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Pfannschmidt, Lukas
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1

Relevance Learning for Redundant Features:

Pfannschmidt, Lukas , 2021
Link: https://nbn-resolving.de..
 
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2

Feature relevance determination for ordinal regression in t..:

Pfannschmidt, Lukas ; Jakob, Jonathan ; Hinder, Fabian...
Neurocomputing.  416 (2020)  - p. 266-279 , 2020
Link: https://doi.org/10.1016/..
 
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3

Interpretation of linear classifiers by means of feature re..:

Göpfert, Christina ; Pfannschmidt, Lukas ; Göpfert, Jan Philip.
Neurocomputing.  298 (2018)  - p. 69-79 , 2018
Link: https://doi.org/10.1016/..
 
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4

Relevance learning for redundant features:

Pfannschmidt, Lukas
vignette : https://noah.nrw/titlepage/urn/urn:nbn:de:0070-pub-29598614/128.  , 2021
Link: https://nbn-resolving.or..
 
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5

Sequential Feature Classification in the Context of Redunda..:

Pfannschmidt, Lukas ; Hammer, Barbara
vignette : https://noah.nrw/titlepage/urn/urn:nbn:de:0070-pub-29422719/128.  , 2020
Link: https://nbn-resolving.or..
 
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6

Sequential Feature Classification in the Context of Redunda..:

Pfannschmidt, Lukas ; Hammer, Barbara
http://arxiv.org/abs/2004.00658.  , 2020
Link: http://arxiv.org/abs/200..
 
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7

Feature Relevance Determination for Ordinal Regression in t..:

Pfannschmidt, Lukas ; Jakob, Jonathan ; Hinder, Fabian...
https://research.rug.nl/en/publications/2c4aed46-2645-417e-a07f-97bfc304d682.  , 2020
Link: https://hdl.handle.net/1..
 
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8

Feature Relevance Determination for Ordinal Regression in t..:

Pfannschmidt, Lukas ; Jakob, Jonathan ; Hinder, Fabian...
http://arxiv.org/abs/1912.04832.  , 2019
Link: http://arxiv.org/abs/191..
 
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9

FRI - Feature Relevance Intervals for Interpretable and Int..:

Pfannschmidt, Lukas ; Göpfert, Christina ; Neumann, Ursula..
vignette : https://noah.nrw/titlepage/urn/urn:nbn:de:0070-pub-29354564/128.  , 2019
Link: https://nbn-resolving.or..
 
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10

FRI -- Feature Relevance Intervals for Interpretable and In..:

Pfannschmidt, Lukas ; Göpfert, Christina ; Neumann, Ursula..
http://arxiv.org/abs/1903.00719.  , 2019
Link: http://arxiv.org/abs/190..
 
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11

Feature Relevance Bounds for Ordinal Regression:

Pfannschmidt, Lukas ; Jakob, Jonathan ; Biehl, Michael..
http://arxiv.org/abs/1902.07662.  , 2019
Link: http://arxiv.org/abs/190..
 
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12

Neurocomputing / Interpretation of Linear Classifiers by Me..:

Göpfert, Christina ; Pfannschmidt, Lukas ; Göpfert, Jan Philip.
vignette : https://noah.nrw/titlepage/urn/urn:nbn:de:0070-pub-29152737/128.  , 2018
Link: https://nbn-resolving.or..
 
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13

Feature Relevance Bounds for Linear Classification:

Göpfert, Christina ; Pfannschmidt, Lukas ; Hammer, Barbara
vignette : https://noah.nrw/titlepage/urn/urn:nbn:de:0070-pub-29082012/128.  , 2017
Link: https://nbn-resolving.or..
 
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14

lpfann/fri: Python 3.9 support and new dependencies:

Lukas Pfannschmidt ; jonjakob ; Vighnesh Birodkar...
https://github.com/lpfann/fri/tree/8.1.0.  , 2021
Link: https://zenodo.org/recor..
 
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15

lpfann/fri: Small dependency updates:

Lukas Pfannschmidt ; jonjakob ; Vighnesh Birodkar...
https://github.com/lpfann/fri/tree/8.0.1.  , 2020
Link: https://zenodo.org/recor..
 
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