Stefan C. Kremer

发表

Regularization of sequence data for machine learning

Bryan Bai, Stefan C. Kremer, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

Amino acid encoding schemes for machine learning methods

Stefan C. Kremer, Masood Zamani, S. C. Kremer, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

Protein secondary structure prediction using an evolutionary computation method and clustering

Stefan C. Kremer, Masood Zamani, S. C. Kremer, 2015, 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

A Wi-Fi Simulation Model Which Supports Channel Scanning across Multiple Non-overlapping Channels in NS3

Joel J. P. C. Rodrigues, Jason B. Ernst, Stefan C. Kremer, 2014, 2014 IEEE 28th International Conference on Advanced Information Networking and Applications.

Neural Grammar Networks

Stefan C. Kremer, Eddie Y. T. Ma, 2009, Innovations in Neural Information Paradigms and Applications.

Protein coding region prediction based on the adaptive representation method

Stefan C. Kremer, Sajid Marhon, 2011, 2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE).

Neural and Statistical Classification to Families of Bio-sequences

Stefan C. Kremer, Mosaab Daoud, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

An Algorithm for Inducing Stochastic Finite Memory Machines

Stefan C. Kremer, Michael Curchin, 2006 .

A multi-stage protein secondary structure prediction system using machine learning and information theory

Stefan C. Kremer, Masood Zamani, S. C. Kremer, 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Simple Stable Encodings of FiniteState Machines in Dynamic Recurrent Networks

John F. Kolen, Stefan C. Kremer, 2001 .

Past, present and future approaches using computer vision for animal re‐identification from camera trap data pdf

Graham W. Taylor, Stefan C. Kremer, Stefan Schneider, 2018, Methods in Ecology and Evolution.

A survey of QoS/QoE mechanisms in heterogeneous wireless networks

Joel J. P. C. Rodrigues, Jason B. Ernst, Stefan C. Kremer, 2014, Phys. Commun..

Representation beyond Finite States: Alternatives to Pushdown Automata

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Sequence learning: analysis and solutions for sparse data in high dimensional spaces

Bryan Bai, Stefan C. Kremer, S. C. Kremer, 2012, 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

Dynamical Recurrent Networks for Sequential Data Processing

John F. Kolen, Stefan C. Kremer, 1998, Hybrid Neural Systems.

General Fuzzy Automata, New Efficient Acceptors for Fuzzy Languages

Stefan C. Kremer, Mansoor Doostfatemeh, 2006, 2006 IEEE International Conference on Fuzzy Systems.

Dynamical Recurrent Networks

John F. Kolen, Stefan C. Kremer, 2001 .

The Implementation of the Alopex-B Training Algorithm in Parallel

Stefan C. Kremer, Michael De Ridder, 2007 .

On the computational power of Elman-style recurrent networks

Stefan C. Kremer, S. C. Kremer, 1995, IEEE Trans. Neural Networks.

Neural Networks in Bioinformatics

Stefan C. Kremer, Masood Zamani, S. C. Kremer, 2013, Handbook on Neural Information Processing.

Theoretical justification of computing the 3-base periodicity using nucleotide distribution variance

Stefan C. Kremer, Sajid Marhon, 2010, Biosyst..

Sentence Processing and Linguistic Structure

John F. Kolen, Stefan C. Kremer, 2001 .

A Taxonomy for Spatiotemporal Connectionist Networks Revisited: The Unsupervised Case

Aluizio F. R. Araújo, Guilherme De A. Barreto, Stefan C. Kremer, 2003, Neural Computation.

Understanding and Explaining DRN Behavior

John F. Kolen, Stefan C. Kremer, 2001 .

Intrusion Detection in Contemporary Environments

Stefan C. Kremer, Tarfa Hamed, Rozita Dara, 2017 .

A utility based access point selection method for IEEE 802.11 wireless networks with enhanced quality of experience

Joel J. P. C. Rodrigues, Jason B. Ernst, Stefan C. Kremer, 2014, 2014 IEEE International Conference on Communications (ICC).

