Philip K. Chan

65 papers A* 11A 6B 3C 6Misc 5Journal 20Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	C	`conf`	Highly Imbalanced Regression with Tabular Data in SEP and Other Applications. ICMLA Josias K. Moukpe, Philip K. Chan, Ming Zhang
2025	J	`jnl`	Highly Imbalanced Regression with Tabular Data in SEP and Other Applications. CoRR Josias K. Moukpe, Philip K. Chan, Ming Zhang
2023	B	`conf`	Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition. IJCNN Jingyun Jia, Philip K. Chan
2023	—	`conf`	GII: A Unified Approach to Representation Learning in Open Set Recognition with Novel Category Discovery. ICANN (8) Jingyun Jia, Philip K. Chan
2022	J	`jnl`	Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition. CoRR Jingyun Jia, Philip K. Chan
2022	B	`conf`	Representation Learning with Function Call Graph Transformations for Malware Open Set Recognition. IJCNN Jingyun Jia, Philip K. Chan
2022	J	`jnl`	Representation learning with function call graph transformations for malware open set recognition. CoRR Jingyun Jia, Philip K. Chan
2022	—	`conf`	Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition. ICANN (4) Jingyun Jia, Philip K. Chan
2021	—	`conf`	MMF: A Loss Extension for Feature Learning in Open Set Recognition. ICANN (2) Jingyun Jia, Philip K. Chan
2021	J	`jnl`	Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition. CoRR Jingyun Jia, Philip K. Chan
2020	A	`conf`	Learning a Neural-network-based Representation for Open Set Recognition. SDM Mehadi Hassen, Philip K. Chan
2020	J	`jnl`	MMF: A loss extension for feature learning in open set recognition. CoRR Jingyun Jia, Philip K. Chan
2020	C	`conf`	Unsupervised Open Set Recognition using Adversarial Autoencoders. ICMLA Mehadi Hassen, Philip K. Chan
2018	Misc	`conf`	Detecting Harmful Hand Behaviors with Machine Learning from Wearable Motion Sensor Data. FLAIRS Lingfeng Zhang, Philip K. Chan
2018	J	`jnl`	Estimating effectiveness of twitter messages with a personalized machine learning approach. Knowl. Inf. Syst. Xunhu Sun, Philip K. Chan
2018	—	`conf`	Identifying Pros and Cons of Product Aspects Based on Customer Reviews. IEEE BigData Ebad Ahmadzadeh, Philip K. Chan
2018	J	`jnl`	Learning a Neural-network-based Representation for Open Set Recognition. CoRR Mehadi Hassen, Philip K. Chan
2018	Misc	`conf`	Learning to Identify Known and Unknown Classes: A Case Study in Open World Malware Classification. FLAIRS Mehadi Hassen, Philip K. Chan
2018	Misc	`conf`	Using A Personalized Anomaly Detection Approach with Machine Learning to Detect Stolen Phones. FLAIRS Huizhong Hu, Philip K. Chan
2017	—	`ch.`	Machine Learning for IT Security. Encyclopedia of Machine Learning and Data Mining Philip K. Chan
2017	—	`conf`	Malware classification using static analysis based features. SSCI Mehadi Hassen, Marco M. Carvalho, Philip K. Chan
2017	—	`conf`	Mining pros and cons of actions from social media for decision support. IEEE BigData Ebad Ahmadzadeh, Philip K. Chan
2017	—	`conf`	Scalable Function Call Graph-based Malware Classification. CODASPY Mehadi Hassen, Philip K. Chan
2016	—	`conf`	Improving efficiency of maximizing spread in the flow authority model for large sparse networks. IEEE BigData Philip K. Chan, Ebad Ahmadzadeh
2014	C	`conf`	An Analysis of Instance Selection for Neural Networks to Improve Training Speed. ICMLA Xunhu Sun, Philip K. Chan
2014	J	`jnl`	Semantic Search Techniques for Learning Smaller Boolean Expression Trees in Genetic Programming. Int. J. Comput. Intell. Appl. Nicholas C. Miller, Philip K. Chan
2012	—	`conf`	Estimating Hospital Admissions with a Randomized Regression Approach. ICMLA (1) Kleber A. Garcia, Philip K. Chan
2010	J	`jnl`	Increasing coverage to improve detection of network and host anomalies. Mach. Learn. Gaurav Tandon, Philip K. Chan
2010	Misc	`conf`	Incrementally Learning Rules for Anomaly Detection. FLAIRS Denis Petrussenko, Philip K. Chan
2010	—	`ch.`	Machine Learning for IT Security. Encyclopedia of Machine Learning Philip K. Chan
2009	A	`conf`	Tracking User Mobility to Detect Suspicious Behavior. SDM Gaurav Tandon, Philip K. Chan
2008	J	`jnl`	Learning implicit user interest hierarchy for context in personalization. Appl. Intell. Hyoung-rae Kim, Philip K. Chan
2007	J	`jnl`	Intelligent Systems at Florida Tech. IEEE Intell. Informatics Bull. Philip K. Chan, Ronaldo Menezes, Debasis Mitra, Eraldo Ribeiro, Marius Silaghi
2007	A*	`conf`	Weighting versus pruning in rule validation for detecting network and host anomalies. KDD Gaurav Tandon, Philip K. Chan
2006	J	`jnl`	Machine Learning for Computer Security. J. Mach. Learn. Res. Philip K. Chan, Richard Lippmann
2006	J	`jnl`	On the Learning of System Call Attributes for Host-based Anomaly Detection. Int. J. Artif. Intell. Tools Gaurav Tandon, Philip K. Chan
2005	C	`conf`	Implicit Indicators for Interesting Web Pages. WEBIST Hyoung-rae Kim, Philip K. Chan
2005	Misc	`conf`	Learning Useful System Call Attributes for Anomaly Detection. FLAIRS Gaurav Tandon, Philip K. Chan
2005	A*	`conf`	Modeling Multiple Time Series for Anomaly Detection. ICDM Philip K. Chan, Matthew V. Mahoney
2005	—	`conf`	Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks. WebKDD Hyoung-rae Kim, Philip K. Chan
2004	B	`conf`	Identifying Variable-Length Meaningful Phrases with Correlation Functions. ICTAI Hyoung-rae Kim, Philip K. Chan
2004	C	`conf`	MORPHEUS: motif oriented representations to purge hostile events from unlabeled sequences. VizSEC Gaurav Tandon, Philip K. Chan, Debasis Mitra
2004	C	`conf`	Motif-Oriented Representation of Sequences for a Host-Based Intrusion Detection System. IEA/AIE Gaurav Tandon, Debasis Mitra, Philip K. Chan
2004	J	`jnl`	Using artificial anomalies to detect unknown and known network intrusions. Knowl. Inf. Syst. Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan
2003	A	`conf`	An Analysis of the 1999 DARPA/Lincoln Laboratory Evaluation Data for Network Anomaly Detection. RAID Matthew V. Mahoney, Philip K. Chan
2003	A*	`conf`	Learning Rules for Anomaly Detection of Hostile Network Traffic. ICDM Matthew V. Mahoney, Philip K. Chan
2003	A	`conf`	Learning implicit user interest hierarchy for context in personalization. IUI Hyoung R. Kim, Philip K. Chan
2002	A*	`conf`	Learning nonstationary models of normal network traffic for detecting novel attacks. KDD Matthew V. Mahoney, Philip K. Chan
2001	J	`jnl`	Data Mining-based Intrusion Detectors: An Overview of the Columbia IDS Project. SIGMOD Rec. Salvatore J. Stolfo, Wenke Lee, Philip K. Chan, Wei Fan, Eleazar Eskin
2001	A*	`conf`	Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. ICDM Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan
1999	A*	`conf`	AdaCost: Misclassification Cost-Sensitive Boosting. ICML Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan
1999	—	`conf`	Constructing Web User Profiles: A non-invasive Learning Approach. WebKDD Philip K. Chan
1999	J	`jnl`	Guest Editors' Introduction. Mach. Learn. Philip K. Chan, Salvatore J. Stolfo, David H. Wolpert
1998	A*	`conf`	Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection. KDD Philip K. Chan, Salvatore J. Stolfo
1997	A*	`conf`	JAM: Java Agents for Meta-Learning over Distributed Databases. KDD Salvatore J. Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Dave W. Fan, Philip K. Chan
1997	J	`jnl`	On the Accuracy of Meta-Learning for Scalable Data Mining. J. Intell. Inf. Syst. Philip K. Chan, Salvatore J. Stolfo
1996	A*	`conf`	Sharing Learned Models among Remote Database Partitions by Local Meta-Learning. KDD Philip K. Chan, Salvatore J. Stolfo
1995	A*	`conf`	A Comparative Evaluation of Voting and Meta-learning on Partitioned Data. ICML Philip K. Chan, Salvatore J. Stolfo
1995	A*	`conf`	Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning. KDD Philip K. Chan, Salvatore J. Stolfo
1993	A	`conf`	Experiments on Multi-Strategy Learning by Meta-Learning. CIKM Philip K. Chan, Salvatore J. Stolfo
1993	J	`jnl`	Systems for Knowledge Discovery in Databases. IEEE Trans. Knowl. Data Eng. Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-Shapiro
1993	A	`conf`	Toward Multi-Strategy Parallel & Distributed Learning in Sequence Analysis. ISMB Philip K. Chan, Salvatore J. Stolfo
1991	J	`jnl`	PARULE: Parallel Rule Processing Using Meta-rules for Redaction. J. Parallel Distributed Comput. Salvatore J. Stolfo, Ouri Wolfson, Philip K. Chan, Hasanat M. Dewan, Leland Woodbury, Jason S. Glazier, David Ohsie
1990	J	`jnl`	Statistical guidance in symbolic learning. Ann. Math. Artif. Intell. Douglas H. Fisher, Philip K. Chan
1989	—	`conf`	Inductive Learning with BCT. ML Philip K. Chan