Theodore J. Perkins

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Two Search Techniques for Imperfect Information Games and Application to Hearts

Theodore J. Perkins, 1998 .

Scheduling contract algorithms on multiple processors

Shlomo Zilberstein, Theodore J. Perkins, Daniel S. Bernstein, 2002, AAAI/IAAI.

Maximum Probability Reaction Sequences in Stochastic Chemical Kinetic Systems

Theodore J. Perkins, Maryam Salehi, T. Perkins, 2010, Front. Physio..

Analysis of Controls in ChIP-seq

Theodore J. Perkins, Aseel Awdeh, 2017, BCB.

Learning a cost function for microscope image segmentation

Theodore J. Perkins, Sharmin Nilufar, T. Perkins, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Trade-Off between Sample Complexity and Computational Complexity in Learning Boolean Networks from Time-Series Data

Michael T. Hallett, Theodore J. Perkins, 2010, IEEE ACM Trans. Comput. Biol. Bioinform..

RECAP reveals the true statistical significance of ChIP-seq peak calls

Theodore J. Perkins, Aseel Awdeh, Justin G. Chitpin, 2018 .

State Sequence Analysis in Hidden Markov Models

Theodore J. Perkins, Yuri Grinberg, 2015, UAI.

COGEM: A Toolbox for Computational Genomics in Matlab

Theodore J. Perkins, 2017 .

Learning-based interactive segmentation using the maximum mean cycle weight formalism

Doina Precup, Theodore J. Perkins, D. Yang, 2017, Medical Imaging.

Optimal Risk in Multiagent Blind Tournaments

Theodore J. Perkins, 2019, AAMAS.

A scaling law for random walks on networks

Theodore J. Perkins, Roderick Edwards, Eric Foxall, 2014, Nature Communications.

Lyapunov Design for Safe Reinforcement Learning

Andrew G. Barto, Theodore J. Perkins, A. Barto, 2003, J. Mach. Learn. Res..

Methods for Determining the Statistical Significance of Enrichment or Depletion of Gene Ontology Classifications under Weighted Membership

Theodore J. Perkins, Ernesto Iacucci, Hans H. Zingg, 2011, Front. Gene..

On the Existence of Fixed Points for Q-Learning and Sarsa in Partially Observable Domains

Theodore J. Perkins, Mark D. Pendrith, T. Perkins, 2002, ICML.

Maximum likelihood trajectories for continuous-time Markov chains

Theodore J. Perkins, 2009, NIPS.

Faculty of Graduate and Postdoctoral Studies

Theodore J. Perkins, Pavel Levin, T. Perkins, 2012 .

Learning to Detect Contours with Dynamic Programming Snakes

Theodore J. Perkins, Sharmin Nilufar, T. Perkins, 2014, 2014 22nd International Conference on Pattern Recognition.

Robust dynamics in minimal hybrid models of genetic networks

Theodore J. Perkins, Roy Wilds, Leon Glass, 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data

Theodore J. Perkins, Christopher J. Porter, Parameswaran Ramachandran, 2013, Bioinform..

Super-enhancer Dynamics Throughout Myogenesis

Theodore J. Perkins, Basma Abdelkarim, 2017, BCB.

FiloDetect: automatic detection of filopodia from fluorescence microscopy images

Theodore J. Perkins, Sharmin Nilufar, Jonathan Lee, 2013, BMC Systems Biology.

Reverse Engineering the Gap Gene Network of Drosophila melanogaster

Leon Glass, Theodore J. Perkins, Johannes Jaeger, 2006, PLoS Comput. Biol..

Learning Instance-Independent Value Functions to Enhance Local Search

Richard S. Sutton, Andrew G. Barto, Theodore J. Perkins, 1998, NIPS.

Implementing Arithmetic and Other Analytic Operations By Transcriptional Regulation

Theodore J. Perkins, Sean M. Cory, T. Perkins, 2008, PLoS Comput. Biol..

Fully polynomial-time computation of maximum likelihood trajectories in Markov chains

Theodore J. Perkins, Yuri Grinberg, 2017, Inf. Process. Lett..

A Convergent Form of Approximate Policy Iteration

Doina Precup, Theodore J. Perkins, Doina Precup, 2002, NIPS.

Quantitative Epistasis Analysis and Pathway Inference from Genetic Interaction Data

Liu Yang, Theodore J. Perkins, Vida Abedi, 2011, PLoS Comput. Biol..

Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis

Andrew G. Barto, Theodore J. Perkins, A. Barto, 2001, IJCAI.

Statistical lower bounds on protein copy number from fluorescence expression images

Theodore J. Perkins, Lee Zamparo, T. Perkins, 2009, Bioinform..

Estimating the Stochastic Bifurcation Structure of Cellular Networks

Theodore J. Perkins, Vida Abedi, Mads Kærn, 2010, PLoS Comput. Biol..

Lyapunov methods for safe intelligent agent design

Theodore J. Perkins, Andrew G. Barto, 2002 .

Introduction to Machine Learning and Bioinformatics

George Michailidis, Theodore J. Perkins, Sushmita Mitra, 2008 .

Using Options for Knowledge Transfer in Reinforcement Learning

Doina Precup, Theodore J. Perkins, Doina Precup, 1999 .

Reinforcement learning for POMDPs based on action values and stochastic optimization

Theodore J. Perkins, T. Perkins, 2002, AAAI/IAAI.

On cross-conditional and fluctuation correlations in competitive RNA networks

Theodore J. Perkins, Matthew MacLeod, Daniel Sánchez-Taltavull, 2016, Bioinform..

Machine Learning for Subproblem Selection

Andrew G. Barto, Theodore J. Perkins, Robert Moll, 2000, ICML.

Learning a Cost Function for Interactive Microscope Image Segmentation

Theodore J. Perkins, Sharmin Nilufar, T. Perkins, 2014, AAAI Workshop: Modern Artificial Intelligence for Health Analytics.

Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach

Nathalie Japkowicz, Theodore J. Perkins, Mohamed A. Ghadie, 2015, Bioinform..

Lyapunov-Constrained Action Sets for Reinforcement Learning

Andrew G. Barto, Theodore J. Perkins, A. Barto, 2001, ICML.

The potential power of dynamics in epistasis analysis

Theodore J. Perkins, Aseel Awdeh, Mads Kærn, 2015, BCB.

Dynamics in Epistasis Analysis

Theodore J. Perkins, Aseel Awdeh, Mads Kærn, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

WACS: improving ChIP-seq peak calling by optimally weighting controls

Theodore J. Perkins, Aseel Awdeh, Marcel Turcotte, 2021, BMC Bioinform..

Pooled Screening for Synergistic Interactions Subject to Blocking and Noise

Doina Precup, Theodore J. Perkins, Kyle Li, 2014, PloS one.

WACS: Improving Peak Calling by Optimally Weighting Controls

Theodore J. Perkins, Aseel Awdeh, Marcel Turcotte, 2019 .

BIDCHIPS: bias decomposition and removal from ChIP-seq data clarifies true binding signal and its functional correlates

Theodore J. Perkins, Parameswaran Ramachandran, Gareth A. Palidwor, 2015, Epigenetics & Chromatin.

A General Model of Codon Bias Due to GC Mutational Bias

Theodore J. Perkins, Xuhua Xia, Gareth A. Palidwor, 2010, PloS one.