引用次数
引用: 3,900
H-指数: 33
I10-指数 : 62
出版物: 134
Learned Subproblem Selection Techniques for Combinatorial Optimization
A. G. Barto , R. Moll , T. J. Perkins
University of Massachusetts
1
1999
Lyapunov Methods for Reinforcement Learnin: A PhD Thesis Proposal Draft
T. J. Perkins
University of Massachusetts
1999
Reinforcement Learning with Stability Guarantees TITLE2
S. E. Engelbrecht , A. G. Barto , T. J. Perkins
University of Massachusetts
2000
Statistical lower bounds on protein copy number from fluorescence expression images
L. Zamparo , T. J. Perkins
Bioinformatics 25 ( 20) 2670 -2676
11
2009
Noisy information processing through transcriptional regulation
E. Libby , T. J. Perkins , P. S. Swain
Proceedings of the National Academy of Sciences of the United States of America 104 ( 17) 7151 -7156
82
2007
The gap gene system of Drosophila melanogaster: model-fitting and validation.
T. J. PERKINS
Annals of the New York Academy of Sciences 1115 ( 1) 116 -131
5
2007
Lyapunov-Constrained Action Sets for Reinforcement Learning
Andrew G. Barto , Theodore J. Perkins
international conference on machine learning 409 -416
15
2001
Lyapunov methods for safe intelligent agent design
Andrew G. Barto , Theodore J. Perkins
University of Massachusetts Amherst
7
2002
Using Options for Knowledge Transfer in Reinforcement Learning
Doina Precup , Theodore J. Perkins
38
1999
On the Existence of Fixed Points for Q-Learning and Sarsa in Partially Observable Domains
Mark D. Pendrith , Theodore J. Perkins
international conference on machine learning 490 -497
49
2002
Reinforcement learning for POMDPs based on action values and stochastic optimization
Theodore J. Perkins
national conference on artificial intelligence 199 -204
47
2002
A Convergent Form of Approximate Policy Iteration
Doina Precup , Theodore J. Perkins
neural information processing systems 15 1627 -1634
72
2002
Maximum likelihood trajectories for continuous-time Markov chains
Theodore J. Perkins
neural information processing systems 22 1437 -1445
14
2009
Lyapunov design for safe reinforcement learning
Andrew G. Barto , Theodore J. Perkins
Journal of Machine Learning Research 3 803 -832
197
2003
Learning a Cost Function for Interactive Microscope Image Segmentation
Sharmin Nilufar , Theodore J. Perkins
national conference on artificial intelligence
2
2014
Automatic Detection of Filopodia from Fluorescence Microscopy Images.
Anne Morrow , Jonathan Lee , Sharmin Nilufar , Theodore J. Perkins
IWBBIO 251 -252
2013
Optimal Risk in Multiagent Blind Tournaments
Theodore J. Perkins
adaptive agents and multi-agents systems 2159 -2161
2019
WACS: improving ChIP-seq peak calling by optimally weighting controls.
Marcel Turcotte , Aseel Awdeh , Aseel Awdeh , Theodore J. Perkins
BMC Bioinformatics 22 ( 1) 69 -69
1
2021
Estimating the Stochastic Bifurcation Structure of Cellular Networks
Carl Song , Hilary Phenix , Vida Abedi , Matthew Scott
PLoS Computational Biology 6 ( 3) e1000699
53
2010
Methods for Determining the Statistical Significance of Enrichment or Depletion of Gene Ontology Classifications under Weighted Membership
Ernesto Iacucci , Hans H. Zingg , Theodore J. Perkins
Frontiers in Genetics 3 24 -24
2012