Philip K. Chan

2008
33	EE	Hyoung-rae Kim, Philip K. Chan: Learning implicit user interest hierarchy for context in personalization. Appl. Intell. 28(2): 153-166 (2008)
2007
32	EE	Gaurav Tandon, Philip K. Chan: Weighting versus pruning in rule validation for detecting network and host anomalies. KDD 2007: 697-706
2006
31	EE	Gaurav Tandon, Philip K. Chan: On the Learning of System Call Attributes for Host-based Anomaly Detection. International Journal on Artificial Intelligence Tools 15(6): 875-892 (2006)
30	EE	Philip K. Chan, Richard Lippmann: Machine Learning for Computer Security. Journal of Machine Learning Research 6: 2669-2672 (2006)
2005
29		Gaurav Tandon, Philip K. Chan: Learning Useful System Call Attributes for Anomaly Detection. FLAIRS Conference 2005: 405-411
28	EE	Philip K. Chan, Matthew V. Mahoney: Modeling Multiple Time Series for Anomaly Detection. ICDM 2005: 90-97
27		Hyoung-rae Kim, Philip K. Chan: Implicit Indicators for Interesting Web Pages. WEBIST 2005: 270-277
26	EE	Hyoung-rae Kim, Philip K. Chan: Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks. WEBKDD 2005: 158-176
2004
25	EE	Hyoung-rae Kim, Philip K. Chan: Identifying Variable-Length Meaningful Phrases with Correlation Functions. ICTAI 2004: 30-38
24	EE	Gaurav Tandon, Debasis Mitra, Philip K. Chan: Motif-Oriented Representation of Sequences for a Host-Based Intrusion Detection System. IEA/AIE 2004: 605-615
23	EE	Gaurav Tandon, Philip K. Chan, Debasis Mitra: MORPHEUS: motif oriented representations to purge hostile events from unlabeled sequences. VizSEC 2004: 16-25
22	EE	Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan: Using artificial anomalies to detect unknown and known network intrusions. Knowl. Inf. Syst. 6(5): 507-527 (2004)
2003
21	EE	Matthew V. Mahoney, Philip K. Chan: Learning Rules for Anomaly Detection of Hostile Network Traffic. ICDM 2003: 601-604
20	EE	Hyoung R. Kim, Philip K. Chan: Learning implicit user interest hierarchy for context in personalization. IUI 2003: 101-108
19	EE	Matthew V. Mahoney, Philip K. Chan: An Analysis of the 1999 DARPA/Lincoln Laboratory Evaluation Data for Network Anomaly Detection. RAID 2003: 220-237
2002
18	EE	Matthew V. Mahoney, Philip K. Chan: Learning nonstationary models of normal network traffic for detecting novel attacks. KDD 2002: 376-385
2001
17	EE	Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan: Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. ICDM 2001: 123-130
16	EE	Salvatore J. Stolfo, Wenke Lee, Philip K. Chan, Wei Fan, Eleazar Eskin: Data Mining-based Intrusion Detectors: An Overview of the Columbia IDS Project. SIGMOD Record 30(4): 5-14 (2001)
1999
15		Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan: AdaCost: Misclassification Cost-Sensitive Boosting. ICML 1999: 97-105
14	EE	Philip K. Chan: Constructing Web User Profiles: A non-invasive Learning Approach. WEBKDD 1999: 39-55
13		Philip K. Chan, Salvatore J. Stolfo, David Wolpert: Guest Editors' Introduction. Machine Learning 36(1-2): 5-7 (1999)
1998
12		Philip K. Chan, Salvatore J. Stolfo: Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection. KDD 1998: 164-168
1997
11		Salvatore J. Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Dave W. Fan, Philip K. Chan: JAM: Java Agents for Meta-Learning over Distributed Databases. KDD 1997: 74-81
10		Philip K. Chan, Salvatore J. Stolfo: On the Accuracy of Meta-Learning for Scalable Data Mining. J. Intell. Inf. Syst. 8(1): 5-28 (1997)
1996
9		Philip K. Chan, Salvatore J. Stolfo: Sharing Learned Models among Remote Database Partitions by Local Meta-Learning. KDD 1996: 2-7
1995
8		Philip K. Chan, Salvatore J. Stolfo: A Comparative Evaluation of Voting and Meta-learning on Partitioned Data. ICML 1995: 90-98
7		Philip K. Chan, Salvatore J. Stolfo: Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning. KDD 1995: 39-44
1993
6	EE	Philip K. Chan, Salvatore J. Stolfo: Experiments on Multi-Strategy Learning by Meta-Learning. CIKM 1993: 314-323
5		Philip K. Chan, Salvatore J. Stolfo: Toward Multi-Strategy Parallel & Distributed Learning in Sequence Analysis. ISMB 1993: 65-73
4	EE	Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-Shapiro: Systems for Knowledge Discovery in Databases. IEEE Trans. Knowl. Data Eng. 5(6): 903-913 (1993)
1991
3		Salvatore J. Stolfo, Ouri Wolfson, Philip K. Chan, Hasanat M. Dewan, Leland Woodbury, Jason S. Glazier, David Ohsie: PARULE: Parallel Rule Processing Using Meta-rules for Redaction. J. Parallel Distrib. Comput. 13(4): 366-382 (1991)
1990
2		Douglas H. Fisher, Philip K. Chan: Statistical guidance in symbolic learning. Ann. Math. Artif. Intell. 2: 135-147 (1990)
1989
1		Philip K. Chan: Inductive Learning with BCT. ML 1989: 104-108

Coauthor Index

1	Hasanat M. Dewan	[3]
2	Eleazar Eskin	[16]
3	Dave W. Fan	[11]
4	Wei Fan	[15] [16] [17] [22]
5	Douglas H. Fisher	[2]
6	Jason S. Glazier	[3]
7	Hyoung R. Kim	[20]
8	Hyoung-rae Kim	[25] [26] [27] [33]
9	Wenke Lee	[11] [16] [17] [22]
10	Richard Lippmann	[30]
11	Matthew V. Mahoney	[18] [19] [21] [28]
12	Christopher J. Matheus	[4]
13	Matthew Miller	[17] [22]
14	Debasis Mitra	[23] [24]
15	David Ohsie	[3]
16	Gregory Piatetsky-Shapiro	[4]
17	Andreas L. Prodromidis	[11]
18	Salvatore J. Stolfo	[3] [5] [6] [7] [8] [9] [10] [11] [12] [13] [15] [16] [17] [22]
19	Gaurav Tandon	[23] [24] [29] [31] [32]
20	Shelley Tselepis	[11]
21	Ouri Wolfson	[3]
22	David Wolpert (David H. Wolpert)	[13]
23	Leland Woodbury	[3]
24	Junxin Zhang	[15]

Colors in the list of coauthors