Comments on "Constructive learning of recurrent neural networks: limitations of recurrent cascade correlation and a simple solution"

Stefan C. Kremer, S. C. Kremer, 1996, IEEE Trans. Neural Networks.

Evaluating Benchmark Problems by Random Guessing

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

09081 Summary - Similarity-based learning on structures

Thomas Villmann, Michael Biehl, Barbara Hammer, 2009, Similarity-based learning on structures.

A Survey and Comparison of Performance Evaluation in Intrusion Detection Systems

Jason B. Ernst, Stefan C. Kremer, Tarfa Hamed, 2018, Computer and Network Security Essentials.

Insertion of Prior Knowledge

John F. Kolen, Stefan C. Kremer, 2001 .

Introduction By Guest Editors: Non-Gradient Learning Techniques

André Carlos Ponce de Leon Ferreira de Carvalho, Stefan C. Kremer, 2001, Int. J. Neural Syst..

Neural Network Architectures for the Modeling of Dynamic Systems

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

A Survey and Taxonomy of Classifiers of Intrusion Detection Systems

Jason B. Ernst, Stefan C. Kremer, Tarfa Hamed, 2018, Computer and Network Security Essentials.

Delay Networks: Buffers to the Rescue

John F. Kolen, Stefan C. Kremer, 2001 .

Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results

Stefan C. Kremer, S. C. Kremer, Orlando Cicchello, 2003, J. Mach. Learn. Res..

New directions in fuzzy automata

Stefan C. Kremer, Mansoor Doostfatemeh, S. C. Kremer, 2005, Int. J. Approx. Reason..

From Sequences to Data Structures: Theory and Applications

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

A brief comparison of DSP and HMM methods for gene finding

Stefan C. Kremer, Sajid Marhon, 2012, BCB '12.

A testbed for automatic modulation recognition using artificial neural networks

Stefan C. Kremer, J. Shiels, 1997, CCECE '97. Canadian Conference on Electrical and Computer Engineering. Engineering Innovation: Voyage of Discovery. Conference Proceedings.

Clustering unlabeled data with SOMs improves classification of labeled real-world data

Stefan C. Kremer, Deborah Stacey, Rozita Dara, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012, Philadelphia, USA, October 4-7, 2012

Pablo Moscato, Giovanni De Micheli, Wenqi You, 2012, BIBM Workshops.

A Survey and Taxonomy on Data and Pre-processing Techniques of Intrusion Detection Systems

Jason B. Ernst, Stefan C. Kremer, Tarfa Hamed, 2018, Computer and Network Security Essentials.

Spatiotemporal Connectionist Networks: A Taxonomy and Review

Stefan C. Kremer, S. C. Kremer, 2001, Neural Computation.

Finite State Automata that Recurrent Cascade-Correlation Cannot Represent

Stefan C. Kremer, S. C. Kremer, 1995, NIPS.

Classifying and scoring of molecules with the NGN: new datasets, significance tests, and generalization

Stefan C. Kremer, Eddie Y. T. Ma, Christopher J. F. Cameron, 2010, BMC Bioinformatics.

Protein secondary structure prediction using support vector machines and a codon encoding scheme

Stefan C. Kremer, Masood Zamani, 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops.

Hidden Markov models and neural networks

Pierre Baldi, Stefan C. Kremer, 2005 .

A dynamic representation-based, de novo method for protein-coding region prediction and biological information detection

Stefan C. Kremer, Sajid Marhon, S. C. Kremer, 2015, Digit. Signal Process..

A theory of grammatical induction in the connectionist paradigm

Renée Elio, Stefan C. Kremer, Michael R. W. Dawson, 1996 .

Deep Learning Object Detection Methods for Ecological Camera Trap Data

Graham W. Taylor, Stefan C. Kremer, Stefan Schneider, 2018, 2018 15th Conference on Computer and Robot Vision (CRV).

Three critical factors affecting automated image species recognition performance for camera traps

Saul Greenberg, Graham W. Taylor, Stefan C. Kremer, 2020, Ecology and evolution.

Similarity-based learning on structures

Thomas Villmann, Michael Biehl, Barbara Hammer, 2009 .

