Edwin P. D. Pednault

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Extending Conventional Planning Techniques to Handle Actions with Context-Depen dent Effects

Edwin P. D. Pednault, 1988, AAAI.

Segmentation-based modeling for advanced targeted marketing

Edwin P. D. Pednault, Chidanand Apté, Eric Bibelnieks, 2001, KDD '01.

Handling Imbalanced Data Sets in Insurance Risk Modeling

Edwin P. D. Pednault, Barry K. Rosen, Chidanand Apte, 2000 .

Probabilistic estimation-based data mining for discovering insurance risks

Edwin P. D. Pednault, Barry K. Rosen, Brian F. White, 1999, IEEE Intell. Syst..

Data-intensive analytics for predictive modeling

Sholom M. Weiss, Edwin P. D. Pednault, Chidanand Apté, 2003, IBM J. Res. Dev..

Segmented Regression Estimators for Massive Data Sets

Edwin P. D. Pednault, Ramesh Natarajan, 2002, SDM.

IBM Research Report The Parallel Machine Learning (PML) Framework and the Transform Regression Algorithm

Edwin P. D. Pednault, Amol Ghoting, Sitaram Asur, 2009 .

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Ramakrishnan Kannan, Edwin P. D. Pednault, Amol Ghoting, 2011, KDD.

Transform Regression and the Kolmogorov Superposition Theorem

Edwin P. D. Pednault, E. Pednault, 2006, SDM.

Reading handwritten digits: a ZIP code recognition system

Lawrence D. Jackel, Yann LeCun, Edwin P. D. Pednault, 1992, Computer.

Business applications of data mining

Padhraic Smyth, Bing Liu, Edwin P. D. Pednault, 2002, CACM.

Decomposition of Heterogeneous Classification Problems

Edwin P. D. Pednault, Chidanand Apté, Jonathan R. M. Hosking, 1997, IDA.

Generalizing Nonlinear Planning to Handle Complex Goals and Actions with Context-Dependent Effects

Edwin P. D. Pednault, E. Pednault, 1991, IJCAI.

A statistical perspective on data mining

Madhu Sudan, Edwin P. D. Pednault, Jonathan R. M. Hosking, 1997, Future Gener. Comput. Syst..

Trends and outlook for the massive-scale analytics stack

Mark S. Squillante, John A. Gunnels, Edwin P. D. Pednault, 2013, IBM J. Res. Dev..

Scaling Up Machine Learning: The Transform Regression Algorithm

Edwin P. D. Pednault, Ramesh Natarajan, 2011 .

Empirical comparison of various reinforcement learning strategies for sequential targeted marketing

Haixun Wang, Naoki Abe, Bianca Zadrozny, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Theory and Application of Minimal-Length Encoding: 1990 AAAI Spring Symposium Report

Edwin P. D. Pednault, 1991, AI Mag..

Probabilistic Estimation in Data Mining

Edwin P. D. Pednault, Chidanand Apte, 2001 .

Decomposition of Heterogeneous Classification Problems

Edwin P. D. Pednault, Chidanand Apté, Jonathan R. M. Hosking, 1997, Intell. Data Anal..

Using Simulated Pseudo Data To Speed Up Statistical Predictive Modeling From Massive Data Sets

Edwin P. D. Pednault, Ramesh Natarajan, E. Pednault, 2001, SDM.

Minimal-Length Encoding and Inductive Inference

Edwin P. D. Pednault, 1991, Knowledge Discovery in Databases.

SystemML: Declarative machine learning on MapReduce

Shirish Tatikonda, Rajasekar Krishnamurthy, Berthold Reinwald, 2011, 2011 IEEE 27th International Conference on Data Engineering.

Deep issues: representation is everything.

Edwin P. D. Pednault, 2000 .

Representation is everything

Edwin P. D. Pednault, 2000, CACM.

A probabilistic estimation framework for predictive modeling analytics

Edwin P. D. Pednault, Chidanand Apté, Ramesh Natarajan, 2002, IBM Syst. J..

Some Experiments in Applying Inductive Inference Principles to Surface Reconstruction

Edwin P. D. Pednault, E. Pednault, 1989, IJCAI.

FORMULATING MULTIAGENT, DYNAMIC-WORLD PROBLEMS IN THE CLASSICAL PLANNING FRAMEWORK

Edwin P. D. Pednault, E. Pednault, 1987 .

Scaling Up Machine Learning: IBM Parallel Machine Learning Toolbox

Edwin P. D. Pednault, Amol Ghoting, Elad Yom-Tov, 2011 .

Sequential cost-sensitive decision making with reinforcement learning

Naoki Abe, Bianca Zadrozny, Edwin P. D. Pednault, 2002, KDD.

CRM Analytics Framework

Mukesh K. Mohania, Ramakrishnan Kannan, Edwin P. D. Pednault, 2009, COMAD.

Inferring probabilistic theories from data

Edwin P. D. Pednault, 1988, AAAI 1988.

A neural network approach to handprint character recognition

Lawrence D. Jackel, Yann LeCun, Edwin P. D. Pednault, 1991, COMPCON Spring '91 Digest of Papers.

ADL: Exploring the Middle Ground Between STRIPS and the Situation Calculus

Edwin P. D. Pednault, E. Pednault, 1989, KR.

On the Independence Assumption Underlying Subjective Bayesian Updating

Steven W. Zucker, Edwin P. D. Pednault, L. V. Muresan, 1981, Artif. Intell..

Synthesizing plans that contain actions with context‐dependent effects 1

Edwin P. D. Pednault, E. Pednault, 1988, Comput. Intell..

ADL and the State-Transition Model of Action

Edwin P. D. Pednault, E. Pednault, 1994, J. Log. Comput..

Infering Probabilistic Theofies from Data

Edwin P. D. Pednault, 1988, AAAI.

Embedded predictive modeling in a parallel relational database

Edwin P. D. Pednault, Ramesh Natarajan, Fateh Tipu, 2006, SAC.

OF DATA MINING

Bing Liu, Padhraic Smyth, Edwin P. D. Pednault, 2002 .

The Importance of Estimation Errors in Cost-Sensitive Learning

Edwin P. D. Pednault, Barry K. Rosen, Chidanand Apte, .