Zobrazeno 1 - 10
of 15 645
pro vyhledávání: '"A, Shervin"'
Autor:
Arikan, Demir, Zhang, Peiyao, Sommersperger, Michael, Dehghani, Shervin, Esfandiari, Mojtaba, Taylor, Russel H., Nasseri, M. Ali, Gehlbach, Peter, Navab, Nassir, Iordachita, Iulian
Exudative (wet) age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, typically treated with intravitreal injections. Emerging therapies, such as subretinal injections of stem cells, gene therapy, small molecules o
Externí odkaz:
http://arxiv.org/abs/2411.18521
Autor:
Arikan, Demir, Zhang, Peiyao, Sommersperger, Michael, Dehghani, Shervin, Esfandiari, Mojtaba, Taylor, Russel H., Nasseri, M. Ali, Gehlbach, Peter, Navab, Nassir, Iordachita, Iulian
Robotic platforms provide repeatable and precise tool positioning that significantly enhances retinal microsurgery. Integration of such systems with intraoperative optical coherence tomography (iOCT) enables image-guided robotic interventions, allowi
Externí odkaz:
http://arxiv.org/abs/2411.06557
This paper presents a novel approach to one-class classifier fusion through locally adaptive learning with dynamic $\ell$p-norm constraints. We introduce a framework that dynamically adjusts fusion weights based on local data characteristics, address
Externí odkaz:
http://arxiv.org/abs/2411.06406
In e-commerce, high consideration search missions typically require careful and elaborate decision making, and involve a substantial research investment from customers. We consider the task of identifying High Consideration (HC) queries. Identifying
Externí odkaz:
http://arxiv.org/abs/2410.13951
Autor:
Ghasemlou, Shervin, Katiyar, Ashish, Saraf, Aparajita, Moon, Seungwhan, Pujari, Mangesh, Donmez, Pinar, Damavandi, Babak, Kumar, Anuj
In this paper, we investigate the problem of "generation supervision" in large language models, and present a novel bicameral architecture to separate supervision signals from their core capability, helpfulness. Doppelg\"anger, a new module parallel
Externí odkaz:
http://arxiv.org/abs/2409.06107
Autor:
Ardeshir, Shervin
This paper explores a top-down approach to automating incremental advances in machine learning research through component-level innovation, facilitated by Large Language Models (LLMs). Our framework systematically generates novel components, validate
Externí odkaz:
http://arxiv.org/abs/2409.05258
Diffusion models have attained prominence for their ability to synthesize a probability distribution for a given dataset via a diffusion process, enabling the generation of new data points with high fidelity. However, diffusion processes are prone to
Externí odkaz:
http://arxiv.org/abs/2408.15094
In this work, we survey recent studies on masked image modeling (MIM), an approach that emerged as a powerful self-supervised learning technique in computer vision. The MIM task involves masking some information, e.g. pixels, patches, or even latent
Externí odkaz:
http://arxiv.org/abs/2408.06687
This letter introduces a framework for the automatic generation of hardware cores for Artificial Neural Network (ANN)-based chaotic oscillators. The framework trains the model to approximate a chaotic system, then performs design space exploration yi
Externí odkaz:
http://arxiv.org/abs/2407.19165
Autor:
Kuzi, Saar, Malmasi, Shervin
Publikováno v:
In ACM SIGIR Forum, vol. 58, no. 1, pp. 1-10. New York, NY, USA: ACM, 2024
Consumers on a shopping mission often leverage both product search and information seeking systems, such as web search engines and Question Answering (QA) systems, in an iterative process to improve their understanding of available products and reach
Externí odkaz:
http://arxiv.org/abs/2407.09653