Donald Trump’s legal team is making an 11th-hour attempt to block a court order
that would grant the BBC access to the president’s financial records,
as part of his multibillion-dollar lawsuit against the British broadcaster.
Trump claims that the BBC’s 2024 documentary on the January 6 attacks have damaged the president’s business interests.
In July, a Miami-based judge ruled that the president would have to start handing over detailed financial records to the BBC b…
#TuneTuesday (Aug 4)
“Never imagined, like an assassin / Yeah, one look took me down”
I became really aware of Canadian electronic music duo Sultan Shepard a few years ago and I instantly loved their 2021 song “Assassin” when I heard it. While it is technically EDM, the song’s vibe is a lot more chill and uplifting especially with the quiet breakdown in the middle.
Turns out @… and I both added some pride to our outfits today 🙌🏳️🌈 #mindmeld
Siri (Beta) is really interesting.
On one hand, I don't have to trust any new parties with my data. Apple already has it since they have my mobile devices, so if they were going to maliciously steal (e.g.) my email contents, they could already do that. This opens the door to a whole bunch of LLM data based interrogation that I wouldn't trust with other providers.
…on the other hand, the "on-device only" Siri falls over immediately when disabling the internet c…
from my link log —
Inko: Friendship ended with the garbage collector.
https://yorickpeterse.com/articles/friendship-ended-with-the-garbage-collector/
saved 2021-08-26
Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift
Bong Gyun Shin, Chan Sik Lee, Hyesun Suh
https://arxiv.org/abs/2605.21507 https://arxiv.org/pdf/2605.21507 https://arxiv.org/html/2605.21507
arXiv:2605.21507v1 Announce Type: new
Abstract: Atmospheric visibility is a critical variable for transportation safety and air quality management, however, accurate prediction remains challenging due to the complex interactions between meteorological conditions and air pollutants, as well as the rarity of low-visibility events. This study introduces a machine learning framework to nowcast visibility in six major South Korean cities. To handle the imbalance in the 2018-2020 training data, we applied the Synthetic Minority Over-sampling Technique with Nominal and Continuous (SMOTENC) and Conditional Tabular Generative Adversarial Network (CTGAN). An ensemble approach combining machine learning and deep learning models was then used and evaluated on a 2021 test dataset. The results revealed a marked decline in predictive performance in the test set compared to the cross-validation phase. This degradation was attributed to a distributional shift between training and testing periods, which was quantitatively confirmed by measuring the Wasserstein distance of the most influential feature identified by SHAP analysis. In general, this study presents a methodology that aims to simultaneously address the dual challenges of data imbalance and temporal distributional shifts, and emphasizes the necessity of accounting for evolving external environmental factors when implementing nowcasting models on time-series data.
toXiv_bot_toot
@cdarwin@c.im
