Marcus A. Maloof

发表

An Adaptive Architecture for Hierarchical Vision Systems

Marcus A. Maloof, 2000 .

A method for partial-memory incremental learning and its application to computer intrusion detection

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1995, Proceedings of 7th IEEE International Conference on Tools with Artificial Intelligence.

Some Basic Concept of Machine Learning and Data Mining

Marcus A. Maloof, M. Maloof, 2006 .

Incremental Learning with Partial Instance Memory

Ryszard S. Michalski, Marcus A. Maloof, 2002, ISMIS.

A General Model for Finite-Sample Effects in Training and Testing of Competing Classifiers

Marcus A. Maloof, R. F. Wagner, Sergey V. Beiden, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Learning to detect malicious executables in the wild

Marcus A. Maloof, J. Zico Kolter, J. Z. Kolter, 2004, KDD.

Learning to Detect and Classify Malicious Executables in the Wild

Marcus A. Maloof, J. Zico Kolter, J. Z. Kolter, 2006, J. Mach. Learn. Res..

An Initial Study of an Adaptive Hierarchical Vision System

Marcus A. Maloof, M. Maloof, 2000, ICML.

HOW DID AQ FACE THE EAST-WEST CHALLENGE? An Analysis of the AQ Family's Performance in the 2nd International Competition of Machine Learning Programs

Kenneth A. Kaufman, Ryszard S. Michalski, Marcus A. Maloof, 1995 .

elicit: A System for Detecting Insiders Who Violate Need-to-Know

Marcus A. Maloof, Gregory D. Stephens, 2007, RAID.

Marcus A. Maloof, 2009, Encyclopedia of Biometrics.

On the Performance of Online Learning Methods for Detecting Malicious Executables

Marcus A. Maloof, M. Maloof, 2009 .

ROC components-of-variance analysis of competing classifiers

Marcus A. Maloof, Sergey V. Beiden, Robert F. Wagner, 2002, SPIE Medical Imaging.

Paired Learners for Concept Drift

Marcus A. Maloof, Stephen H. Bach, M. Maloof, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Incremental learning with partial instance memory

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 2002, Artif. Intell..

Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts

Marcus A. Maloof, J. Zico Kolter, J. Z. Kolter, 2007, J. Mach. Learn. Res..

Learning Evolving Concepts Using Partial Memory Approach

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1995 .

Progressive partial memory learning

Marcus A. Maloof, M. Maloof, 1997 .

Learning to Detect Malicious Executables

Marcus A. Maloof, J. Z. Kolter, Jeremy Z. Kolter, 2006 .

A Bayesian Approach to Concept Drift

Marcus A. Maloof, Stephen H. Bach, M. Maloof, 2010, NIPS.

Dynamic weighted majority: a new ensemble method for tracking concept drift

Marcus A. Maloof, J. Zico Kolter, J. Z. Kolter, 2003, Third IEEE International Conference on Data Mining.

Improved Rooftop Detection in Aerial Images with Machine Learning

Ramakant Nevatia, Marcus A. Maloof, Pat Langley, 2003, Machine Learning.

MACHINE LEARNING AND DATA MINING FOR COMPUTER SECURITY: METHODS AND APPLICATIONS

Marcus A. Maloof, 2011 .

Design of a Machine Learning Architecture for Hierarchical Vision Systems

Marcus A. Maloof, 1999 .

On machine learning, ROC analysis, and statistical tests of significance

Marcus A. Maloof, 2002, Object recognition supported by user interaction for service robots.

Multi-class Traffic Morphing for Encrypted VoIP Communication

Micah Sherr, Marcus A. Maloof, Henry Tan, 2015, Financial Cryptography.

Machine Learning and Data Mining for Computer Security

Marcus A. Maloof, M. Maloof, 2006 .

Machine Learning and Data Mining for Computer Security: Methods and Applications (Advanced Information and Knowledge Processing)

Marcus A. Maloof, M. Maloof, 2005 .

10 Learning Patterns in Images

Azriel Rosenfeld, Ryszard S. Michalski, Marcus A. Maloof, 2002 .

Improving Rooftop Detection in Aerial Images Through Machine Learning

Marcus A. Maloof, Pat Langley, Thomas O. Binford, 1998 .

Using additive expert ensembles to cope with concept drift

Marcus A. Maloof, J. Zico Kolter, J. Z. Kolter, 2005, ICML.

The AQ Methods for Concept Drift

Marcus A. Maloof, M. Maloof, 2010, Advances in Machine Learning I.

AQ-PM: A Method for Partial Memory Learning

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1999 .

Partial Memory Learning System AQ-PM: The Method and User's Guide

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1996 .

Detecting Insider Theft of Trade Secrets

Marcus A. Maloof, Deanna D. Caputo, Gregory D. Stephens, 2009, IEEE Security & Privacy.

Generalizing over aspect and location for rooftop detection

Ramakant Nevatia, Marcus A. Maloof, Pat Langley, 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

Selecting Examples for Partial Memory Learning

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 2000, Machine Learning.

Learning Descriptions of 2D Shapes for Object Recognition and X-Ray Images

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1994 .

A Partial Memory Incremental Learning Methodology and its Application to Computer Intrusion Detection

Ryszard S. Michalski, Marcus A. Maloof, 1995 .

LEARNING SYMBOLIC DESCRIPTIONS OF 2 D SHAPES FOR OBJECT RECOGNITION IN X-RAY IMAGES

Ryszard S. Michalski, Marcus A. Maloof, R. Michalski, 1995 .

Analysis of Competing Classifiers using Components of Variance of roc Accuracy Measures

Marcus A. Maloof, Sergey V. Beiden, Robert F. Wagner, .