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Paul Rodríguez
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. The links to all actual bibliographies of persons of the same or a similar name can be found below. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Other persons with the same name
- Paul Rodríguez 0001
(aka: Paul A. Rodríguez, Paul Rodríguez V.) — Pontifical Catholic University of Peru, Department of Electrical Engineering, Lima, Peru (and 1 more)
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2020 – today
- 2023
- [j9]Rodrigo García
, José Aguilar, Mauricio Toro, Nelson Pérez
, Ángel Pinto, Paul Rodríguez:
Autonomic computing in a beef-production process for Precision Livestock Farming. J. Ind. Inf. Integr. 31: 100425 (2023) - [j8]Arunav Gupta
, John Ge, John Li
, Zihao Kong, Kaiwen He, Matthew Mikhailov, Bryan Chin, Xiaochen Li
, Maximilian Apodaca, Paul Rodríguez, Mahidhar Tatineni, Mary P. Thomas
, Santosh Bhatt:
Critique of: "A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery" by SCC Team From UC San Diego. IEEE Trans. Parallel Distributed Syst. 34(6): 1727-1730 (2023) - [c19]Rommie E. Amaro
, Jiunn-Yeu Chen
, Javier M. Duarte
, Thomas E. Hutton
, Christopher Irving
, Martin C. Kandes
, Amit Majumdar
, Dmitry Y. Mishin
, Mai H. Nguyen
, Paul Rodríguez
, Fernando Silva
, Robert S. Sinkovits
, Shawn M. Strande
, Mahidhar Tatineni
, Leon Si Tran
, Nicole Wolter
:
Voyager - An Innovative Computational Resource for Artificial Intelligence & Machine Learning Applications in Science and Engineering. PEARC 2023: 278-282 - [c18]Mary P. Thomas
, Andreas W. Götz
, Martin C. Kandes
, Mai H. Nguyen
, Paul Rodríguez
, Peter W. Rose
, Robert S. Sinkovits
:
Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research. PEARC 2023: 390-394 - [i1]Gustavo Silva, Paul Rodríguez:
Optimal Hyperparameter ε for Adaptive Stochastic Optimizers through Gradient Histograms. CoRR abs/2311.11532 (2023) - 2021
- [j7]Alison Langmead, Christopher J. Nygren, Paul Rodríguez, Alan B. Craig:
Leonardo, Morelli, and the Computational Mirror. Digit. Humanit. Q. 15(1) (2021) - [c17]Duong-Hung Pham, Adrian Basarab, Jean-Pierre Remenieras, Paul Rodríguez, Denis Kouamé:
Fast High Resolution Blood Flow Estimation and Clutter Rejection Via an Alternating Optimization Problem. ISBI 2021: 1907-1910 - 2020
- [j6]Rodrigo García
, José Aguilar, Mauricio Toro, Ángel Pinto, Paul Rodríguez:
A systematic literature review on the use of machine learning in precision livestock farming. Comput. Electron. Agric. 179: 105826 (2020) - [c16]Paul Rodríguez, Alan B. Craig, Alison Langmead, Christopher J. Nygren
:
Extracting and Analyzing Deep Learning Features for Discriminating Historical Art: Deep Learning Features and Art. PEARC 2020: 358-363
2010 – 2019
- 2019
- [c15]Paul Rodríguez:
X-ray CT reconstruction via 𝓁0 gradient projection. CAMSAP 2019: 306-310 - [c14]Paul Rodríguez:
Improving FISTA's Speed of Convergence via a Novel Inertial Sequence. EUSIPCO 2019: 1-5 - [c13]Joël Goossens, Xavier Poczekajlo, Antonio Paolillo, Paul Rodríguez:
ACCEPTOR: a model and a protocol for real-time multi-mode applications on reconfigurable heterogeneous platforms. RTNS 2019: 209-219 - 2018
- [c12]Tristan Fautrel, Laurent George
