Todd K. Leen

发表

Detecting mild cognitive loss with continuous monitoring of medication adherence

Deniz Erdogmus, Zhengdong Lu, Yonghong Huang, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria

John E. Moody, Todd K. Leen, J. Moody, 1992, NIPS.

Fast neural network surrogates for very high dimensional physics-based models in computational oceanography

Zhengdong Lu, António M. Baptista, Rudolph van der Merwe, 2007, Neural Networks.

Dimension Reduction by Local Principal Component Analysis

Nanda Kambhatla, Todd K. Leen, N. Kambhatla, 1997, Neural Computation.

Optimal dimension reduction and transform coding with mixture principal components

Todd K. Leen, Cynthia Archer, T. Leen, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Bayesian sensor image fusion using local linear generative models

Ravi K. Sharma, Misha Pavel, Todd K. Leen, 2001 .

Assessing subsets of analytes in context of detecting laboratory errors

Murat Akçakaya, Deniz Erdogmus, Jennifer G. Dy, 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Optimizing Medication Reminders Using a Decision-Theoretic Framework

Misha Pavel, Holly Brügge Jimison, Umut Ozertem, 2010, MedInfo.

Dynamics and VLSI Implementation of Self–Organizing Networks*

Todd K. Leen, Dan Hammerstrom, Eric Means, 1990 .

Using Curvature Information for Fast Stochastic Search

Todd K. Leen, Genevieve B. Orr, G. Orr, 1996, NIPS.

Approximating distributions in stochastic learning

Todd K. Leen, David Nielsen, Robert Friel, 2012, Neural Networks.

Statistical error detection for clinical laboratory tests

Deniz Erdogmus, Todd K. Leen, Steven C. Kazmierczak, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A generalized Lloyd-type algorithm for adaptive transform coder design

Todd K. Leen, Cynthia Archer, 2004, IEEE Transactions on Signal Processing.

From Data Distributions to Regularization in Invariant Learning

Todd K. Leen, T. Leen, 1995, Neural Computation.

Parameterized Novelty Detectors for Environmental Sensor Monitoring

António M. Baptista, Todd K. Leen, Cynthia Archer, 2003, NIPS.

Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals

Zhengdong Lu, Todd K. Leen, Jeffrey A. Kaye, 2011, Neural Computation.

A reproducing kernel Hilbert space framework for pairwise time series distances

Deniz Erdogmus, Zhengdong Lu, Yonghong Huang, 2008, ICML '08.

Advances in Neural Information Processing Systems 11

Rajeev Sharma, Misha Pavel, Todd K. Leen, 1999 .

Fast Pruning Using Principal Components

John E. Moody, Todd K. Leen, Asriel U. Levin, 1993, NIPS.

A Probabilistic Active Learning Algorithm Based on Fisher Information Ratio

Murat Akcakaya, Deniz Erdogmus, Jennifer G. Dy, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning pdf

Murat Akçakaya, Deniz Erdogmus, Jennifer G. Dy, 2016, J. Mach. Learn. Res..

A Fast Histogram-Based Postprocessor That Improves Posterior Probability Estimates

Etienne Barnard, Wei Wei, Todd K. Leen, 1999, Neural Computation.

Classification Active Learning Based on Mutual Information

Murat Akçakaya, Deniz Erdogmus, Jennifer G. Dy, 2016, Entropy.

Multistream video fusion using local principal components analysis

Ravi K. Sharma, Misha Pavel, Todd K. Leen, 1998, Optics & Photonics.

Fast nonlinear dimension reduction

Todd K. Leen, Nanda Kambhatla, N. Kambhatla, 1993, IEEE International Conference on Neural Networks.

Optimal Stochastic Search and Adaptive Momentum

Todd K. Leen, Genevieve B. Orr, G. Orr, 1993, NIPS.

A novel delta check method for detecting laboratory errors

Murat Akçakaya, Deniz Erdogmus, Todd K. Leen, 2015, 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP).

Perturbation theory for stochastic learning dynamics

Todd K. Leen, Robert Friel, 2011, The 2011 International Joint Conference on Neural Networks.

Classifying with Gaussian Mixtures and Clusters

Nanda Kambhatla, Todd K. Leen, 1994, NIPS.

Automatic Prediction of Trauma Registry Procedure Codes from Emergency Room Dictations

William R. Hersh, Todd K. Leen, Susan Malveau, 1998, MedInfo.

Fast Non-Linear Dimension Reduction

Nanda Kambhatla, Todd K. Leen, N. Kambhatla, 1993, NIPS.

Adaptive Principal Component Analysis

Todd K. Leen, Cynthia Archer, 2002 .

Two Approaches to Optimal Annealing

David Saad, Todd K. Leen, Bernhard Schottky, 1997, NIPS.

Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times

Todd K. Leen, Genevieve B. Orr, G. Orr, 1992, NIPS.

Penalized Probabilistic Clustering

Zhengdong Lu, Todd K. Leen, T. Leen, 2007, Neural Computation.

Semi-supervised Learning with Penalized Probabilistic Clustering

Zhengdong Lu, Todd K. Leen, T. Leen, 2004, NIPS.

From Mixtures of Mixtures to Adaptive Transform Coding

Todd K. Leen, Cynthia Archer, 2000, NIPS.

Anti-Hebbian Spike-Timing-Dependent Plasticity and Adaptive Sensory Processing

Todd K. Leen, Patrick D. Roberts, T. Leen, 2010, Front. Comput. Neurosci..

Hierarchical Fisher Kernels for Longitudinal Data

Zhengdong Lu, Todd K. Leen, Jeffrey A. Kaye, 2008, NIPS.

Erratum to "Fast neural network surrogates for very high dimensional physics-based models in computational oceanography" [Neural Netw. 20(4) (2007) 462-478]

Zhengdong Lu, António M. Baptista, Rudolph van der Merwe, 2007, Neural Networks.

Dynamics of Learning in Recurrent Feature-Discovery Networks

Todd K. Leen, 1990, NIPS.

A framework for representing non-stationary data with mixtures of linear models

Todd K. Leen, Cynthia Archer, 2002 .

Stochastic Learning Dynamics and Non-Linear Dimension Reduction.

Todd K. Leen, 1994 .

Compression of line spectral frequency parameters using the asynchronous interpolation model

Todd K. Leen, Alexander Kain, 2010, SSW.

Probabilistic Image Sensor Fusion

Ravi K. Sharma, Misha Pavel, Todd K. Leen, 1998, NIPS.

Hebbian feature discovery improves classifier efficiency

Todd K. Leen, Dan Hammerstrom, Mike Rudnick, 1990, 1990 IJCNN International Joint Conference on Neural Networks.

Feature selection for improved classification

Todd K. Leen, F. E. Shaudys, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

The coding-optimal transform

Todd K. Leen, Cynthia Archer, 2001, Proceedings DCC 2001. Data Compression Conference.

Stochastic Perturbation Methods for Spike-Timing-Dependent Plasticity

Todd K. Leen, Robert Friel, T. Leen, 2012, Neural Computation.

Optimal asymptotic learning rate: Macroscopic versus microscopic dynamics

David Saad, Todd K. Leen, Bernhard Schottky, 1999 .

Theory and practice of proximity correction by secondary exposure

Todd K. Leen, T. Leen, 1989 .

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error

Deniz Erdogmus, Todd K. Leen, Steven C. Kazmierczak, 2007, Clinical chemistry and laboratory medicine.

Author's Personal Copy Dynamics of Atmospheres and Oceans Fast Data Assimilation Using a Nonlinear Kalman Filter and a Model Surrogate: an Application to the Columbia River Estuary

António M. Baptista, Rudolph van der Merwe, Todd K. Leen, 2022 .

Exact and perturbation solutions for the ensemble dynamics

Todd K. Leen, T. Leen, 1999 .

Sequential Data Assimilation with Sigma-point Kalman Filter on Low-dimensional Manifold June 23 , 2007 DRAFT-DO NOT CIRCULATE

Zhengdong Lu, Rudolph van der Merwe, Todd K. Leen, 2007 .