Zobrazeno 1 - 10
of 613
pro vyhledávání: '"Chen, Tianqi"'
Autor:
Jeon, Byungsoo, Wu, Mengdi, Cao, Shiyi, Kim, Sunghyun, Park, Sunghyun, Aggarwal, Neeraj, Unger, Colin, Arfeen, Daiyaan, Liao, Peiyuan, Miao, Xupeng, Alizadeh, Mohammad, Ganger, Gregory R., Chen, Tianqi, Jia, Zhihao
Deep neural networks (DNNs) continue to grow rapidly in size, making them infeasible to train on a single device. Pipeline parallelism is commonly used in existing DNN systems to support large-scale DNN training by partitioning a DNN into multiple st
Externí odkaz:
http://arxiv.org/abs/2406.17145
Autor:
Chen, Tianqi, Hou, Jun, Zhou, Yinchi, Xie, Huidong, Chen, Xiongchao, Liu, Qiong, Guo, Xueqi, Xia, Menghua, Duncan, James S., Liu, Chi, Zhou, Bo
Positron Emission Tomography (PET) is an important clinical imaging tool but inevitably introduces radiation hazards to patients and healthcare providers. Reducing the tracer injection dose and eliminating the CT acquisition for attenuation correctio
Externí odkaz:
http://arxiv.org/abs/2406.08374
Autor:
Chen, Tianqi, Li, Zhe, Xu, Weixiang, Zhu, Zeyu, Li, Dong, Tian, Lu, Barsoum, Emad, Wang, Peisong, Cheng, Jian
Large language models (LLMs) have achieved remarkable performance on Natural Language Processing (NLP) tasks, but they are hindered by high computational costs and memory requirements. Ternarization, an extreme form of quantization, offers a solution
Externí odkaz:
http://arxiv.org/abs/2406.07177
Autor:
Feng, Siyuan, Liu, Jiawei, Lai, Ruihang, Ruan, Charlie F., Yu, Yong, Zhang, Lingming, Chen, Tianqi
Deploying machine learning (ML) on diverse computing platforms is crucial to accelerate and broaden their applications. However, it presents significant software engineering challenges due to the fast evolution of models, especially the recent Large
Externí odkaz:
http://arxiv.org/abs/2404.09151
Autor:
Zhou, Yinchi, Chen, Tianqi, Hou, Jun, Xie, Huidong, Dvornek, Nicha C., Zhou, S. Kevin, Wilson, David L., Duncan, James S., Liu, Chi, Zhou, Bo
Image-to-image translation is a vital component in medical imaging processing, with many uses in a wide range of imaging modalities and clinical scenarios. Previous methods include Generative Adversarial Networks (GANs) and Diffusion Models (DMs), wh
Externí odkaz:
http://arxiv.org/abs/2405.12223
The concepts of topology and geometry are of critical importance in exploring exotic phases of quantum matter. Though they have been investigated on various experimental platforms, to date a direct probe of topological and geometric properties on a u
Externí odkaz:
http://arxiv.org/abs/2403.14249
Aligning text-to-image diffusion model (T2I) with preference has been gaining increasing research attention. While prior works exist on directly optimizing T2I by preference data, these methods are developed under the bandit assumption of a latent re
Externí odkaz:
http://arxiv.org/abs/2402.08265
Autor:
Zhou, Bo, Hou, Jun, Chen, Tianqi, Zhou, Yinchi, Chen, Xiongchao, Xie, Huidong, Liu, Qiong, Guo, Xueqi, Tsai, Yu-Jung, Panin, Vladimir Y., Toyonaga, Takuya, Duncan, James S., Liu, Chi
Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging. However, the prevalent practice of employing additional CT scans for generating attenuation maps (u-map) for PET attenuation correction significantly elevates radia
Externí odkaz:
http://arxiv.org/abs/2401.14285
Autor:
Miao, Xupeng, Oliaro, Gabriele, Zhang, Zhihao, Cheng, Xinhao, Jin, Hongyi, Chen, Tianqi, Jia, Zhihao
In the rapidly evolving landscape of artificial intelligence (AI), generative large language models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However, the computational intensity and memory consumption of deploying
Externí odkaz:
http://arxiv.org/abs/2312.15234
Autor:
Chen, Tianqi, Liu, Yongfei, Wang, Zhendong, Yuan, Jianbo, You, Quanzeng, Yang, Hongxia, Zhou, Mingyuan
In light of the remarkable success of in-context learning in large language models, its potential extension to the vision domain, particularly with visual foundation models like Stable Diffusion, has sparked considerable interest. Existing approaches
Externí odkaz:
http://arxiv.org/abs/2312.01408