Zobrazeno 1 - 10
of 24 883
pro vyhledávání: '"Eslami, A. A."'
Autor:
Koukounas, Andreas, Mastrapas, Georgios, Wang, Bo, Akram, Mohammad Kalim, Eslami, Sedigheh, Günther, Michael, Mohr, Isabelle, Sturua, Saba, Martens, Scott, Wang, Nan, Xiao, Han
Contrastive Language-Image Pretraining (CLIP) is a highly effective method for aligning images and texts in a shared embedding space. These models are widely used for tasks such as cross-modal information retrieval and multi-modal understanding. Howe
Externí odkaz:
http://arxiv.org/abs/2412.08802
Autor:
Sedaghat, Nima, Chatchadanoraset, Tanawan, Chandler, Colin Orion, Mahabal, Ashish, Eslami, Maryam
Motivated by the scarcity of proper labels in an astrophysical application, we have developed a novel technique, called Selfish Evolution, which allows for the detection and correction of corrupted labels in a weakly supervised fashion. Unlike method
Externí odkaz:
http://arxiv.org/abs/2412.00077
This study introduces a novel methodology for managing train network disruptions across the entire rail network, leveraging digital tools and methodologies. The approach involves two stages, taking into account possible and practical features such as
Externí odkaz:
http://arxiv.org/abs/2411.14671
Autor:
Johnson, Nari, Silva, Elise, Leon, Harrison, Eslami, Motahhare, Schwanke, Beth, Dotan, Ravit, Heidari, Hoda
Most AI tools adopted by governments are not developed internally, but instead are acquired from third-party vendors in a process called public procurement. While scholars and regulatory proposals have recently turned towards procurement as a site of
Externí odkaz:
http://arxiv.org/abs/2411.04994
Diabetic retinopathy is the leading cause of vision loss in working-age adults worldwide, yet under-resourced regions lack ophthalmologists. Current state-of-the-art deep learning systems struggle at these institutions due to limited generalizability
Externí odkaz:
http://arxiv.org/abs/2411.00869
The recent excitement around generative models has sparked a wave of proposals suggesting the replacement of human participation and labor in research and development--e.g., through surveys, experiments, and interviews--with synthetic research data g
Externí odkaz:
http://arxiv.org/abs/2409.19430
Recently, an increasing number of news organizations have integrated artificial intelligence (AI) into their workflows, leading to a further influx of AI technologists and data workers into the news industry. This has initiated cross-functional colla
Externí odkaz:
http://arxiv.org/abs/2409.12000
Autor:
Hsieh, Jane, Zhang, Angie, Kim, Seyun, Rao, Varun Nagaraj, Dalal, Samantha, Mateescu, Alexandra, Grohmann, Rafael Do Nascimento, Eslami, Motahhare, Lee, Min Kyung, Zhu, Haiyi
Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulations. The CSCW and HCI communities increasingly turn to worker data col
Externí odkaz:
http://arxiv.org/abs/2409.00737
This paper presents a memristor-based compute-in-memory hardware accelerator for on-chip training and inference, focusing on its accuracy and efficiency against device variations, conductance errors, and input noise. Utilizing realistic SPICE models
Externí odkaz:
http://arxiv.org/abs/2408.14680
Autor:
Eslami, Navid, Dayan, Niv
Range filters are probabilistic data structures that answer approximate range emptiness queries. They aid in avoiding processing empty range queries and have use cases in many application domains such as key-value stores and social web analytics. How
Externí odkaz:
http://arxiv.org/abs/2408.05625