Learning Theory Structure Train 
Beth's Blog: How Nonprofits Can Use Social Media
FEBRUARY 11, 2014
As a trainer and facilitator who works with nonprofit organizations and staffers, you have to be obsessed with learning theory to design and deliver effective instruction, have productive meetings, or embark on your own self-directed learning path. Here’s some examples.
Beth's Blog: How Nonprofits Can Use Social Media
JANUARY 27, 2014
Join me for a FREE Webinar: Training Tips that Work for Nonprofits on Jan.29th I’ll be sharing my best tips and secrets for designing and delivering training for nonprofit professionals that get results. I use a simple structure to design: before, during, and after. 29th at 1:00 PM EST/10:00 AM PST.
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The AI Alignment Forum
FEBRUARY 20, 2025
Published on February 20, 2025 11:54 PM GMT TLDR: We made substantial progress in 2024: We published a series of papers that verify key predictions of Singular Learning Theory (SLT) [ 1 , 2 , 3 , 4 , 5 , 6 ]. The S4 correspondence: Training data (and architecture) determine the loss landscape. Figure from Pepin Lehalleur et al.
Google Research AI blog
APRIL 30, 2023
If you’re registered for ICLR 2023, we hope you’ll visit the Google booth to learn more about the exciting work we’re doing across topics spanning representation and reinforcement learning, theory and optimization, social impact, safety and privacy, and applications from generative AI to speech and robotics. Mukund Varma T.
Stanford AI Lab Blog
DECEMBER 6, 2021
Kochenderfer Contact : philhc@stanford.edu Links: Paper Keywords : deep learning or neural networks, sparsity and feature selection, variational inference, (application) natural language and text processing Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Authors : Jeff Z.
Stanford AI Lab Blog
APRIL 25, 2022
List of Accepted Papers Autonomous Reinforcement Learning: Formalism and Benchmarking Authors : Archit Sharma*, Kelvin Xu*, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn Contact : architsh@stanford.edu Links: Paper | Website Keywords : reinforcement learning, continual learning, reset-free reinforcement learning MetaShift: (..)
The AI Alignment Forum
FEBRUARY 7, 2025
*Backdoors and other alignment stress tests: Past research has implanted backdoors in safety-trained LLMs and tested whether standard alignment techniques are capable of catching or removing them. Were interested in techniques like latent adversarial training and circuit breaking that might succeed where standard adversarial training falters.
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