Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Alex Tamkin"'
Publikováno v:
EMNLP (Findings)
How does language model pretraining help transfer learning? We consider a simple ablation technique for determining the impact of each pretrained layer on transfer task performance. This method, partial reinitialization, involves replacing different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ede900e376fa9ccf014b1c2d3702b0f4
Publikováno v:
AAAI
While maximizing expected return is the goal in most reinforcement learning approaches, risk-sensitive objectives such as conditional value at risk (CVaR) are more suitable for many high-stakes applications. However, relatively little is known about
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e210cf5eab74f44f4161816e37aba18e
http://arxiv.org/abs/1911.01546
http://arxiv.org/abs/1911.01546
Autor:
James A. Landay, Tommy Fang, Michelle Park, Cheng Yao Wang, Jessica R. Cauchard, Luke Vink, Alex Tamkin
Publikováno v:
HRI
Drones are becoming ubiquitous and offer support to people in various tasks, such as photography, in increasingly interactive social contexts. We introduce drone.io, a projected body-centric graphical user interface for human-drone interaction. Using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eb0273c4c774e050947c45e7fac933d
https://doi.org/10.1109/hri.2019.8673011
https://doi.org/10.1109/hri.2019.8673011
Autor:
Olivia Li, Atticus Geiger, Alex Tamkin, Clemens Rosenbaum, Sandhini Agarwal, Matthew Riemer, Tim Klinger, Lauri Karttunen, Ignacio Cases, Christopher Potts, Dan Jurafsky, Joshua D. Greene
Publikováno v:
NAACL-HLT (1)
We introduce Recursive Routing Networks (RRNs), which are modular, adaptable models that learn effectively in diverse environments. RRNs consist of a set of functions, typically organized into a grid, and a meta-learner decision-making component call
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2af9c9a0bd1c85c45c0be3bb4ad98b1d
https://doi.org/10.18653/v1/n19-1365
https://doi.org/10.18653/v1/n19-1365