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1The Predictive Privacy Project - Rainer Mühlhoff
Data Protection in the Context of Big Data and AI
2 years ago by @hotho
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deep
privacy
data
machine
Datenschutz
predictive
learning
big
ml
deepprivacydatamachineDatenschutzpredictivelearningbigml
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1Technical threads
https://twitter.com/docmilanfar/status/1528179986393247744?t=UvZ0PICIMAMFEGG2KlYDhQ&s=19
2 years ago by @becker
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twitter
roc
technical
thread
tweet
ml
statistics
auc
twitterroctechnicalthreadtweetmlstatisticsauc
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1Predicting algorithms - machine learning for index structures
https://www.quantamagazine.org/machine-learning-reimagines-the-building-blocks-of-computing-20220315/
3 years ago by @becker
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subgroup
machine
discovery
learning
index
ml
structure
subgroupmachinediscoverylearningindexmlstructure
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1Deterministic python
https://twitter.com/kastnerkyle/status/1473361479143460872?t=-q6YbOcOZ2AXJ_EgW0vkJg&s=19
3 years ago by @becker
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cuda
random
python
seed
machine
learning
numpy
deterministic
torch
ml
cudarandompythonseedmachinelearningnumpydeterministictorchml
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2The Neural Network Zoo - The Asimov Institute
https://www.asimovinstitute.org/neural-network-zoo/
3 years ago by @jaeschke
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dnn
deeplearning
neural
machine
network
ml
dnndeeplearningneuralmachinenetworkml
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1Notebooks Gallery — mlinsights
http://www.xavierdupre.fr/app/mlinsights/helpsphinx/all_notebooks.html
3 years ago by @becker
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visualize
library
learn
pipeline
extension
insights
mlinsights
support
scikit
ml
sklearn
visualizelibrarylearnpipelineextensioninsightsmlinsightssupportscikitmlsklearn
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1Home - Leaderboards by Allen AI
The AI2 Leaderboard platform hosts public leaderboards for a variety of AI challenge tasks across multiple research domains.
3 years ago by @jaeschke
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dataset
leaderboard
deeplearning
evaluation
machine
ai
learning
ml
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datasetleaderboarddeeplearningevaluationmachineailearningmlbenchmark
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4Browse the State-of-the-Art in Machine Learning | Papers With Code
4726 leaderboards • 2203 tasks • 3914 datasets • 46332 papers with code.
3 years ago by @jaeschke
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nlp
leaderboard
deeplearning
evaluation
machine
ai
learning
datasets
ml
benchmark
nlpleaderboarddeeplearningevaluationmachineailearningdatasetsmlbenchmark
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1Must-read Papers on pre-trained language models
https://pythonawesome.com/must-read-papers-on-pre-trained-language-models/
4 years ago by @hotho
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deep
language
pre-trained
elmo
learning
bert
model
ml
deeplanguagepre-trainedelmolearningbertmodelml
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2Transfer learning from pre-trained models | by Pedro Marcelino | Towards Data Science
https://towardsdatascience.com/transfer-learning-from-pre-trained-models-f2393f124751
4 years ago by @becker
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transfer
dataset
neural
size
use
machine
learning
to
network
when
ml
nn
transferdatasetneuralsizeusemachinelearningtonetworkwhenmlnn
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1MULTI-VIEW LEARNING | Papers With Code
https://paperswithcode.com/task/multi-view-learning/
4 years ago by @becker
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overview
nalab
code
learn
multiview
python
py
learning
multi
list
view
omics
butterfly
multiomics
ml
overviewnalabcodelearnmultiviewpythonpylearningmultilistviewomicsbutterflymultiomicsml
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1Overview of mvlearn — mvlearn alpha documentation
https://mvlearn.neurodata.io/index.html
4 years ago by @becker
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nalab
learn
multiview
view
python
omics
butterfly
py
multiomics
learning
multi
ml
nalablearnmultiviewviewpythonomicsbutterflypymultiomicslearningmultiml
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1CS 11-747: Neural Networks for NLP
http://phontron.com/class/nn4nlp2019/
4 years ago by @hotho
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nlp
deep
language
learning
ml
nlpdeeplanguagelearningml
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4Interpretable Machine Learning
https://christophm.github.io/interpretable-ml-book/
5 years ago by @becker
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artifical
machine
ai
learning
interpretable
explainable
xai
ml
intelligence
artificalmachineailearninginterpretableexplainablexaimlintelligence
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1machine learning - Getting a low ROC AUC score but a high accuracy - Stack Overflow
https://stackoverflow.com/questions/47104129/getting-a-low-roc-auc-score-but-a-high-accuracy/47111246#47111246
5 years ago by @becker
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acc
comparison
roc
precision
data
accuracy
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metric
auc
science
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recall