Spatio-Temporal Connectionist Networks

Stefan C. Kremer, S. C. Kremer, 2007, Handbook of Dynamic System Modeling.

Recurrent Neural Networks

Stefan C. Kremer, Sajid Marhon, S. C. Kremer, 2013, Handbook on Neural Information Processing.

Field Guide to Dynamical Recurrent Networks

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Beyond EDSM

Stefan C. Kremer, Orlando Cicchello, 2002, ICGI.

Network intrusion detection system based on recursive feature addition and bigram technique

Stefan C. Kremer, Tarfa Hamed, Rozita Dara, 2018, Comput. Secur..

Dynamical Recurrent Networks in Control

John F. Kolen, Stefan C. Kremer, 2001 .

Constrained Second-Order Recurrent Networks for Finite-State Automata Induction

Mikel L. Forcada, Stefan C. Kremer, Ramón P. Ñeco, 1998 .

Prediction of Protein Coding Regions Using a Wide-Range Wavelet Window Method

Stefan C. Kremer, Sajid Marhon, S. C. Kremer, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

09081 Abstracts Collection - Similarity-based learning on structures

Thomas Villmann, Michael Biehl, Barbara Hammer, 2009, Similarity-based learning on structures.

Neural Grammar Networks in QSAR Chemistry

Stefan C. Kremer, Eddie Y. T. Ma, 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine.

Identification of a specific limitation on local-feedback recurrent networks acting as Mealy-Moore machines

Stefan C. Kremer, S. C. Kremer, 1999, IEEE Trans. Neural Networks.

An Accurate, Fast Embedded Feature Selection for SVMs

Stefan C. Kremer, Tarfa Hamed, Rozita Dara, 2014, 2014 13th International Conference on Machine Learning and Applications.

Stefan C. Kremer, Mosaab Daoud, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Graham W. Taylor, Stefan C. Kremer, Stefan Schneider, 2019, 2020 IEEE Winter Applications of Computer Vision Workshops (WACVW).

Fuzzy Grammar Induction from Large Corpora

Stefan C. Kremer, Patrick Carter, 2006, 2006 IEEE International Conference on Fuzzy Systems.

A new Canadian interdisciplinary Ph.D. in computational sciences

Gary William Grewal, Stefan C. Kremer, Fangju Wang, 2015, J. Comput. Sci..

Biological Sequence Prediction using General Fuzzy Automata

Stefan C. Kremer, Mansoor Doostfatemeh, 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Limiting the Computational Power of Recurrent Neural Networks: VapnikChervonenkis Dimension and Noise

John F. Kolen, Stefan C. Kremer, 2001 .

A New, Dynamic-Representation-Based Gene Finding Method with an Analysis of False Positive Peaks

Stefan C. Kremer, Sajid Marhon, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

The Guelph Darwin Project: the evolution of neural networks by genetic algorithms

Stefan C. Kremer, Deborah Stacey, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Protein secondary structure prediction through a novel framework of secondary structure transition sites and new encoding schemes

Stefan C. Kremer, Masood Zamani, S. C. Kremer, 2016, 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

Dynamical Recurrent Networks: Looking Back and Looking Forward

John F. Kolen, Stefan C. Kremer, 2001 .

Universal Computation and SuperTuring Capabilities

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Networks with Adaptive State Transitions

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Heterogeneous wireless network RAT selection with multiple operators and service contracts

Joel J. P. C. Rodrigues, Jason B. Ernst, Stefan C. Kremer, 2015, 2015 IEEE International Conference on Communications (ICC).

Performance evaluation of heterogeneous wireless networks considering competing objectives and viewpoints

Joel J. P. C. Rodrigues, Stefan C. Kremer, Jason Ernst, 2015, SAC.

Dynamical Systems and Iterated Function Systems

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Gradient Calculations for Dynamic Recurrent Neural Networks

John F. Kolen, Stefan C. Kremer, S. C. Kremer, 2001 .

Evaluation of Selected DNA Spectral Analysis-Based Gene Prediction Techniques

Stefan C. Kremer, Sajid A. Marhon, 2017 .