: Identifying Class Noise in Large, Distributed Data Datasets (2006) (49)
- Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data (2017) (49)
- SODE: Self-Adaptive One-Dependence Estimators for classification (2016) (48)
- Cost-constrained data acquisition for intelligent data preparation (2005) (48)
- Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts (2007) (47)
- Incremental Subgraph Feature Selection for Graph Classification (2017) (47)
- Enabling Fast Lazy Learning for Data Streams (2011) (47)
- NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints (2018) (46)
- Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering (2006) (45)
- Artificial immune system for attribute weighted Naive Bayes classification (2013) (45)
- Self-Taught Active Learning from Crowds (2012) (45)
- Transfer Learning across Networks for Collective Classification (2013) (44)
- Enabling fast prediction for ensemble models on data streams (2011) (44)
- Multi-instance Multi-graph Dual Embedding Learning (2013) (44)
- Multi-graph-view Learning for Graph Classification (2014) (44)
- Mining Complex Patterns across Sequences with Gap Requirements (2007) (44)
- Noisy but non-malicious user detection in social recommender systems (2013) (43)
- A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD (2018) (42)
- Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams (2012) (42)
- TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs (2015) (42)
- CogBoost: Boosting for Fast Cost-Sensitive Graph Classification (2015) (42)
- Finding the best not the most: regularized loss minimization subgraph selection for graph classification (2015) (42)
- A survey and taxonomy of adversarial neural networks for text‐to‐image synthesis (2019) (41)
- Topic discovery and future trend forecasting for texts (2016) (41)
- PMBC: Pattern mining from biological sequences with wildcard constraints (2013) (41)
- Self-adaptive probability estimation for Naive Bayes classification (2013) (39)
- iSRD: Spam review detection with imbalanced data distributions (2014) (38)
- Effective classification of noisy data streams with attribute-oriented dynamic classifier selection (2006) (38)
- One-class learning and concept summarization for data streams (2011) (36)
- Multi-Graph Learning with Positive and Unlabeled Bags (2014) (35)
- Scalable Representative Instance Selection and Ranking (2006) (35)
- A lazy bagging approach to classification (2008) (34)
- Deep Structure Learning for Fraud Detection (2018) (32)
- Graph Classification with Imbalanced Class Distributions and Noise (2013) (32)
- Lazy Bagging for Classifying Imbalanced Data (2007) (31)
- CFOND: Consensus Factorization for Co-Clustering Networked Data (2019) (31)
- Discovering Relational Patterns across Multiple Databases (2007) (30)
- Attributed network embedding via subspace discovery (2019) (30)
- Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks (2016) (30)
- Sequential association mining for video summarization (2003) (30)
- An Empirical Study of Bagging Predictors for Different Learning Algorithms (2011) (29)
- Convolutional neural network learning for generic data classification (2019) (29)
- Extreme clustering - A clustering method via density extreme points (2021) (28)
- Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach (2014) (28)
- Fraud Prevention in Online Digital Advertising (2017) (27)
- Cleansing Noisy Data Streams (2008) (27)
- Cost-guided class noise handling for effective cost-sensitive learning (2004) (27)
- vEye: behavioral footprinting for self-propagating worm detection and profiling (2009) (27)
- NTP-Miner: Nonoverlapping Three-Way Sequential Pattern Mining (2021) (26)
- Relation Structure-Aware Heterogeneous Graph Neural Network (2019) (26)
- Fast Graph Stream Classification Using Discriminative Clique Hashing (2013) (26)
- IoT Network Security: Threats, Risks, and a Data-Driven Defense Framework (2020) (26)
- Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources (2004) (26)
- SINE: Scalable Incomplete Network Embedding (2018) (25)
- Domain-Adversarial Graph Neural Networks for Text Classification (2019) (24)
- The Impact of Gene Selection on Imbalanced Microarray Expression Data (2009) (24)
- Mining Sequential Patterns Across Data Streams (2005) (24)
- Active learning with uncertain labeling knowledge (2014) (23)
- Multi-graph-view subgraph mining for graph classification (2016) (23)
- HANP-Miner: High average utility nonoverlapping sequential pattern mining (2021) (22)
- CLAP: Collaborative pattern mining for distributed information systems (2011) (22)
- An Aggregate Ensemble for Mining Concept Drifting Data Streams with Noise (2009) (22)
- Time-Variant Graph Classification (2016) (22)
- Tracking User-Preference Varying Speed in Collaborative Filtering (2011) (21)
- An Empirical Study of the Noise Impact on Cost-Sensitive Learning (2007) (21)
- Context-Preserving Hashing for Fast Text Classification (2014) (19)
