Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Hemmat, Reyhane Askari"'
Autor:
Hemmat, Reyhane Askari, Hall, Melissa, Sun, Alicia, Ross, Candace, Drozdzal, Michal, Romero-Soriano, Adriana
With the growing popularity of text-to-image generative models, there has been increasing focus on understanding their risks and biases. Recent work has found that state-of-the-art models struggle to depict everyday objects with the true diversity of
Externí odkaz:
http://arxiv.org/abs/2406.04551
Autor:
Bordes, Florian, Pang, Richard Yuanzhe, Ajay, Anurag, Li, Alexander C., Bardes, Adrien, Petryk, Suzanne, Mañas, Oscar, Lin, Zhiqiu, Mahmoud, Anas, Jayaraman, Bargav, Ibrahim, Mark, Hall, Melissa, Xiong, Yunyang, Lebensold, Jonathan, Ross, Candace, Jayakumar, Srihari, Guo, Chuan, Bouchacourt, Diane, Al-Tahan, Haider, Padthe, Karthik, Sharma, Vasu, Xu, Hu, Tan, Xiaoqing Ellen, Richards, Megan, Lavoie, Samuel, Astolfi, Pietro, Hemmat, Reyhane Askari, Chen, Jun, Tirumala, Kushal, Assouel, Rim, Moayeri, Mazda, Talattof, Arjang, Chaudhuri, Kamalika, Liu, Zechun, Chen, Xilun, Garrido, Quentin, Ullrich, Karen, Agrawal, Aishwarya, Saenko, Kate, Celikyilmaz, Asli, Chandra, Vikas
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guide us through unfamiliar environments to generative models that produce
Externí odkaz:
http://arxiv.org/abs/2405.17247
Autor:
AskariHemmat, MohammadHossein, Jeddi, Ahmadreza, Hemmat, Reyhane Askari, Lazarevich, Ivan, Hoffman, Alexander, Sah, Sudhakar, Saboori, Ehsan, Savaria, Yvon, David, Jean-Pierre
Quantization lowers memory usage, computational requirements, and latency by utilizing fewer bits to represent model weights and activations. In this work, we investigate the generalization properties of quantized neural networks, a characteristic th
Externí odkaz:
http://arxiv.org/abs/2404.11769
Autor:
Hemmat, Reyhane Askari, Pezeshki, Mohammad, Bordes, Florian, Drozdzal, Michal, Romero-Soriano, Adriana
Current status quo in machine learning is to use static datasets of real images for training, which often come from long-tailed distributions. With the recent advances in generative models, researchers have started augmenting these static datasets wi
Externí odkaz:
http://arxiv.org/abs/2310.00158
Autor:
AskariHemmat, MohammadHossein, Hemmat, Reyhane Askari, Hoffman, Alex, Lazarevich, Ivan, Saboori, Ehsan, Mastropietro, Olivier, Sah, Sudhakar, Savaria, Yvon, David, Jean-Pierre
In this paper we study the effects of quantization in DNN training. We hypothesize that weight quantization is a form of regularization and the amount of regularization is correlated with the quantization level (precision). We confirm our hypothesis
Externí odkaz:
http://arxiv.org/abs/2206.12372
Adversarial formulations such as generative adversarial networks (GANs) have rekindled interest in two-player min-max games. A central obstacle in the optimization of such games is the rotational dynamics that hinder their convergence. In this paper,
Externí odkaz:
http://arxiv.org/abs/2010.13846
Autor:
Gidel, Gauthier, Hemmat, Reyhane Askari, Pezeshki, Mohammad, Lepriol, Remi, Huang, Gabriel, Lacoste-Julien, Simon, Mitliagkas, Ioannis
Games generalize the single-objective optimization paradigm by introducing different objective functions for different players. Differentiable games often proceed by simultaneous or alternating gradient updates. In machine learning, games are gaining
Externí odkaz:
http://arxiv.org/abs/1807.04740
Service level agreement (SLA) is an essential part of cloud systems to ensure maximum availability of services for customers. With a violation of SLA, the provider has to pay penalties. In this paper, we explore two machine learning models: Naive Bay
Externí odkaz:
http://arxiv.org/abs/1611.10338