'Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis', by Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang.

http://jmlr.org/papers/v26/23-0832.html

#pruning #pruned #generalization

Humans can apply solutions of past problems to new problems. @gershbrain @nicoschuck &co reveal the neural correlates of #generalization and show that humans apply past policies in a reward-sensitive manner that leads to high performance @PLOSBiology https://plos.io/3SJPMof

AI Learns by Watching - Sholto & Trenton on Dwarkesh

#generalization #ai #reinforcementlearning

π0.5: A VLA with open-world generalization

https://pi.website/blog/pi05

#HackerNews #π0.5 #VLA #openworld #generalization #machinelearning #AI

e509 — Maverick and Marbles

e509 with Michael and Michael – stories and discussion all around #AI, #LLMs, #llamas, generated #Quake, #grokking, #generalization and much more.

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https://gamesatwork.biz/2025/04/14/e509-maverick-and-marbles/

e509 — Maverick and Marbles

e509 with Michael and Michael - stories and discussion all around #AI, #LLMs, #llamas, generated #Quake, #grokking, #generalization and much more.

https://gamesatwork.biz/2025/04/14/e509-maverick-and-marbles/

e509 — Maverick and Marbles

e509 with Michael and Michael - stories and discussion all around #AI, #LLMs, #llamas, generated #Quake, #grokking, #generalization and much more.

https://gamesatwork.biz/2025/04/14/e509-maverick-and-marbles/

Pipeline release! nf-core/drugresponseeval v1.0.0 - 1.0.0!

Please see the changelog: https://github.com/nf-core/drugresponseeval/releases/tag/1.0.0

#celllines #crossvalidation #deeplearning #drugresponse #drugresponseprediction #drugs #fairprinciples #generalization #hyperparametertuning #machinelearning #randomizationtests #robustnessassessment #training #nfcore #openscience #nextflow #bioinformatics

People value us for the value (they believe) we (might) add to them.

Generalizing of course, but it's all transactional. There's no (longer) valuing people for just who they are.

#society #people #life #generalization

Grokking at Edge of Numerical Stability
https://arxiv.org/abs/2501.04697
https://old.reddit.com/r/MachineLearning/comments/1i34keg/grokking_at_the_edge_of_numerical_stability
https://en.wikipedia.org/wiki/Grokking_(machine_learning)

* sudden generalization after prolonged overfitting
* massively overtrained NN can acq. "emergent"/supra performance/unexpected abilities
* unexp./accid. finding
* mechanisms starting to unravel

Grokked Transformers are Implicit Reasoners: Mechanistic Journey to Edge of Generalization
https://arxiv.org/abs/2405.15071
https://news.ycombinator.com/item?id=40495149

#LLM #ML #grokking #NN #emergence #generalization

A post from August 2024 by @grimalkina, boosted by someone on another instance, about why to report demographics in research even when you're not studying those groups. This seems like a great primer for people who have little background in basic #sampling and #generalization (for some reason I can't link/boost from here, so):

https://mastodon.social/@grimalkina/112966685297897685

My 2 cents (already at least partially covered by Dr. Hicks):

1. Your study is never just about your study. Good science is #open and reusable. e.g., maybe your study on tech-enabled healthcare access isn't specifically about LGBTQ+ or Hispanic people, but what are you doing to help a researcher who comes along in 10 years? That information will change what they find and report.

2. Marginalized groups are often minorities, meaning representative probability samples (or --uncomfortable gesture-- convenience samples) for bread-and-butter research frequently have subpopulations too small for reasonable power in correlations, group differences, etc. That's just reality. It's also a big problem for our understanding of #marginalized + #minority groups. Oversampling or targeted studies of those groups are important. It's also important to have a large number of less-targeted studies with relevant information that can be synthesized later (see #1): one study with 1.3% trans participants doesn't tell us much about the trans population, but 20 studies, each of which has 1.3% trans participants, could tell us meaningful things.

3. Representation is important. My belief is that #marginalized+minoritized people need their identities and existence public and constant. In #science, both they and other people consuming the research will benefit from being reminded that they are there, almost always, in our #research.

'Generalization on the Unseen, Logic Reasoning and Degree Curriculum', by Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk.

http://jmlr.org/papers/v25/24-0220.html

#sparse #learns #generalization

'Mentored Learning: Improving Generalization and Convergence of Student Learner', by Xiaofeng Cao, Yaming Guo, Heng Tao Shen, Ivor W. Tsang, James T. Kwok.

http://jmlr.org/papers/v25/23-1213.html

#learners #learner #generalization

'Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK', by Hongru Yang, Ziyu Jiang, Ruizhe Zhang, Yingbin Liang, Zhangyang Wang.

http://jmlr.org/papers/v25/23-0831.html

#sparse #gradient #generalization

@schizanon @strebski @fossdd I think #nationalism and #generalization are important factors for war and killing. I try to treat living beings as #individuals.

#STARTREK #LogicalThinking #70 - Proof By Example (Inappropriate #Generalization)

https://www.youtube.com/watch?v=NjntoaujuF0

#Trek #LogicalThinking #Philosophy #Spock #Enterprise #TAS #StarTrekTAS #TheAnimatedSeries

Могут ли трансформеры «думать»

Недавние исследования показывают, что модели трансформеров способны почти безошибочно решать задачи, требующие нескольких логических шагов. Например, из утверждения А вывести Б и дойти логически до В. И что удивительно, это достигается без использования Chain-of-Thought или особых промптов — только классический GPT-2. Давайте посмотрим, как трансформеры «думают» при решении задач рассуждения, и напишем для этого код с использованием библиотеки Hugging Face.

https://habr.com/ru/articles/840136/

#GPT #грокинг #память_ИИ #задачи_рассуждения #общий_искусственный_интеллект #обобщение #generalization #трансформатор #память_трансформеров

#8
The benefits of #Multitask studies are huge!

Most importantly, they allow testing the prevalent assumption of #generalization, yielding results with high chance of generalizing beyond the lab. What's more, they even enable the discovery of *new concepts*!

'Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance', by Lisha Chen, Heshan Fernando, Yiming Ying, Tianyi Chen.

http://jmlr.org/papers/v25/23-1287.html

#objectives #objective #generalization

@markstos Impressive work. Connectivity, to me, implies network / topological metrics. I’ve experimented a bit with betweenness centrality (https://en.wikipedia.org/wiki/Betweenness_centrality) in Python and found it promising (also, e.g., for #network #generalization). However, it’s computationally expensive. #gis