- Vague One-Class Learning for Data Streams (2009) (19)
- Active Learning With Optimal Instance Subset Selection (2013) (19)
- TCSST: transfer classification of short & sparse text using external data (2012) (18)
- Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards (2014) (18)
- Conceptual equivalence for contrast mining in classification learning (2008) (18)
- Top-k Self-Adaptive Contrast Sequential Pattern Mining (2021) (18)
- Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts (2018) (18)
- $K$ -Ary Tree Hashing for Fast Graph Classification (2018) (17)
- SKIF: a data imputation framework for concept drifting data streams (2010) (17)
- Tackling Class Imbalance in Cyber Security Datasets (2018) (17)
- Editorial: Special issue on mining low-quality data (2007) (17)
- Evolutionary Architecture Search for Graph Neural Networks (2020) (16)
- Discriminative Sample Generation for Deep Imbalanced Learning (2019) (16)
- Hierarchical Sampling for Multi-Instance Ensemble Learning (2013) (16)
- Knowledge Transfer for Multi-labeler Active Learning (2013) (16)
- Cross-Domain Semi-Supervised Learning Using Feature Formulation (2011) (16)
- Compression in Molecular Simulation Datasets (2013) (15)
- DCMS: A data analytics and management system for molecular simulation (2014) (15)
- MLNE: Multi-Label Network Embedding (2019) (15)
- Predictive modeling of clinical trial terminations using feature engineering and embedding learning (2021) (15)
- SAIL-APPROX: An Efficient On-Line Algorithm for Approximate Pattern Matching with Wildcards and Length Constraints (2007) (15)
- OpenWGL: Open-World Graph Learning (2020) (14)
- An empirical study of morphing on behavior-based network traffic classification (2015) (14)
- Learning Graph Neural Networks with Positive and Unlabeled Nodes (2021) (14)
- An Empirical Study of Bagging Predictors for Imbalanced Data with Different Levels of Class Distribution (2011) (13)
- Dual instance and attribute weighting for Naive Bayes classification (2014) (13)
- Boosting for graph classification with universum (2016) (13)
- Do they belong to the same class: active learning by querying pairwise label homogeneity (2011) (13)
- OIDM: Online Interactive Data Mining (2004) (13)
- Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning (2019) (12)
- Mining Sequential Patterns across Time Sequences (2007) (12)
- Gene Selection for Microarray Expression Data with Imbalanced Sample Distributions (2009) (12)
- Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction (2007) (12)
- Multi-Graph-View Learning for Complicated Object Classification (2015) (12)
- Mining Frequent Patterns with Wildcards from Biological Sequences (2007) (11)
- Transfer active learning (2011) (11)
- Continuous top-k query for graph streams (2012) (11)
- User Response Prediction in Online Advertising (2021) (11)
- Multi-Label Graph Convolutional Network Representation Learning (2019) (11)
- Multiple criteria programming models for VIP E-Mail behavior analysis (2010) (11)
- The effect of varying levels of class distribution on bagging for different algorithms: An empirical study (2014) (11)
- MULFE: Multi-Label Learning via Label-Specific Feature Space Ensemble (2021) (11)
- Generalized Feature Embedding for Supervised, Unsupervised, and Online Learning Tasks (2019) (11)
- Data acquisition with active and impact-sensitive instance selection (2004) (10)
- Topology and Content Co-Alignment Graph Convolutional Learning (2020) (10)
- Multi-Instance Learning from Positive and Unlabeled Bags (2014) (10)
- SNOC: Streaming Network Node Classification (2014) (10)
- Towards a Big Data Architecture for Facilitating Cyber Threat Intelligence (2016) (10)
- Normalized dimensionality reduction using nonnegative matrix factorization (2010) (10)
- Multiple Information Sources Cooperative Learning (2009) (10)
- CGStream: continuous correlated graph query for data streams (2012) (10)
- Topical network embedding (2019) (9)
- Feature Selection for Datasets with Imbalanced Class Distributions (2010) (9)
- ACE: an aggressive classifier ensemble with error detection, correction and cleansing (2005) (9)
- Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning (2014) (9)
- Deep learning data augmentation for Raman spectroscopy cancer tissue classification (2021) (9)
- GAEN: Graph Attention Evolving Networks (2021) (9)
- Combining Structured Node Content and Topology Information for Networked Graph Clustering (2017) (9)
- Active exploration: simultaneous sampling and labeling for large graphs (2013) (9)
- A cost sensitive approach to predicting 30-day hospital readmission in COPD patients (2017) (9)
- Active exploration for large graphs (2015) (8)
- Proactive-Reactive Prediction for Data Streams (2005) (8)
- Who wrote this paper? Learning for authorship de-identification using stylometric featuress (2014) (8)
- Graph hashing and factorization for fast graph stream classification (2013) (8)
- Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction (2008) (8)
- MINING APPROXIMATE REPEATING PATTERNS FROM SEQUENCE DATA WITH GAP CONSTRAINTS (2011) (8)
- Co-clustering enterprise social networks (2016) (8)
- GraSSNet: Graph Soft Sensing Neural Networks (2021) (8)
- Understanding the roles of sub-graph features for graph classification: an empirical study perspective (2013) (8)
- Mining Video Associations for Efficient Database Management (2003) (8)
- Attribute weighting: How and when does it work for Bayesian Network Classification (2014) (8)
- Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness (2016) (8)
- Latent topic ensemble learning for hospital readmission cost reduction (2017) (7)
- OPP-Miner: Order-Preserving Sequential Pattern Mining for Time Series (2022) (7)
- Approximate Repeating Pattern Mining with Gap Requirements (2009) (7)
- Inverse matrix-free incremental proximal support vector machine (2012) (7)
- SALE: Self-adaptive LSH encoding for multi-instance learning (2017) (7)
- Big data driven co-occurring evidence discovery in chronic obstructive pulmonary disease patients (2017) (7)
- I don't know the label: Active learning with blind knowledge (2012) (7)
- Knowledge Graph Embedding by Double Limit Scoring Loss (2021) (6)
- Topic-aware Web Service Representation Learning (2020) (6)
- Understanding and predicting COVID-19 clinical trial completion vs. cessation (2021) (6)
- Deep Transfer Learning for Traffic Sign Recognition (2018) (6)
- Feature selection with biased sample distributions (2009) (6)
- Corrective classification: Learning from data imperfections with aggressive and diverse classifier ensembling (2011) (6)
- Active Class Discovery and Learning for Networked Data (2013) (6)
- Reverse twin plant for efficient diagnosability testing and optimizing (2015) (6)
- Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 (2015) (6)
- Feature-Attention Graph Convolutional Networks for Noise Resilient Learning (2019) (6)
- Bagging very weak learners with lazy local learning (2008) (6)
- How Does Research Evolve? Pattern Mining for Research Meme Cycles (2011) (5)
- Decision Rule Extraction for Regularized Multiple Criteria Linear Programming Model (2011) (5)
- Ad Ecosystems and Key Components (2017) (5)
- ULTR-CTR: Fast Page Grouping Using URL Truncation for Real-Time Click Through Rate Estimation (2017) (5)
- Topic Discovery and Future Trend Prediction Using Association Analysis and Ensemble Forecasting (2015) (5)
- VoB predictors: Voting on bagging classifications (2008) (5)
- An Empirical Study of Robustness of Network Centrality Scores in Various Networks and Conditions (2013) (5)
- Rule Synthesizing from Multiple Related Databases (2010) (5)
- CNFL: Categorical to Numerical Feature Learning for Clustering and Classification (2017) (5)
- Generalizing Long Short-Term Memory Network for Deep Learning from Generic Data (2020) (5)
- Active Learning from Oracle with Knowledge Blind Spot (2012) (5)
- HW-Forest: Deep Forest with Hashing Screening and Window Screening (2022) (5)
- MMIS07, 08: mining multiple information sources workshop report (2008) (5)
- Error awareness data mining (2006) (5)
- Predictive Modeling of Hospital Readmission: Challenges and Solutions (2021) (4)
- The Evolution of Search: Three Computing Paradigms (2022) (4)
- Gender Prediction in Random Chat Networks Using Topological Network Structures and Masked Content (2015) (4)
- Social Network Privacy: Issues and Measurement (2015) (4)
- An empirical study of morphing on network traffic classification (2012) (4)
- Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners (2006) (4)
- ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting (2021) (4)
- Transfer incremental learning for pattern classification (2010) (4)
- Learning Convolutional Neural Networks from Ordered Features of Generic Data (2018) (4)
- EDLT: Enabling Deep Learning for Generic Data Classification (2018) (4)
- Select Objective Functions for Multiple Criteria Programming Classification (2008) (4)
- Hierarchical Feature Selection Based on Label Distribution Learning (2023) (4)
- Error Detection and Uncertainty Modeling for Imprecise Data (2009) (3)
- Ubiquitous Mining with Interactive Data Mining Agents (2009) (3)
- Imbalanced Learning for Hospital Readmission Prediction using National Readmission Database (2020) (3)
- OpenWGL: open-world graph learning for unseen class node classification (2021) (3)
- Attraction and Repulsion: Unsupervised Domain Adaptive Graph Contrastive Learning Network (2022) (3)
- Encrypted data indexing for the secure outsourcing of spectral clustering (2018) (3)
- Search Efficient Binary Network Embedding (2019) (3)
- Ad Fraud Categorization and Detection Methods (2017) (3)
- Online Mining of Maximal Frequent Itemsequences from Data Streams (2005) (3)
- Optimal Subset Selection for Active Learning (2011) (3)
