Zobrazeno 1 - 10
of 3 537
pro vyhledávání: '"Khashayar P"'
Publikováno v:
International Journal of Dentistry, Vol 2023 (2023)
Introduction. This study compared the shear bond strength (SBS) of four innovative designs of the bonding surface of 3D-printed orthodontic attachments with conventional mesh design. Methods. In this in vitro study, the bonding surface design in diff
Externí odkaz:
https://doaj.org/article/5eec8b33b0874fb39fac538a5095519d
In many industrial applications, it is common that the graph embeddings generated from training GNNs are used in an ensemble model where the embeddings are combined with other tabular features (e.g., original node or edge features) in a downstream ML
Externí odkaz:
http://arxiv.org/abs/2411.00287
The intriguing in-context learning (ICL) abilities of deep Transformer models have lately garnered significant attention. By studying in-context linear regression on unimodal Gaussian data, recent empirical and theoretical works have argued that ICL
Externí odkaz:
http://arxiv.org/abs/2410.21698
Follow-the-Regularized-Leader (FTRL) algorithms are a popular class of learning algorithms for online linear optimization (OLO) that guarantee sub-linear regret, but the choice of regularizer can significantly impact dimension-dependent factors in th
Externí odkaz:
http://arxiv.org/abs/2410.17336
The remarkable generalization ability of neural networks is usually attributed to the implicit bias of SGD, which often yields models with lower complexity using simpler (e.g. linear) and low-rank features. Recent works have provided empirical and th
Externí odkaz:
http://arxiv.org/abs/2410.16401
The remarkable capability of Transformers to do reasoning and few-shot learning, without any fine-tuning, is widely conjectured to stem from their ability to implicitly simulate a multi-step algorithms -- such as gradient descent -- with their weight
Externí odkaz:
http://arxiv.org/abs/2410.08292
The use of guidance in diffusion models was originally motivated by the premise that the guidance-modified score is that of the data distribution tilted by a conditional likelihood raised to some power. In this work we clarify this misconception by r
Externí odkaz:
http://arxiv.org/abs/2409.13074
Publikováno v:
5th ACM International Conference on AI in Finance (ICAIF 2024)
Large Language Models such as GPTs (Generative Pre-trained Transformers) exhibit remarkable capabilities across a broad spectrum of applications. Nevertheless, due to their intrinsic complexity, these models present substantial challenges in interpre
Externí odkaz:
http://arxiv.org/abs/2407.11215
Autor:
Gatmiry, Khashayar, Schneider, Jon
We study a variant of prediction with expert advice where the learner's action at round $t$ is only allowed to depend on losses on a specific subset of the rounds (where the structure of which rounds' losses are visible at time $t$ is provided by a d
Externí odkaz:
http://arxiv.org/abs/2407.00571
It is essential to detect functional differences in various software engineering tasks, such as automated program repair, mutation testing, and code refactoring. The problem of detecting functional differences between two programs can be reduced to s
Externí odkaz:
http://arxiv.org/abs/2406.10375