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2Demystifying Reward Design in Reinforcement Learning for Upper Extremity Interaction: Practical Guidelines for Biomechanical Simulations in HCI
H. Selder, F. Fischer, P. Kristensson, and A. Fleig. Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, Association for Computing Machinery, (2025)
2 months ago by @scadsfct
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Biomechanical
Design
Function
Human-Computer
Interaction
Learning
Reinforcement
Reward
Simulations
User
myown
xack
yaff
BiomechanicalDesignFunctionHuman-ComputerInteractionLearningReinforcementRewardSimulationsUsermyownxackyaff
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1Graph Metrics-driven Record Cluster Repair meets LLM-based active learning
V. Christen, D. Obraczka, M. Hofer, M. Franke, and E. Rahm. Journal of Data and Information Quality, 17 (2): 1–25 (June 2025)
3 months ago by @scadsfct
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LLM_based
active
learning
record_cluster
xack
LLM_basedactivelearningrecord_clusterxack
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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)
7 months ago by @scadsfct
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Biomechanical
Design
Function
Reinforcement
Reward
User_Simulation
xack
learning
BiomechanicalDesignFunctionReinforcementRewardUser_Simulationxacklearning
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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)
12 months ago by @scadsfct
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Feature
Regularization
Subspace
distance
learning
selection
xack
FeatureRegularizationSubspacedistancelearningselectionxack
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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)
12 months ago by @scadsfct
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MLcps
cumulative
learning
machine
performance
yaff
xack
MLcpscumulativelearningmachineperformanceyaffxack
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1WARC-DL: Scalable Web Archive Processing for Deep Learning
N. Deckers, and M. Potthast. (2022)
12 months ago by @scadsfct
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Archive
Processing
Scalable
WARC-DL
xack
learning
deep
web
ArchiveProcessingScalableWARC-DLxacklearningdeepweb
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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)
12 months ago by @scadsfct
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Sim2Real
autonomous
deep
driving
framework
learning
platform-agnostic
reinforcement
xack
Sim2Realautonomousdeepdrivingframeworklearningplatform-agnosticreinforcementxack
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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)
12 months ago by @scadsfct
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Advantage
Domains
Entity
Recognition
Specific
Transfer
learning
xack
AdvantageDomainsEntityRecognitionSpecificTransferlearningxack
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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)
12 months ago by @scadsfct
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algorithms
learning
networks
neural
neurological
plausible
spiking
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algorithmslearningnetworksneuralneurologicalplausiblespikingxack
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1Few-Shot Learning for Argument Aspects of the Nuclear Energy Debate
L. Jurkschat, G. Wiedemann, M. Heinrich, M. Ruckdeschel, and S. Torge. 2022 Language Resources and Evaluation Conference, LREC 2022, page 663--672. European Language Resources Association (ELRA), (2022)Publisher Copyright: © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.; 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 ; Conference date: 20-06-2022 Through 25-06-2022.
a year ago by @scadsfct
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FIS_scads
argument
aspect-based
aspects,
classification
discourse,
energy
few-shot
frames,
mining,
nuclear
text
xack
learning
FIS_scadsargumentaspect-basedaspects,classificationdiscourse,energyfew-shotframes,mining,nucleartextxacklearning
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2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, and E. Rahm. (September 2024)
a year ago by @scadsfct
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(cs.CR)
(cs.CV)
(cs.LG)
Computer
Cryptography
FOS
Pattern
Recognition
Security
Vision
area_bigdata
area_responsibleai
ep
information
learning
machine
sciences
xack
yaff
(cs.CR)(cs.CV)(cs.LG)ComputerCryptographyFOSPatternRecognitionSecurityVisionarea_bigdataarea_responsibleaiepinformationlearningmachinesciencesxackyaff
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1Steuerung von Compliant-Mechanismen durch Reinforcement Learning
L. Muschalski, J. Wollmann, A. Hornig, and N. Modler. GETRIEBETAGUNG 2022, (2022)
a year ago by @scadsfct
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Compliant-Mechanismen
Reinforcement
Steuerung
learning
topic_engineering
xack
Compliant-MechanismenReinforcementSteuerunglearningtopic_engineeringxack
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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)
a year ago by @scadsfct
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COVID-19,
Cross-species
Disease
Hamster
RNA-seq,
Single-cell
analysis,
learning
matching,
model,
state
topic_mathfoundation
yaff
xack
deep
COVID-19,Cross-speciesDiseaseHamsterRNA-seq,Single-cellanalysis,learningmatching,model,statetopic_mathfoundationyaffxackdeep
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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)
a year ago by @scadsfct
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(cs.LG)
(math.NA)
(physics.data-an)
Analysis
Computer
FOS
Mathematics
Numerical
Physical
Probability
Statistics
data
information
learning
machine
sciences
xack
(cs.LG)(math.NA)(physics.data-an)AnalysisComputerFOSMathematicsNumericalPhysicalProbabilityStatisticsdatainformationlearningmachinesciencesxack
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1Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study
M. Huemer, A. Bauer, A. Petrera, M. Scholz, S. Hauck, M. Drey, A. Peters, and B. Thorand. J. Cachexia Sarcopenia Muscle, 12 (4): 1011--1023 (August 2021)
a year ago by @scadsfct
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Appendicular
Body
Fat
Muscle
Proteomics
fat
index
learning
machine
mass
muscle
skeletal
xack
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1Structural damage identification of composite rotors based on fully connected neural networks and convolutional neural networks
V. Scholz, P. Winkler, A. Hornig, M. Gude, and A. Filippatos. Sensors (Basel), 21 (6): 2005 (March 2021)
a year ago by @scadsfct
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(SHM)
composite
composites;
connected
convolutional
dense
fully
health
machine
monitoring
neural
rotors;
structural
xack
learning
networks
(SHM)compositecomposites;connectedconvolutionaldensefullyhealthmachinemonitoringneuralrotors;structuralxacklearningnetworks
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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)
a year ago by @scadsfct
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Biological
Economics
Manuals
Pipelines
Production
Software
learning
machine
modeling
system
systems
topic_software
xack
yaff
BiologicalEconomicsManualsPipelinesProductionSoftwarelearningmachinemodelingsystemsystemstopic_softwarexackyaff
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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)
a year ago by @scadsfct
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AutoML
analysis
classification
data
learning
machine
problems
topic_federatedlearn
visualization
xack
yaff
AutoMLanalysisclassificationdatalearningmachineproblemstopic_federatedlearnvisualizationxackyaff
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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)
a year 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
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publications (hide)19
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2Demystifying Reward Design in Reinforcement Learning for Upper Extremity Interaction: Practical Guidelines for Biomechanical Simulations in HCI

1Graph Metrics-driven Record Cluster Repair meets LLM-based active learning

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

1Few-Shot Learning for Argument Aspects of the Nuclear Energy Debate

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

1Steuerung von Compliant-Mechanismen durch Reinforcement 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

1Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study

1Structural damage identification of composite rotors based on fully connected neural networks and convolutional neural networks

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

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

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

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