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machine
metrics
ml
acccomparisonrocprecisiondataaccuracylearningmetricaucscienceminingrecallevaluationmachinemetricsml
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1KI made in Germany
https://www.plattform-lernende-systeme.de/files/Downloads/Publikationen/AG1_Whitepaper_280619.pdf
5 years ago by @hotho
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paper
deep
white
machine
ai
learning
ki
ml
Germany
paperdeepwhitemachineailearningkimlGermany
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1Kara Primer
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team
5 years ago by @hotho
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analytics
primer
kara
privacy
data
Datenschutz
Medizin
ml
analyticsprimerkaraprivacydataDatenschutzMedizinml
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1mgbckr/mlflowhelper: Various tools for working with mlflow (see https://mlflow.org)
https://github.com/mgbckr/mlflowhelper
5 years ago by @becker
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machine
mlflowhelper
learning
tracking
mlflow
ml
machinemlflowhelperlearningtrackingmlflowml
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1EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
https://github.com/EthicalML/awesome-production-machine-learning
5 years ago by @becker
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science
systems
data
machine
libraries
learning
ml
list
sciencesystemsdatamachinelibrarieslearningmllist
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1[D] How do you manage your machine learning experiments? : MachineLearning
https://www.reddit.com/r/MachineLearning/comments/bx0apm/d_how_do_you_manage_your_machine_learning/
5 years ago by @becker
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projects
monitoring
data
learning
tracking
mlflow
science
productivity
machine
logger
logging
managing
sacred
model
ml
projectsmonitoringdatalearningtrackingmlflowscienceproductivitymachineloggerloggingmanagingsacredmodelml
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publications (hide)108
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1Feature-weighted elastic net: using "features of features" for better prediction
J. Tay, N. Aghaeepour, T. Hastie, and R. Tibshirani. Statistica Sinica, 33 (1): 259--279 (January 2023)
8 months ago by @becker
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ien
linear
background
machine
regression
learning
knowledge
bki
ml
informed
integration
ienlinearbackgroundmachineregressionlearningknowledgebkimlinformedintegration
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2Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer
H. Chereda, A. Bleckmann, F. Kramer, A. Leha, and T. Beissbarth. Studies in health technology and informatics, (September 2019)
8 months ago by @becker
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neural
background
gnn
machine
learning
knowledge
networks
graph
bki
ml
informed
integration
neuralbackgroundgnnmachinelearningknowledgenetworksgraphbkimlinformedintegration
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1Neuro-symbolic approaches in artificial intelligence
P. Hitzler, A. Eberhart, M. Ebrahimi, M. Sarker, and L. Zhou. National Science Review, 9 (6): nwac035 (March 2022)
11 months ago by @jaeschke
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deep
machine
neurosymbolic
ai
learning
ml
deepmachineneurosymbolicailearningml
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1Understanding Deep Learning
S. Prince. MIT Press, (2023)
11 months ago by @jaeschke
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deeplearning
neural
book
network
ml
deeplearningneuralbooknetworkml
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7On Calibration of Modern Neural Networks
C. Guo, G. Pleiss, Y. Sun, and K. Weinberger. roceedings of the 34th International Conference on Machine Learning, 70, page 1321-1330. PMLR, (2017)
11 months ago by @jaeschke
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neural
machine
learning
network
calibration
ml
neuralmachinelearningnetworkcalibrationml
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2Machine learning techniques for accountability
B. Kim, and F. Doshi-Velez. AI Magazine, 42 (1): 47--52 (2021)
2 years ago by @becker
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artificial
responsible
machine
ai
citedby:scholar:count:15
learning
intelligence
ml
citedby:scholar:timestamp:2023-4-10
accountability
artificialresponsiblemachineaicitedby:scholar:count:15learningintelligencemlcitedby:scholar:timestamp:2023-4-10accountability
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2Model Cards for Model Reporting
M. Mitchell, S. Wu, A. Zaldivar, P. Barnes, L. Vasserman, B. Hutchinson, E. Spitzer, I. Raji, and T. Gebru. Proceedings of the Conference on Fairness, Accountability, and Transparency, ACM, (January 2019)
2 years ago by @jaeschke
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card
machine
learning
model
description
ml
report
cardmachinelearningmodeldescriptionmlreport
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4Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
P. Villalobos, J. Sevilla, L. Heim, T. Besiroglu, M. Hobbhahn, and A. Ho. (2022)cite arxiv:2211.04325.
2 years ago by @jaeschke
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dataset
data
machine
learning
training
ml
datasetdatamachinelearningtrainingml
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4Decision Transformer: Reinforcement Learning via Sequence Modeling
L. Chen, K. Lu, A. Rajeswaran, K. Lee, A. Grover, M. Laskin, P. Abbeel, A. Srinivas, and I. Mordatch. (2021)cite arxiv:2106.01345Comment: First two authors contributed equally. Last two authors advised equally.
