Analysis Evaluation Learning Theory 
Beth's Blog: How Nonprofits Can Use Social Media
FEBRUARY 18, 2014
Using the ADDIE for designing your workshop, you arrive at the “E” or evaluation. ” While a participant survey is an important piece of your evaluation, it is critical to incorporate a holistic reflection of your workshop. There are two different methods to evaluate your training. Use Learning Theory.
Beth's Blog: How Nonprofits Can Use Social Media
JANUARY 27, 2014
Designing and delivering a training to a nonprofit audience is not about extreme content delivery or putting together a PowerPoint and answering questions. If you want to get results, you need to think about instructional design and learning theory. And, there is no shortage of learning theories and research.
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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
We think this adversarial style of evaluation and iteration is necessary to ensure an AI system has a low probability of catastrophic failure. Wed like to support more such evaluations, especially on scalable oversight protocols like AI debate. and Which rules are LLM agents happy to break, and which are they more committed to? .
The AI Alignment Forum
FEBRUARY 28, 2025
The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret In this paper , we look at what happens when a learnt reward function is optimised. This means that it essentially makes the analysis in this paper more realistic, and more closely applicable to humans.
Museum 2.0
SEPTEMBER 26, 2012
The purpose of my thesis was two-fold: To research and analyze community and civic engagement practices, methods, theories and examples in other museum programs. To apply the results of my analysis to produce a community-driven program design specifically for implementation at the Santa Cruz Museum of Art & History (the MAH).
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