bookmarks (hide)65
- In mathematics, the Wasserstein or Kantorovich–Rubinstein metric or distance is a distance function defined between probability distributions on a given metric space M {\displaystyle M} M. Intuitively, if each distribution is viewed as a unit amount of "dirt" piled on M {\displaystyle M} M, the metric is the minimum "cost" of turning one pile into the other, which is assumed to be the amount of dirt that needs to be moved times the mean distance it has to be moved. Because of this analogy, the metric is known in computer science as the earth mover's distance.
- Scientists used machine learning to reveal new scientific knowledge hidden in old research papers.
- Can't remember what is precision and recall (sensitivity)? Why accuracy is not enough? Read the explanation with an example with a confusion matrix.
- We introduce Vicuna-13B, an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. Preliminary evaluation using GPT-4 as a judge shows Vicuna-13B achieves more than 90%* quality of OpenAI ChatGPT and Google Bard while outperforming other models like LLaMA and Stanford Alpaca in more than 90%* of cases. The cost of training Vicuna-13B is around $300. The code and weights, along with an online demo, are publicly available for non-commercial use.
publications
(hide)155
This list of posts may not be accurate to recent changes. If you want accurate posts, but with limited sorting follow this link.
- (2024)
- The Twelfth International Conference on Learning Representations, (2024)
- (2024)
- Forty-first International Conference on Machine Learning, (2024)
- (2024)
- (2024)
- (November 2023)
- (June 2023)
- (2023)
- (2023)
