On #scienceTwitter, my favourite thing was reading and, on rare occasions, writing "paper/preprint threads". From the researchers I followed and through the #Twitter algorithm, this became my most important source for new #research.

While people start to do the same on #Mastodon, I have the feeling that I miss important work bc no algorithm "saves" it for me if I don't watch my timeline constantly.

Two simple solutions would be: a commonly accepted hashtag that everybody uses when writing "paper threads" or an [...] @ a.gup.pe group with a similar adaptation rate.

#Question 1: is there already a mechanism for this that I missed?
#Question 2: What hashtag or group name?
I saw #TootPrint before. Maybe #PaperInAToot? #PaperInAPost? #PaperInAThread? #PaperPost? #MastoPrint?

Suggestions and boosts, please, we need reach for this! 🤓​

#TwitterMigration #Science #Scientist @phdstudents @academicchatter @neuroscience @cognition

'Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach', by Kweku Abraham, Ismaël Castillo, Elisabeth Gassiat.

http://jmlr.org/papers/v23/21-0054.html

#NewPaper #PaperPost

Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach

Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcemen...

Tong Mu, Stephan Zheng, Alexander R Trott

https://openreview.net/forum?id=DY1pMrmDkm

#NewPaper #PaperPost

Modeling Bounded Rationality in Multi-Agent Simulations Using...

Multi-agent reinforcement learning (MARL) is a powerful framework for studying emergent behavior in complex agent-based simulations. However, RL agents are often assumed to be rational and behave...

OpenReview

'Regularized K-means Through Hard-Thresholding', by Jakob Raymaekers, Ruben H. Zamar.

http://jmlr.org/papers/v23/21-0052.html

#NewPaper #PaperPost

Regularized K-means Through Hard-Thresholding

Calibrated Selective Classification

Adam Fisch, Tommi S. Jaakkola, Regina Barzilay

https://openreview.net/forum?id=zFhNBs8GaV

#NewPaper #PaperPost

Calibrated Selective Classification

Selective classification allows models to abstain from making predictions (e.g., say ``I don't know'') when in doubt in order to obtain better effective accuracy. While typical selective models...

OpenReview

'Gauss-Legendre Features for Gaussian Process Regression', by Paz Fink Shustin, Haim Avron.

http://jmlr.org/papers/v23/21-0030.html

#NewPaper #PaperPost

Gauss-Legendre Features for Gaussian Process Regression

'When Hardness of Approximation Meets Hardness of Learning', by Eran Malach, Shai Shalev-Shwartz.

http://jmlr.org/papers/v23/20-940.html

#NewPaper #PaperPost

When Hardness of Approximation Meets Hardness of Learning

Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunci...

Wei Wei, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang

https://openreview.net/forum?id=29V0xo7jKp

#NewPaper #PaperPost

Unsupervised Mismatch Localization in Cross-Modal Sequential Data...

Content mismatch usually occurs when data from one modality is translated to another, e.g. language learners producing mispronunciations (errors in speech) when reading a sentence (target text)...

OpenReview

'Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling', by Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang.

http://jmlr.org/papers/v23/20-910.html

#NewPaper #PaperPost

Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling