#supervised — Public Fediverse posts

#Teilautonomes #Fahren:

#Tesla bringt #FSD erstmals nach #Europa

Tesla darf sein fortgeschrittenes Fahrassistenzsystem "Full Self-Driving ( #Supervised )" erstmals in Europa einsetzen, und zwar in den Niederlanden. Die dortige #Zulassungsbehörde #RDW hat dem System laut Reuters eine Typgenehmigung erteilt und gleichzeitig ein ungewöhnlich klares Statement zur Sicherheit abgegeben.

https://www.golem.de/news/teilautonomes-fahren-tesla-bringt-fsd-erstmals-nach-europa-2604-207468.html

#TeslaKägi

vom #TESLA #autonom chauffiert - meine " #FSD #Supervised " #Probefahrt in #Deutschland

https://m.youtube.com/watch?v=y0rSTe9msRk

'A Comparative Evaluation of Quantification Methods', by Tobias Schumacher, Markus Strohmaier, Florian Lemmerich.

http://jmlr.org/papers/v26/21-0241.html

#classifiers #supervised #quantification

'Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response', by Jue Hou, Rajarshi Mukherjee, Tianxi Cai.

http://jmlr.org/papers/v26/23-1587.html

#supervised #annotated #annotate

'Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response', by Jue Hou, Rajarshi Mukherjee, Tianxi Cai.

http://jmlr.org/papers/v26/23-1587.html

#supervised #annotated #annotate

'Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response', by Jue Hou, Rajarshi Mukherjee, Tianxi Cai.

http://jmlr.org/papers/v26/23-1587.html

#supervised #annotated #annotate

'Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response', by Jue Hou, Rajarshi Mukherjee, Tianxi Cai.

http://jmlr.org/papers/v26/23-1587.html

#supervised #annotated #annotate

'Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response', by Jue Hou, Rajarshi Mukherjee, Tianxi Cai.

http://jmlr.org/papers/v26/23-1587.html

#supervised #annotated #annotate

'Learning from many trajectories', by Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi.

http://jmlr.org/papers/v25/23-1145.html

#trajectories #trajectory #supervised

'An Entropy-Based Model for Hierarchical Learning', by Amir R. Asadi.

http://jmlr.org/papers/v25/23-0096.html

#supervised #hierarchical #multiscale

'Semi-supervised Inference for Block-wise Missing Data without Imputation', by Shanshan Song, Yuanyuan Lin, Yong Zhou.

http://jmlr.org/papers/v25/21-1504.html

#imputation #supervised #neuroimaging

'On Truthing Issues in Supervised Classification', by Jonathan K. Su.

http://jmlr.org/papers/v25/19-301.html

#classification #classifier #supervised

'Fair Data Representation for Machine Learning at the Pareto Frontier', by Shizhou Xu, Thomas Strohmer.

http://jmlr.org/papers/v24/22-0005.html

#wasserstein #supervised #fairness

'The Power of Contrast for Feature Learning: A Theoretical Analysis', by Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang.

http://jmlr.org/papers/v24/21-1501.html

#autoencoders #supervised #generative

'Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes', by Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee.

http://jmlr.org/papers/v24/21-0187.html

#supervised #labeled #annotated

'Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes', by Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee.

http://jmlr.org/papers/v24/21-0187.html

#supervised #labeled #annotated

'Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes', by Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee.

http://jmlr.org/papers/v24/21-0187.html

#supervised #labeled #annotated

'Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes', by Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee.

http://jmlr.org/papers/v24/21-0187.html

#supervised #labeled #annotated

'Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes', by Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee.

http://jmlr.org/papers/v24/21-0187.html

#supervised #labeled #annotated

'Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction', by Jue Hou, Zijian Guo, Tianxi Cai.

http://jmlr.org/papers/v24/21-1075.html

#imputation #predictors #supervised

Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj et al.

Action editor: Frederic Sala.

https://openreview.net/forum?id=PRrKOaDQtQ

#supervised #labeling #classifier

Supervised Knowledge May Hurt Novel Class Discovery Performance

ZIYUN LI, Jona Otholt, Ben Dai, Di Hu, Christoph Meinel, Haojin Yang

Action editor: Vikas Sindhwani.

https://openreview.net/forum?id=oqOBTo5uWD

#supervised #labeled #imagenet

Trip-ROMA: Self-Supervised Learning with Triplets and Random Mappings

Wenbin Li, Xuesong Yang, Meihao Kong, Lei Wang, Jing Huo, Yang Gao, Jiebo Luo

Action editor: Joao Carreira.

https://openreview.net/forum?id=MR4glug5GU

#supervised #mappings #visual

FASTRAIN-GNN: Fast and Accurate Self-Training for Graph Neural Networks

Amrit Nagarajan, Anand Raghunathan

https://openreview.net/forum?id=1IYJfwJtjQ

#supervised #trained #gnn

'Labels, Information, and Computation: Efficient Learning Using Sufficient Labels', by Shiyu Duan, Spencer Chang, Jose C. Principe.

http://jmlr.org/papers/v24/22-0019.html

#supervised #labeled #classifier

TLDR: Twin Learning for Dimensionality Reduction

Yannis Kalantidis, Carlos Eduardo Rosar Kos Lassance, Jon Almazán, Diane Larlus

https://openreview.net/forum?id=86fhqdBUbx

#dimensionality #dimensional #supervised