Adam Kowalczyk

Orcid: 0000-0001-9068-3383

According to our database1, Adam Kowalczyk authored at least 45 papers between 1991 and 2019.

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Bibliography

2019
Exploring effective approaches for haplotype block phasing.
BMC Bioinform., 2019

2014
GWISFI: A universal GPU interface for exhaustive search of pairwise interactions in case-control GWAS in minutes.
Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014

2012
SparSNP: Fast and memory-efficient analysis of all SNPs for phenotype prediction.
BMC Bioinform., 2012

FSR: feature set reduction for scalable and accurate multi-class cancer subtype classification based on copy number.
Bioinform., 2012

2011
The Poisson Margin Test for Normalization-Free Significance Analysis of NGS Data.
J. Comput. Biol., 2011

Meta-analysis of gene expression microarrays with missing replicates.
BMC Bioinform., 2011

Replication of epistatic DNA loci in two case-control GWAS studies using OPE algorithm.
BMC Bioinform., 2011

Genome annotation test with validation on transcription start site and ChIP-Seq for Pol-II binding data.
Bioinform., 2011

2010
Using Gene Ontology annotations in exploratory microarray clustering to understand cancer etiology.
Pattern Recognit. Lett., 2010

A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer.
BMC Bioinform., 2010

is-rSNP: a novel technique for in silico regulatory SNP detection.
BMC Bioinform., 2010

Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context.
BMC Bioinform., 2010

Exploiting sequence similarity to validate the sensitivity of SNP arrays in detecting fine-scaled copy number variations.
Bioinform., 2010

is-rSNP: a novel technique for <i>in silico</i> regulatory SNP detection.
Bioinform., 2010

The Poisson Margin Test for Normalisation Free Significance Analysis of NGS Data.
Proceedings of the Research in Computational Molecular Biology, 2010

2008
Gene Ontology Assisted Exploratory Microarray Clustering and Its Application to Cancer.
Proceedings of the Pattern Recognition in Bioinformatics, 2008

2007
Classification of Anti-learnable Biological and Synthetic Data.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Continuity of Performance Metrics for Thin Feature Maps.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

2006
An Efficient Alternative to SVM Based Recursive Feature Elimination with Applications in Natural Language Processing and Bioinformatics.
Proceedings of the AI 2006: Advances in Artificial Intelligence, 2006

2005
An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

2004
Extreme re-balancing for SVMs: a case study.
SIGKDD Explor., 2004

Exploring Potential of Leave-One-Out Estimator for Calibration of SVM in Text Mining.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004

2003
Exploring Fringe Settings of SVMs for Classification.
Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

2002
One Class SVM for Yeast Regulation Prediction.
SIGKDD Explor., 2002

Combining clustering and co-training to enhance text classification using unlabelled data.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

Using Unlabelled Data for Text Classification through Addition of Cluster Parameters.
Proceedings of the Machine Learning, 2002

Multi-Instance Kernels.
Proceedings of the Machine Learning, 2002

2001
Kernel Machines and Boolean Functions.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Second Order Features for Maximising Text Classification Performance.
Proceedings of the Machine Learning: EMCL 2001, 2001

Learner's Self-Assessment: A Case Study of SVM for Information Retrieval.
Proceedings of the AI 2001: Advances in Artificial Intelligence, 2001

2000
Sparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1997
Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units.
Neural Networks, 1997

Experiments with Simple Neural Networks for Real-Time Control.
IEEE J. Sel. Areas Commun., 1997

Dense Shattering and Teaching Dimensions for Differentiable Families (Extended Abstract).
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

1996
MLP Can Provably Generalize Much Better than VC-bounds Indicate.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995
Examples of learning curves from a modified VC-formalism.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Experiments with Neural Networks for Real Time Implementation of Control.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Learning curves from a modified VC-formalism: a case study.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Neural networks in real time control of telecommunication networks.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

1994
Developing higher-order networks with empirically selected units.
IEEE Trans. Neural Networks, 1994

Generalisation in Feedforward Networks.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993
Constructive higher-order network that is polynomial time.
Neural Networks, 1993

Counting Function Theorem for Multi-Layer Networks.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992
Some Estimates on the Number of Connections and Hidden Units for Feed-Forward Networks.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
Discovering Production Rules with Higher Order Neural Networks.
Proceedings of the Eighth International Workshop (ML91), 1991


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