2 years ago by @jaeschke
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deeplearning
machine
transformer
learning
rl
reinforcement
ml
plk
deeplearningmachinetransformerlearningrlreinforcementmlplk
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2Pretrained Transformers for Text Ranking: BERT and Beyond
J. Lin, R. Nogueira, and A. Yates. (2020)cite arxiv:2010.06467Comment: Final preproduction version of volume in Synthesis Lectures on Human Language Technologies by Morgan & Claypool.
2 years ago by @jaeschke
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retrieval
deeplearning
neural
machine
ir
transformer
learning
bert
network
information
ml
retrievaldeeplearningneuralmachineirtransformerlearningbertnetworkinformationml
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2Why do tree-based models still outperform deep learning on typical tabular data?
L. Grinsztajn, E. Oyallon, and G. Varoquaux. Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, (2022)
2 years ago by @becker
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comparison
forest
decision
neural
data
tabular
learning
tree
trees
network
performance
random
citedby:scholar:count:5
evaluation
citedby:scholar:timestamp:2022-12-1
machine
ml
nn
comparisonforestdecisionneuraldatatabularlearningtreetreesnetworkperformancerandomcitedby:scholar:count:5evaluationcitedby:scholar:timestamp:2022-12-1machinemlnn
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1Interpretable machine learning prediction of all-cause mortality
W. Qiu, H. Chen, A. Dincer, S. Lundberg, M. Kaeberlein, and S. Lee. medRxiv, (2022)
2 years ago by @becker
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supervised
distance
citedby:scholar:count:3
machine
collaboration
fuelln
learning
interpretable
citedby:scholar:timestamp:2022-11-30
ml
superviseddistancecitedby:scholar:count:3machinecollaborationfuellnlearninginterpretablecitedby:scholar:timestamp:2022-11-30ml
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1CCGL: Contrastive Cascade Graph Learning
X. Xu, F. Zhou, K. Zhang, and S. Liu. IEEE Transactions on Knowledge and Data Engineering, (2022)
2 years ago by @jaeschke
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cascade
deeplearning
neural
contrastive
machine
learning
network
graph
ml
cascadedeeplearningneuralcontrastivemachinelearningnetworkgraphml
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1Explainable Deep Learning: A Field Guide for the Uninitiated
G. Ras, N. Xie, M. Gerven, and D. Doran. Journal of Artificial Intelligence Research, (January 2022)
2 years ago by @jaeschke
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deeplearning
machine
learning
survey
explainable
ml
deeplearningmachinelearningsurveyexplainableml
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2Explanatory Interactive Machine Learning
S. Teso, and K. Kersting. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, ACM, (January 2019)
2 years ago by @jaeschke
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artificial
machine
ai
learning
active
explainable
ki
intelligence
ml
artificialmachineailearningactiveexplainablekiintelligenceml
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1Snorkel: rapid training data creation with weak supervision
A. Ratner, S. Bach, H. Ehrenberg, J. Fries, S. Wu, and C. Ré. The VLDB Journal, 29 (2): 709--730 (May 1, 2020)
2 years ago by @jaeschke
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snorkel
labeling
supervision
data
machine
learning
training
ml
snorkellabelingsupervisiondatamachinelearningtrainingml
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1Trouble at the source
D. Monroe. Communications of the ACM, 64 (12): 17--19 (December 2021)
2 years ago by @jaeschke
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artificial
bias
machine
ai
learning
training
intelligence
ml
artificialbiasmachineailearningtrainingintelligenceml
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2Developing Open Source Educational Resources for Machine Learning and Data Science
L. Bothmann, S. Strickroth, G. Casalicchio, D. Rügamer, M. Lindauer, F. Scheipl, and B. Bischl. (2021)cite arxiv:2107.14330Comment: 6 pages.
3 years ago by @jaeschke
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science
data
machine
learning
oer
aiskills
ml
sciencedatamachinelearningoeraiskillsml
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1Maschinelles Lernen in der Prozessplanung
L. Stürenburg, B. Denkena, M. Lindauer, and M. Wichmann. VDI-Z, (October 2021)not peer-reviewed.
3 years ago by @tntl3s
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myown
Prozessplanung
ML
myownProzessplanungML
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1Objective Activity Parameters Track Patient-Specific Physical Recovery Trajectories After Surgery and Link With Individual Preoperative Immune States
R. Fallahzadeh, F. Verdonk, E. Ganio, A. Culos, N. Stanley, I. Maric, A. Chang, M. Becker, T. Phongpreecha, M. Xenochristou and 1 other author(s). Annals of Surgery, (October 2021)
3 years ago by @becker
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myown
machine
actigraphy
learning
medicine
recovery
iti
ml
surgery
myownmachineactigraphylearningmedicinerecoveryitimlsurgery
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