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1What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation
H. Selder, F. Fischer, P. Kristensson, and A. Fleig. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, page 1–10. ACM, (April 2025)
2 months ago by @scadsfct
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Biomechanical
Design
Function
Learning
Reinforcement
Reward
User_Simulation
Xack
BiomechanicalDesignFunctionLearningReinforcementRewardUser_SimulationXack
(0)
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1Unsupervised feature selection based on variance–covariance subspace distance
S. Karami, F. Saberi-Movahed, P. Tiwari, P. Marttinen, and S. Vahdati. Neural Networks, (2023)
7 months ago by @scadsfct
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Feature
Regularization
Subspace
Xack
distance
learning
selection
FeatureRegularizationSubspaceXackdistancelearningselection
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1MLcps: machine learning cumulative performance score for classification problems
A. Akshay, M. Abedi, N. Shekarchizadeh, F. Burkhard, M. Katoch, A. Bigger-Allen, R. Adam, K. Monastyrskaya, and A. Gheinani. GigaScience, (December 2023)
7 months ago by @scadsfct
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MLcps
Xack
Yaff
cumulative
learning
machine
performance
MLcpsXackYaffcumulativelearningmachineperformance
(0)
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1WARC-DL: Scalable Web Archive Processing for Deep Learning
N. Deckers, and M. Potthast. (2022)
7 months ago by @scadsfct
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Archive
Deep
Learning
Processing
Scalable
WARC-DL
Web
Xack
ArchiveDeepLearningProcessingScalableWARC-DLWebXack
(0)
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1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving
D. Li, and O. Okhrin. Commun Eng, 3 (1): 147 (October 2024)
7 months ago by @scadsfct
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Sim2Real
Xack
autonomous
deep
driving
framework
learning
platform-agnostic
reinforcement
Sim2RealXackautonomousdeepdrivingframeworklearningplatform-agnosticreinforcement
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1Named Entity Recognition for Specific Domains - Take Advantage of Transfer Learning
S. Torge, W. Hahn, L. Manjunath, and R. Jäkel. International Journal of Information Science and Technology, (2022)
7 months ago by @scadsfct
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Advantage
Domains
Entity
Learning
Recognition
Specific
Transfer
Xack
AdvantageDomainsEntityLearningRecognitionSpecificTransferXack
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1Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse
M. Bogdan. XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja), Servizo de Publicacións da UDC, (September 2022)
7 months ago by @scadsfct
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Learning
Xack
algorithms
learning
networks
neural
neurological
plausible
spiking
LearningXackalgorithmslearningnetworksneuralneurologicalplausiblespiking
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2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, and E. Rahm. arXiv preprint arXiv:2409.01329, (September 2024)
8 months ago by @scadsfct
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(cs.CR),
(cs.CV),
(cs.LG),
Computer
Cryptography
FOS:
Learning
Machine
Pattern
Recognition
Security
Vision
and
area_bigdata
area_responsibleai
ep
information
sciences
Xack
Yaff
(cs.CR),(cs.CV),(cs.LG),ComputerCryptographyFOS:LearningMachinePatternRecognitionSecurityVisionandarea_bigdataarea_responsibleaiepinformationsciencesXackYaff
(0)
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1Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease
V. Friedrich, P. Pennitz, E. Wyler, J. Adler, D. Postmus, K. Müller, L. Teixeira Alves, J. Prigann, F. Pott, D. Vladimirova and 10 other author(s). eBioMedicine, (2024)
8 months ago by @scadsfct
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COVID-19,
Cross-species
Deep
Disease
Hamster
RNA-seq,
Single-cell
analysis,
learning
matching,
model,
state
topic_mathfoundation
Xack
Yaff
COVID-19,Cross-speciesDeepDiseaseHamsterRNA-seq,Single-cellanalysis,learningmatching,model,statetopic_mathfoundationXackYaff
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1Stability selection enables robust learning of partial differential equations from limited noisy data
S. Maddu, B. Cheeseman, I. Sbalzarini, and C. Müller. (2019)
9 months ago by @scadsfct
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(cs.LG),
(math.NA),
(physics.data-an),
Analysis
Analysis,
Computer
Data
FOS:
Learning
Machine
Mathematics,
Numerical
Physical
Probability
Statistics
and
information
sciences
sciences,
Xack
(cs.LG),(math.NA),(physics.data-an),AnalysisAnalysis,ComputerDataFOS:LearningMachineMathematics,NumericalPhysicalProbabilityStatisticsandinformationsciencessciences,Xack
(0)
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1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis
A. Akshay, M. Katoch, N. Shekarchizadeh, M. Abedi, A. Sharma, F. Burkhard, R. Adam, K. Monastyrskaya, and A. Gheinani. Gigascience, (January 2024)
11 months ago by @scadsfct
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AutoML
analysis
classification
data
learning
machine
problems
topic_federatedlearn
visualization
xack
yaff
AutoMLanalysisclassificationdatalearningmachineproblemstopic_federatedlearnvisualizationxackyaff
(0)
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1MLcps: machine learning cumulative performance score for classification problems
A. Akshay, M. Abedi, N. Shekarchizadeh, F. Burkhard, M. Katoch, A. Bigger-Allen, R. Adam, K. Monastyrskaya, and A. Gheinani. Gigascience, (December 2022)
11 months ago by @scadsfct
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Python
classification
evaluation
learning
machine
model
package
problems
score
topic_federatedlearn
unified
xack
yaff
Pythonclassificationevaluationlearningmachinemodelpackageproblemsscoretopic_federatedlearnunifiedxackyaff
(0)
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1SpheroScan: a user-friendly deep learning tool for spheroid image analysis
A. Akshay, M. Katoch, M. Abedi, N. Shekarchizadeh, M. Besic, F. Burkhard, A. Bigger-Allen, R. Adam, K. Monastyrskaya, and A. Gheinani. Gigascience, (December 2022)
11 months ago by @scadsfct
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3D
Image
Mask
R-CNN
analysis
deep
high-throughput
image
learning
screening
segmentation
spheroids
topic_federatedlearn
xack
yaff
3DImageMaskR-CNNanalysisdeephigh-throughputimagelearningscreeningsegmentationspheroidstopic_federatedlearnxackyaff
(0)
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1Socio-Technical Anti-Patterns in Building ML-Enabled Software: Insights from Leaders on the Forefront
A. Mailach, and N. Siegmund. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), page 690--702. IEEE, (May 2023)
11 months ago by @scadsfct
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Biological
Economics
Machine
Manuals
Pipelines
Production
Software
learning
modeling
system
systems
topic_software
xack
yaff
BiologicalEconomicsMachineManualsPipelinesProductionSoftwarelearningmodelingsystemsystemstopic_softwarexackyaff
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publications (hide)15
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1What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation

1Unsupervised feature selection based on variance–covariance subspace distance

1MLcps: machine learning cumulative performance score for classification problems

1WARC-DL: Scalable Web Archive Processing for Deep Learning

1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving

1Named Entity Recognition for Specific Domains - Take Advantage of Transfer Learning

1Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse

2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning

1Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease

1Stability selection enables robust learning of partial differential equations from limited noisy data

1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis

1MLcps: machine learning cumulative performance score for classification problems

1SpheroScan: a user-friendly deep learning tool for spheroid image analysis

1Socio-Technical Anti-Patterns in Building ML-Enabled Software: Insights from Leaders on the Forefront

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