- A Classifier Ensembling Approach for Imbalanced Social Link Prediction (2013) (3)
- Localized sampling for hospital re-admission prediction with imbalanced sample distributions (2017) (3)
- Network Analysis and Recommendation for Infectious Disease Clinical Trial Research (2019) (3)
- Parallel Selection of Informative Genes for Classification (2009) (2)
- Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems (2021) (2)
- Super-Graph Classification (2014) (2)
- Deep Learning for Online Display Advertising User Clicks and Interests Prediction (2019) (2)
- Self-adjust Local Connectivity Analysis for Spectral Clustering (2011) (2)
- Large Scale Diagnosis Using Associations between System Outputs and Components (2011) (2)
- Cyberbullying and Cyberviolence Detection: A Triangular User-Activity-Content View (2022) (2)
- Supervised sampling for networked data (2016) (2)
- Top-k correlated subgraph query for data streams (2012) (2)
- Network Analysis of Technology Stocks using Market Correlation (2020) (2)
- GFEL: Generalized Feature Embedding Learning Using Weighted Instance Matching (2017) (2)
- iVESTA: an interactive visualization and evaluation system for drive test data (2008) (2)
- A survey on instance selection for active learning (2012) (2)
- OPR-Miner: Order-preserving rule mining for time series (2022) (2)
- An Empirical Study of Deep Learning Frameworks for Melanoma Cancer Detection using Transfer Learning and Data Augmentation (2021) (2)
- Community and topic modeling for infectious disease clinical trial recommendation (2021) (2)
- SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation (2023) (2)
- Co-occurring evidence discovery for COPD patients using natural language processing (2017) (1)
- Noisy but non-malicious user detection in social recommender systems (2012) (1)
- Computer forensic using Lazy Local bagging predictors (2009) (1)
- Data mining (2008) (1)
- OPP-Miner: Order-preserving sequential pattern mining (2022) (1)
- Data Intensive Computing: A Biomedical Case Study in Gene Selection and Filtering (2011) (1)
- MedFroDetect: Medicare Fraud Detection with Extremely Imbalanced Class Distributions (2020) (1)
- TriNE: Network Representation Learning for Tripartite Heterogeneous Networks (2020) (1)
- Mining Knowledge from Multiple Criteria Linear Programming Models (2009) (1)
- Direct Discriminative Bag Mapping for Multi-Instance Learning (2016) (1)
- Web Service Network Embedding Based on Link Prediction and Convolutional Learning (2021) (1)
- Nationwide hospital admission data statistics and disease-specific 30-day readmission prediction (2022) (1)
- An empirical study of supervised learning for biological sequence profiling and microarray expression data analysis (2008) (0)
- Attributed network embedding via subspace discovery (2019) (0)
- Local Contrastive Feature Learning for Tabular Data (2022) (0)
- Active exploration for large graphs (2015) (0)
- Bias-Variance Analysis for Ensembling Regularized Multiple Criteria Linear Programming Models (2009) (0)
- VCI predictors: Voting on classifications from imputed learning sets (2008) (0)
- Active Class Discovery by Querying Pairwise Label Homogeneity (2015) (0)
- Rough Set Theory In Data Mining Ppt (2015) (0)
- Special issue on data mining applications and case study (2012) (0)
- Big Data Characteristics : HACE Theorem (2013) (0)
- Data Compression for Molecular Simulations (2011) (0)
- One-Class Learning and Concept Summarization for Vaguely Labeled Data Streams * (2009) (0)
- Ad Fraud Taxonomy and Prevention Mechanisms (2017) (0)
- Scalable Inductive Learning on Partitioned Data (2005) (0)
- Graph Compression Networks (2021) (0)
- Weak Supervision Network Embedding for Constrained Graph Learning (2021) (0)
- An Ensemble based Bayesian Network Learning Algorithm on Limited Data (2007) (0)
- Intelligence Science and Big Data Engineering (2013) (0)
- Editorial (2013) (0)
- Parallel proximal support vector machine for high-dimensional pattern classification (2012) (0)
- A Multiple Criteria and Multiple Constraints Mathematical Programming Model for Classification (2009) (0)
- First International Workshop on Mining Multiple Information Sources (2007) (0)
- Topical network embedding (2019) (0)
- Introduction to special issue on scientific and statistical data management in the age of AI 2021 (2022) (0)
- Boosting for graph classification with universum (2016) (0)
- gEBoost: Noisy and Imbalanced Graph Stream Classification (2014) (0)
- Understanding and Predicting Faculty Success in Winning Grant Awards (2021) (0)
- COPD Disease Classification Using Network Embedding with Synthetic Relationships (2020) (0)
- The effect of varying levels of class distribution on bagging for different algorithms: An empirical study (2012) (0)
- Ad Fraud Measure and Benchmark (2017) (0)
- Ad Fraud Detection Tools and Systems (2017) (0)
This paper list is powered by the following services: