Philip Chan

According to our database, Philip Chan authored at least 64 papers between 1989 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2023

Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition.

Jingyun Jia, Philip K. Chan

Proceedings of the International Joint Conference on Neural Networks, 2023

GII: A Unified Approach to Representation Learning in Open Set Recognition with Novel Category Discovery.

Jingyun Jia, Philip K. Chan

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2023, 2023

2022

Representation Learning with Function Call Graph Transformations for Malware Open Set Recognition.

Jingyun Jia, Philip K. Chan

Proceedings of the International Joint Conference on Neural Networks, 2022

Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition.

Jingyun Jia, Philip K. Chan

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

MMF: A Loss Extension for Feature Learning in Open Set Recognition.

Jingyun Jia, Philip K. Chan

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Learning a Neural-network-based Representation for Open Set Recognition.

Mehadi Hassen, Philip K. Chan

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Unsupervised Open Set Recognition using Adversarial Autoencoders.

Mehadi Hassen, Philip K. Chan

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2018

Estimating effectiveness of twitter messages with a personalized machine learning approach.

Xunhu Sun, Philip K. Chan

Knowl. Inf. Syst., 2018

Detecting Harmful Hand Behaviors with Machine Learning from Wearable Motion Sensor Data.

Lingfeng Zhang, Philip K. Chan

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

Using A Personalized Anomaly Detection Approach with Machine Learning to Detect Stolen Phones.

Huizhong Hu, Philip K. Chan

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

Learning to Identify Known and Unknown Classes: A Case Study in Open World Malware Classification.

Mehadi Hassen, Philip K. Chan

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

Identifying Pros and Cons of Product Aspects Based on Customer Reviews.

Ebad Ahmadzadeh, Philip K. Chan

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Machine Learning for IT Security.

Philip K. Chan

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Malware classification using static analysis based features.

Mehadi Hassen, Marco M. Carvalho, Philip K. Chan

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Scalable Function Call Graph-based Malware Classification.

Mehadi Hassen, Philip K. Chan

Proceedings of the Seventh ACM Conference on Data and Application Security and Privacy, 2017

Mining pros and cons of actions from social media for decision support.

Ebad Ahmadzadeh, Philip K. Chan

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Improving efficiency of maximizing spread in the flow authority model for large sparse networks.

Philip K. Chan, Ebad Ahmadzadeh

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2014

Semantic Search Techniques for Learning Smaller Boolean Expression Trees in Genetic Programming.

Nicholas C. Miller, Philip K. Chan

Int. J. Comput. Intell. Appl., 2014

An Analysis of Instance Selection for Neural Networks to Improve Training Speed.

Xunhu Sun, Philip K. Chan

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

2012

Estimating Hospital Admissions with a Randomized Regression Approach.

Kleber A. Garcia, Philip K. Chan

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2010

Machine Learning for IT Security.

Philip K. Chan

Proceedings of the Encyclopedia of Machine Learning, 2010

Increasing coverage to improve detection of network and host anomalies.

Gaurav Tandon, Philip K. Chan

Mach. Learn., 2010

Incrementally Learning Rules for Anomaly Detection.

Denis Petrussenko, Philip K. Chan

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009

Tracking User Mobility to Detect Suspicious Behavior.

Gaurav Tandon, Philip K. Chan

Proceedings of the SIAM International Conference on Data Mining, 2009

2008

Learning implicit user interest hierarchy for context in personalization.

Hyoung-rae Kim, Philip K. Chan

Appl. Intell., 2008

2007

Toward accurate dynamic time warping in linear time and space.

Stan Salvador, Philip Chan

Intell. Data Anal., 2007

Intelligent Systems at Florida Tech.

Philip K. Chan, Ronaldo Menezes, Debasis Mitra, Eraldo Ribeiro, Marius Silaghi

IEEE Intell. Informatics Bull., 2007

Weighting versus pruning in rule validation for detecting network and host anomalies.

Gaurav Tandon, Philip K. Chan

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

2006

Machine Learning for Computer Security.

Philip K. Chan, Richard Lippmann

J. Mach. Learn. Res., 2006

On the Learning of System Call Attributes for Host-based Anomaly Detection.

Gaurav Tandon, Philip K. Chan

Int. J. Artif. Intell. Tools, 2006

2005

Data mining methods for anomaly detection KDD-2005 workshop report.

Dragos D. Margineantu, Stephen Bay, Philip Chan, Terran Lane

SIGKDD Explor., 2005

Learning States and Rules for Detecting Anomalies in Time Series.

Stan Salvador, Philip Chan

Appl. Intell., 2005

Implicit Indicators for Interesting Web Pages.

Hyoung-rae Kim, Philip K. Chan

Proceedings of the WEBIST 2005, 2005

Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks.

Hyoung-rae Kim, Philip K. Chan

Proceedings of the Advances in Web Mining and Web Usage Analysis, 2005

Modeling Multiple Time Series for Anomaly Detection.

Philip K. Chan, Matthew V. Mahoney

Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Learning Useful System Call Attributes for Anomaly Detection.

Gaurav Tandon, Philip K. Chan

Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, 2005

2004

Using artificial anomalies to detect unknown and known network intrusions.

Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan

Knowl. Inf. Syst., 2004

MORPHEUS: motif oriented representations to purge hostile events from unlabeled sequences.

Gaurav Tandon, Philip K. Chan, Debasis Mitra

Proceedings of the 1st ACM Workshop on Visualization and Data Mining for Computer Security, 2004

Motif-Oriented Representation of Sequences for a Host-Based Intrusion Detection System.

Gaurav Tandon, Debasis Mitra, Philip K. Chan

Proceedings of the Innovations in Applied Artificial Intelligence, 2004

Determining the Number of Clusters/Segments in Hierarchical Clustering/Segmentation Algorithms.

Stan Salvador, Philip Chan

Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004

Identifying Variable-Length Meaningful Phrases with Correlation Functions.

Hyoung-rae Kim, Philip K. Chan

Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004

Learning States and Rules for Time Series Anomaly Detection.

Stan Salvador, Philip Chan, John Brodie

Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, 2004

2003

An Analysis of the 1999 DARPA/Lincoln Laboratory Evaluation Data for Network Anomaly Detection.

Matthew V. Mahoney, Philip K. Chan

Proceedings of the Recent Advances in Intrusion Detection, 6th International Symposium, 2003

Learning implicit user interest hierarchy for context in personalization.

Hyoung R. Kim, Philip K. Chan

Proceedings of the 8th International Conference on Intelligent User Interfaces, 2003

Learning Rules for Anomaly Detection of Hostile Network Traffic.

Matthew V. Mahoney, Philip K. Chan

Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

2002

Learning nonstationary models of normal network traffic for detecting novel attacks.

Matthew V. Mahoney, Philip K. Chan

Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

2001

Data Mining-based Intrusion Detectors: An Overview of the Columbia IDS Project.

Salvatore J. Stolfo, Wenke Lee, Philip K. Chan, Wei Fan, Eleazar Eskin

SIGMOD Rec., 2001

1999

Guest Editors' Introduction.

Philip K. Chan, Salvatore J. Stolfo, David H. Wolpert

Mach. Learn., 1999

Distributed data mining in credit card fraud detection.

Philip Chan, Wei Fan, Andreas L. Prodromidis, Salvatore J. Stolfo

IEEE Intell. Syst., 1999

Constructing Web User Profiles: A non-invasive Learning Approach.

Philip K. Chan

Proceedings of the Web Usage Analysis and User Profiling, 1999

AdaCost: Misclassification Cost-Sensitive Boosting.

Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan

Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

1998

KDD Cup 1999 Data.

Salvatore J. Stolfo, Wei Fan, Wenke Lee, Andreas L. Prodromidis, Philip Chan

Dataset, December, 1998

Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1997

On the Accuracy of Meta-Learning for Scalable Data Mining.

Philip K. Chan, Salvatore J. Stolfo

J. Intell. Inf. Syst., 1997

JAM: Java Agents for Meta-Learning over Distributed Databases.

Salvatore J. Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Dave W. Fan, Philip K. Chan

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

1996

Sharing Learned Models among Remote Database Partitions by Local Meta-Learning.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

1995

Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

A Comparative Evaluation of Voting and Meta-learning on Partitioned Data.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the Machine Learning, 1995

1993

Systems for Knowledge Discovery in Databases.

Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-Shapiro

IEEE Trans. Knowl. Data Eng., 1993

Toward Multi-Strategy Parallel & Distributed Learning in Sequence Analysis.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, 1993

Experiments on Multi-Strategy Learning by Meta-Learning.

Philip K. Chan, Salvatore J. Stolfo

Proceedings of the CIKM 93, 1993

1991

PARULE: Parallel Rule Processing Using Meta-rules for Redaction.

Salvatore J. Stolfo, Ouri Wolfson, Philip K. Chan, Hasanat M. Dewan, Leland Woodbury, Jason S. Glazier, David Ohsie

J. Parallel Distributed Comput., 1991

1990

Statistical guidance in symbolic learning.

Douglas H. Fisher, Philip K. Chan

Ann. Math. Artif. Intell., 1990

1989

Inductive Learning with BCT.

Philip K. Chan

Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989