Zobrazeno 1 - 10
of 753
pro vyhledávání: '"Gupta, Aman"'
Autor:
Gupta, Aman, Ravichandran, Anirudh, Zhang, Ziji, Shah, Swair, Beniwal, Anurag, Sadagopan, Narayanan
Task-oriented dialogue systems are essential for applications ranging from customer service to personal assistants and are widely used across various industries. However, developing effective multi-domain systems remains a significant challenge due t
Externí odkaz:
http://arxiv.org/abs/2411.00427
Autor:
Schmude, Johannes, Roy, Sujit, Trojak, Will, Jakubik, Johannes, Civitarese, Daniel Salles, Singh, Shraddha, Kuehnert, Julian, Ankur, Kumar, Gupta, Aman, Phillips, Christopher E, Kienzler, Romeo, Szwarcman, Daniela, Gaur, Vishal, Shinde, Rajat, Lal, Rohit, Da Silva, Arlindo, Diaz, Jorge Luis Guevara, Jones, Anne, Pfreundschuh, Simon, Lin, Amy, Sheshadri, Aditi, Nair, Udaysankar, Anantharaj, Valentine, Hamann, Hendrik, Watson, Campbell, Maskey, Manil, Lee, Tsengdar J, Moreno, Juan Bernabe, Ramachandran, Rahul
Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing number of large AI models that address use cases such as forecasting, downs
Externí odkaz:
http://arxiv.org/abs/2409.13598
Publikováno v:
Decision Science Letters, Vol 10, Iss 3, Pp 361-374 (2021)
Already faced with tight competition and low profit margins, the airline industry is going through major changes in the wake of the current pandemic resulting in travel restrictions and slump demands, prompting airlines to curtail services and invest
Externí odkaz:
https://doaj.org/article/febba3d0d47b4e24a2531296e4e5a5ba
Autor:
Borisyuk, Fedor, Song, Qingquan, Zhou, Mingzhou, Parameswaran, Ganesh, Arun, Madhu, Popuri, Siva, Bingol, Tugrul, Pei, Zhuotao, Lee, Kuang-Hsuan, Zheng, Lu, Shao, Qizhan, Naqvi, Ali, Zhou, Sen, Gupta, Aman
This paper introduces LiNR, LinkedIn's large-scale, GPU-based retrieval system. LiNR supports a billion-sized index on GPU models. We discuss our experiences and challenges in creating scalable, differentiable search indexes using TensorFlow and PyTo
Externí odkaz:
http://arxiv.org/abs/2407.13218
Autor:
Dhakal, Manish, Chhetri, Arman, Gupta, Aman Kumar, Lamichhane, Prabin, Pandey, Suraj, Shakya, Subarna
Publikováno v:
2022 International Conference on Inventive Computation Technologies (ICICT), pp. 515-521
This paper presents an end-to-end deep learning model for Automatic Speech Recognition (ASR) that transcribes Nepali speech to text. The model was trained and tested on the OpenSLR (audio, text) dataset. The majority of the audio dataset have silent
Externí odkaz:
http://arxiv.org/abs/2406.17825
Global climate models typically operate at a grid resolution of hundreds of kilometers and fail to resolve atmospheric mesoscale processes, e.g., clouds, precipitation, and gravity waves (GWs). Model representation of these processes and their source
Externí odkaz:
http://arxiv.org/abs/2406.14775
Autor:
Wei, Changshuai, Zelditch, Benjamin, Chen, Joyce, Ribeiro, Andre Assuncao Silva T, Tay, Jingyi Kenneth, Elizondo, Borja Ocejo, Selvaraj, Keerthi, Gupta, Aman, De Almeida, Licurgo Benemann
Computational marketing has become increasingly important in today's digital world, facing challenges such as massive heterogeneous data, multi-channel customer journeys, and limited marketing budgets. In this paper, we propose a general framework fo
Externí odkaz:
http://arxiv.org/abs/2405.10490
Autor:
Wang, Ruofan, Prabhakar, Prakruthi, Srivastava, Gaurav, Wang, Tianqi, Jalali, Zeinab S., Bharill, Varun, Ouyang, Yunbo, Nigam, Aastha, Venugopalan, Divya, Gupta, Aman, Borisyuk, Fedor, Keerthi, Sathiya, Muralidharan, Ajith
In the realm of recommender systems, the ubiquitous adoption of deep neural networks has emerged as a dominant paradigm for modeling diverse business objectives. As user bases continue to expand, the necessity of personalization and frequent model up
Externí odkaz:
http://arxiv.org/abs/2403.00803
Autor:
Borisyuk, Fedor, Zhou, Mingzhou, Song, Qingquan, Zhu, Siyu, Tiwana, Birjodh, Parameswaran, Ganesh, Dangi, Siddharth, Hertel, Lars, Xiao, Qiang, Hou, Xiaochen, Ouyang, Yunbo, Gupta, Aman, Singh, Sheallika, Liu, Dan, Cheng, Hailing, Le, Lei, Hung, Jonathan, Keerthi, Sathiya, Wang, Ruoyan, Zhang, Fengyu, Kothari, Mohit, Zhu, Chen, Sun, Daqi, Dai, Yun, Luan, Xun, Zhu, Sirou, Wang, Zhiwei, Daftary, Neil, Shen, Qianqi, Jiang, Chengming, Wei, Haichao, Varshney, Maneesh, Ghoting, Amol, Ghosh, Souvik
We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modeling improvements, including Residual DCN, which adds attention and resid
Externí odkaz:
http://arxiv.org/abs/2402.06859
Stochastic Gradient Descent (SGD) stands as a cornerstone optimization algorithm with proven real-world empirical successes but relatively limited theoretical understanding. Recent research has illuminated a key factor contributing to its practical e
Externí odkaz:
http://arxiv.org/abs/2401.12332