-
I have categorial features with 256 possible values each. I train a small forest with ~10 non oblique decision stumps. Each trees thus has only one decision node based on exactly one feature.
The m…
-
see also #3270
Dropping outliers or hard rejection weights is one of the easiest way to get high efficiency after using a high breakdown estimator in an initial stage. We can do the reweighting for…
-
|id|title|author|year|
|---|---|---|---|
|2|Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimation|Zhao, Hao and Lu, Ming and Yao, Anbang and Guo…
-
Hi @thiagopbueno,
I'm also working with @ramonpereira and @miquelramirez and I have been trying to run tf-plan in a Linux box with GPUs. However, in our experiments (the same domains as in issue #2…
-
First a great thank you for the great stuff you provide. I just recently started to work with RV and do digital logic since 1996.
While bringing a mini implementation up with all internal memories …
-
Thank you for sharing this beautiful code! I use the default DARTS_V2 architecture with appriximately 3.3M parameters to train CIFAR10 dataset. However, I found that it requires about 24h to train 600…
-
I love jaxtyping! Can I have more of it please?
Specifically, I'd like to make assertions about the sharding of my `jax.Array` objects. Given an array `Float[Array, "batch seqlen channel"]` I'd lik…
-
Hi, I'm grateful for your excellent work! I've implemented the code as per the instructions, and it runs without errors. However, the inference time is slow, approximately 176 seconds per iteration. I…
-
Hey,
Hope you're doing great! First of all thank you so much for this great OS Library. I've been playing with it for some time and am finding it very useful!
I was wondering if you have any recom…
ewajs updated
7 months ago
-
Hello, and thanks for such a great contribution to the field of interleaved LMMs! This is really great work. I was wondering if there was an example of the format for multiple image or multiple video …