Todd K. Leen - RankMe

46 papers A* 1B 4Misc 1Journal 15Unranked 22

Year	Rank	Type	Title / Venue / Authors
2018	J	`jnl`	A Probabilistic Active Learning Algorithm Based on Fisher Information Ratio. IEEE Trans. Pattern Anal. Mach. Intell. Jamshid Sourati, Murat Akçakaya, Deniz Erdogmus, Todd K. Leen, Jennifer G. Dy
2017	J	`jnl`	Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning. J. Mach. Learn. Res. Jamshid Sourati, Murat Akçakaya, Todd K. Leen, Deniz Erdogmus, Jennifer G. Dy
2016	—	`conf`	Assessing subsets of analytes in context of detecting laboratory errors. EMBC Jamshid Sourati, Steven C. Kazmierczak, Murat Akçakaya, Jennifer G. Dy, Todd K. Leen, Deniz Erdogmus
2016	J	`jnl`	Asymptotic Analysis of Objectives based on Fisher Information in Active Learning. CoRR Jamshid Sourati, Murat Akçakaya, Todd K. Leen, Deniz Erdogmus, Jennifer G. Dy
2016	J	`jnl`	Classification Active Learning Based on Mutual Information. Entropy Jamshid Sourati, Murat Akçakaya, Jennifer G. Dy, Todd K. Leen, Deniz Erdogmus
2015	—	`conf`	A novel delta check method for detecting laboratory errors. MLSP Jamshid Sourati, Deniz Erdogmus, Murat Akçakaya, Steven C. Kazmierczak, Todd K. Leen
2012	J	`jnl`	Approximating distributions in stochastic learning. Neural Networks Todd K. Leen, Robert Friel, David Nielsen
2012	—	`conf`	Statistical error detection for clinical laboratory tests. EMBC Todd K. Leen, Deniz Erdogmus, Steven C. Kazmierczak
2012	J	`jnl`	Stochastic Perturbation Methods for Spike-Timing-Dependent Plasticity. Neural Comput. Todd K. Leen, Robert Friel
2011	J	`jnl`	Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals. Neural Comput. Zhengdong Lu, Todd K. Leen, Jeffrey A. Kaye
2011	B	`conf`	Perturbation theory for stochastic learning dynamics. IJCNN Todd K. Leen, Robert Friel
2010	J	`jnl`	Anti-Hebbian Spike-Timing-Dependent Plasticity and Adaptive Sensory Processing. Frontiers Comput. Neurosci. Patrick D. Roberts, Todd K. Leen
2010	—	`conf`	Compression of line spectral frequency parameters using the asynchronous interpolation model. SSW Alexander Kain, Todd K. Leen
2010	—	`conf`	Optimizing Medication Reminders Using a Decision-Theoretic Framework. MedInfo Misha Pavel, Holly Brügge Jimison, Tamara L. Hayes, Nicole Larimer, Stuart Hagler, Yves Vimegnon, Todd K. Leen, Umut Ozertem
2008	A*	`conf`	A reproducing kernel Hilbert space framework for pairwise time series distances. ICML Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz Erdogmus
2008	Misc	`conf`	Detecting mild cognitive loss with continuous monitoring of medication adherence. ICASSP Yonghong Huang, Deniz Erdogmus, Zhengdong Lu, Todd K. Leen
2008	—	`conf`	Hierarchical Fisher Kernels for Longitudinal Data. NIPS Zhengdong Lu, Todd K. Leen, Jeffrey A. Kaye
2007	J	`jnl`	Erratum to "Fast neural network surrogates for very high dimensional physics-based models in computational oceanography" [Neural Netw. 20(4) (2007) 462-478]. Neural Networks Rudolph van der Merwe, Todd K. Leen, Zhengdong Lu, Sergey Frolov, António M. Baptista
2007	J	`jnl`	Fast neural network surrogates for very high dimensional physics-based models in computational oceanography. Neural Networks Rudolph van der Merwe, Todd K. Leen, Zhengdong Lu, Sergey Frolov, António M. Baptista
2007	J	`jnl`	Penalized Probabilistic Clustering. Neural Comput. Zhengdong Lu, Todd K. Leen
2004	J	`jnl`	A generalized Lloyd-type algorithm for adaptive transform coder design. IEEE Trans. Signal Process. Cynthia Archer, Todd K. Leen
2004	—	`conf`	Semi-supervised Learning with Penalized Probabilistic Clustering. NIPS Zhengdong Lu, Todd K. Leen
2003	—	`conf`	Parameterized Novelty Detectors for Environmental Sensor Monitoring. NIPS Cynthia Archer, Todd K. Leen, António M. Baptista
2001	—	`ed.`	Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA NIPS Todd K. Leen, Thomas G. Dietterich, Volker Tresp
2001	B	`conf`	The Coding-Optimal Transform. Data Compression Conference Cynthia Archer, Todd K. Leen
2000	—	`ed.`	Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999] NIPS Sara A. Solla, Todd K. Leen, Klaus-Robert Müller
2000	—	`conf`	From Mixtures of Mixtures to Adaptive Transform Coding. NIPS Cynthia Archer, Todd K. Leen
1999	J	`jnl`	A Fast Histogram-Based Postprocessor That Improves Posterior Probability Estimates. Neural Comput. Wei Wei, Todd K. Leen, Etienne Barnard
1999	B	`conf`	Optimal dimension reduction and transform coding with mixture principal components. IJCNN Cynthia Archer, Todd K. Leen
1998	—	`conf`	Automatic Prediction of Trauma Registry Procedure Codes from Emergency Room Dictations. MedInfo William R. Hersh, Todd K. Leen, P. Steve Rehfuss, Susan Malveau
1998	—	`conf`	Probabilistic Image Sensor Fusion. NIPS Ravi K. Sharma, Todd K. Leen, Misha Pavel
1997	J	`jnl`	Dimension Reduction by Local Principal Component Analysis. Neural Comput. Nanda Kambhatla, Todd K. Leen
1997	—	`conf`	Two Approaches to Optimal Annealing. NIPS Todd K. Leen, Bernhard Schottky, David Saad
1996	—	`conf`	Using Curvature Information for Fast Stochastic Search. NIPS Genevieve B. Orr, Todd K. Leen
1995	—	`ed.`	Advances in Neural Information Processing Systems 7, [NIPS Conference, Denver, Colorado, USA, 1994] NIPS Gerald Tesauro, David S. Touretzky, Todd K. Leen
1995	J	`jnl`	From Data Distributions to Regularization in Invariant Learning. Neural Comput. Todd K. Leen
1994	—	`conf`	Classifying with Gaussian Mixtures and Clusters. NIPS Nanda Kambhatla, Todd K. Leen
1994	—	`conf`	From Data Distributions to Regularization in Invariant Learning. NIPS Todd K. Leen
1993	—	`conf`	Fast Non-Linear Dimension Reduction. NIPS Nanda Kambhatla, Todd K. Leen
1993	—	`conf`	Fast Pruning Using Principal Components. NIPS Asriel U. Levin, Todd K. Leen, John E. Moody
1993	—	`conf`	Fast nonlinear dimension reduction. ICNN Nandakishore Kambhatla, Todd K. Leen
1993	—	`conf`	Optimal Stochastic Search and Adaptive Momentum. NIPS Todd K. Leen, Genevieve B. Orr
1992	—	`conf`	Weight Space Probability Densities in Stochastic Learning: I. Dynamics and Equilibria. NIPS Todd K. Leen, John E. Moody
1992	—	`conf`	Weight Space Probability Densities in Stochastic Learning: II. Transients and Basin Hopping Times. NIPS Genevieve B. Orr, Todd K. Leen
1990	—	`conf`	Dynamics of Learning in Recurrent Feature-Discovery Networks. NIPS Todd K. Leen
1990	B	`conf`	Hebbian feature discovery improves classifier efficiency. IJCNN Todd K. Leen, Mike Rudnick, Dan Hammerstrom