Zobrazeno 1 - 10
of 5 910
pro vyhledávání: '"A. Doudou"'
Covariate shift and outcome model heterogeneity are two prominent challenges in leveraging external sources to improve risk modeling for underrepresented cohorts in paucity of accurate labels. We consider the transfer learning problem targeting some
Externí odkaz:
http://arxiv.org/abs/2410.06484
The test of independence is a crucial component of modern data analysis. However, traditional methods often struggle with the complex dependency structures found in high-dimensional data. To overcome this challenge, we introduce a novel test statisti
Externí odkaz:
http://arxiv.org/abs/2409.07745
Autor:
Shou, Chaofan, Ke, Yuanyu, Yang, Yupeng, Su, Qi, Dadosh, Or, Eli, Assaf, Benchimol, David, Lu, Doudou, Tong, Daniel, Chen, Dex, Tan, Zoey, Chia, Jacob, Sen, Koushik, Lee, Wenke
Billions of dollars have been lost due to vulnerabilities in smart contracts. To counteract this, researchers have proposed attack frontrunning protections designed to preempt malicious transactions by inserting "whitehat" transactions ahead of them
Externí odkaz:
http://arxiv.org/abs/2409.06213
Electronic health record (EHR) systems contain a wealth of multimodal clinical data including structured data like clinical codes and unstructured data such as clinical notes. However, many existing EHR-focused studies has traditionally either concen
Externí odkaz:
http://arxiv.org/abs/2403.14926
Graphical models find numerous applications in biology, chemistry, sociology, neuroscience, etc. While substantial progress has been made in graph estimation, it remains largely unexplored how to select significant graph signals with uncertainty asse
Externí odkaz:
http://arxiv.org/abs/2403.12284
In addition to enhancing traffic safety and facilitating prompt emergency response, traffic incident detection plays an indispensable role in intelligent transportation systems by providing real-time traffic status information. This enables the reali
Externí odkaz:
http://arxiv.org/abs/2403.01147
Long-term traffic prediction has always been a challenging task due to its dynamic temporal dependencies and complex spatial dependencies. In this paper, we propose a model that combines hybrid Transformer and spatio-temporal self-supervised learning
Externí odkaz:
http://arxiv.org/abs/2401.16453
Intelligent Transportation Systems (ITS) utilize sensors, cameras, and big data analysis to monitor real-time traffic conditions, aiming to improve traffic efficiency and safety. Accurate vehicle recognition is crucial in this process, and Vehicle Lo
Externí odkaz:
http://arxiv.org/abs/2401.15458
As blockchain platforms grow exponentially, millions of lines of smart contract code are being deployed to manage extensive digital assets. However, vulnerabilities in this mission-critical code have led to significant exploitations and asset losses.
Externí odkaz:
http://arxiv.org/abs/2401.11108
Previous probabilistic models for 3D Human Pose Estimation (3DHPE) aimed to enhance pose accuracy by generating multiple hypotheses. However, most of the hypotheses generated deviate substantially from the true pose. Compared to deterministic models,
Externí odkaz:
http://arxiv.org/abs/2401.04921