, Joël Goossens, Damien Masson, Paul Rodríguez:
APractical Sub-Optimal Solution for the Dual Priority Scheduling Problem. SIES 2018: 1-10 - 2017
- [c11]Alison Langmead, Paul Rodríguez, Sandeep Puthanveetil Satheesan
, Alan B. Craig:
Extracting Meaningful Data from Decomposing Bodies. PEARC 2017: 41:1-41:8 - [c10]Paul Rodríguez, Sandeep Puthanveetil Satheesan
, Jeffrey Will, Elizabeth Wuerffel, Alan B. Craig:
Extracting, Assimilating, and Sharing the Results of Image Analysis on the FSA/OWI Photography Collection. PEARC 2017: 42:1-42:6 - 2016
- [c9]Antonio Paolillo, Paul Rodríguez, Nikita Veshchikov, Joël Goossens, Ben Rodriguez:
Quantifying Energy Consumption for Practical Fork-Join Parallelism on an Embedded Real-Time Operating System. RTNS 2016: 329-338 - [c8]Nitin Sukhija, Mahidhar Tatineni, Nicole M. Brown
, Mark Van Moer
, Paul Rodríguez, Spencer Callicott
:
Topic Modeling and Visualization for Big Data in Social Sciences. UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld 2016: 1198-1205 - [c7]Marcus Slavenas, Paul Rodríguez, Alan B. Craig, Elizabeth Wuerffel, Jeffrey Will:
Image Analysis and Infrastructure Support for Data Mining the Farm Security Administration: Office of War Information Photography Collection. XSEDE 2016: 1:1-1:6 - 2013
- [c6]Thomas Chapeaux, Paul Rodríguez, Laurent George, Joël Goossens:
The Space of Feasible Execution Times for Asynchronous Periodic Task Systems Using Definitive Idle Times. SBESC 2013: 95-100 - 2011
- [c5]Paul Rodríguez:
Nonconvex total variation speckled image restoration via nonnegative quadratic programming algorithm. EUSIPCO 2011: 288-292 - [c4]Robert S. Sinkovits
, Pietro Cicotti, Shawn Strande, Mahidhar Tatineni, Paul Rodríguez, Nicole Wolter, Natasha Balac:
Data intensive analysis on the gordon high performance data and compute system. KDD 2011: 747-748 - 2010
- [c3]Paul Rodríguez:
A non-negative quadratic programming approach to minimize the generalized vector-valued total variation functional. EUSIPCO 2010: 314-318
2000 – 2009
- 2005
- [j5]William B. Levy, A. Sanyal, Xiangbao Wu, Paul Rodríguez, David W. Sullivan:
The formation of neural codes in the hippocampus: trace conditioning as a prototypical paradigm for studying the random recoding hypothesis. Biol. Cybern. 92(6): 409-426 (2005) - 2004
- [j4]Paul Rodríguez, William B. Levy:
Configural representations in transverse patterning with a hippocampal model. Neural Networks 17(2): 175-190 (2004) - 2003
- [j3]Paul Rodríguez:
Comparing Simple Recurrent Networks and n-Grams in a Large Corpus. Appl. Intell. 19(1-2): 39-50 (2003) - 2002
- [c2]Paul Rodríguez:
Radix-2 multi-dimensional transposition-free FFT algorithm for Modern Single Instruction Multiple Data (SIMD) architectures. EUSIPCO 2002: 1-4 - 2001
- [j2]Paul Rodríguez:
Simple Recurrent Networks Learn Context-Free and Context-Sensitive Languages by Counting. Neural Comput. 13(9): 2093-2118 (2001)
1990 – 1999
- 1999
- [j1]Paul Rodríguez:
A Recurrent Neural Network that Learns to Count. Connect. Sci. 11(1): 5-40 (1999) - 1997
- [c1]Paul Rodríguez, Janet Wiles:
Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting. NIPS 1997: 87-93
Coauthor Index
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