Zobrazeno 1 - 10
of 233
pro vyhledávání: '"Mehta Sanket"'
Publikováno v:
Pleura and Peritoneum, Vol 9, Iss 3, Pp 93-105 (2024)
– Selection criteria used in all three randomized trials are predictive of a complete cytoreduction and not the benefit of surgery– Post-hoc & prespecified subgroup analyses indicate that not all patients undergoing secondary cytoreduction benefi
Externí odkaz:
https://doaj.org/article/ba8a41f2e1224d9a9a49f2718c7ef132
Autor:
Choe, Sang Keun, Mehta, Sanket Vaibhav, Ahn, Hwijeen, Neiswanger, Willie, Xie, Pengtao, Strubell, Emma, Xing, Eric
Despite its flexibility to learn diverse inductive biases in machine learning programs, meta learning (i.e., learning to learn) has long been recognized to suffer from poor scalability due to its tremendous compute/memory costs, training instability,
Externí odkaz:
http://arxiv.org/abs/2310.05674
Autor:
Das, Rajshekhar, Francis, Jonathan, Mehta, Sanket Vaibhav, Oh, Jean, Strubell, Emma, Moura, Jose
Self-training based on pseudo-labels has emerged as a dominant approach for addressing conditional distribution shifts in unsupervised domain adaptation (UDA) for semantic segmentation problems. A notable drawback, however, is that this family of app
Externí odkaz:
http://arxiv.org/abs/2305.00131
Publikováno v:
Journal of Minimal Access Surgery, Vol 5, Iss 2, Pp 43-46 (2009)
A feeding jejunostomy tube placement is required for entral feeding in a variety of clinical scenarios. It offers an advantage over gastrostomies by eliminating the risk of aspiration. Standard described laparoscopic methods require special instrumen
Externí odkaz:
https://doaj.org/article/100bf24614a24e76bd995699773e271f
Autor:
Mehta, Sanket Vaibhav, Gupta, Jai, Tay, Yi, Dehghani, Mostafa, Tran, Vinh Q., Rao, Jinfeng, Najork, Marc, Strubell, Emma, Metzler, Donald
Differentiable Search Indices (DSIs) encode a corpus of documents in model parameters and use the same model to answer user queries directly. Despite the strong performance of DSI models, deploying them in situations where the corpus changes over tim
Externí odkaz:
http://arxiv.org/abs/2212.09744
Autor:
Sodhani, Shagun, Faramarzi, Mojtaba, Mehta, Sanket Vaibhav, Malviya, Pranshu, Abdelsalam, Mohamed, Janarthanan, Janarthanan, Chandar, Sarath
This primer is an attempt to provide a detailed summary of the different facets of lifelong learning. We start with Chapter 2 which provides a high-level overview of lifelong learning systems. In this chapter, we discuss prominent scenarios in lifelo
Externí odkaz:
http://arxiv.org/abs/2207.04354
Model compression by way of parameter pruning, quantization, or distillation has recently gained popularity as an approach for reducing the computational requirements of modern deep neural network models for NLP. Inspired by prior works suggesting a
Externí odkaz:
http://arxiv.org/abs/2205.12694
Publikováno v:
In European Journal of Surgical Oncology October 2024 50(10)
Publikováno v:
Journal of Machine Learning Research 24 (2023) 1-50
The lifelong learning paradigm in machine learning is an attractive alternative to the more prominent isolated learning scheme not only due to its resemblance to biological learning but also its potential to reduce energy waste by obviating excessive
Externí odkaz:
http://arxiv.org/abs/2112.09153
Autor:
Aribandi, Vamsi, Tay, Yi, Schuster, Tal, Rao, Jinfeng, Zheng, Huaixiu Steven, Mehta, Sanket Vaibhav, Zhuang, Honglei, Tran, Vinh Q., Bahri, Dara, Ni, Jianmo, Gupta, Jai, Hui, Kai, Ruder, Sebastian, Metzler, Donald
Despite the recent success of multi-task learning and transfer learning for natural language processing (NLP), few works have systematically studied the effect of scaling up the number of tasks during pre-training. Towards this goal, this paper intro
Externí odkaz:
http://arxiv.org/abs/2111.10952