Zobrazeno 1 - 10
of 420
pro vyhledávání: '"Vishwanath, Sriram"'
Large language models have drastically changed the prospects of AI by introducing technologies for more complex natural language processing. However, current methodologies to train such LLMs require extensive resources including but not limited to la
Externí odkaz:
http://arxiv.org/abs/2410.21548
Stablecoins are a class of cryptocurrencies which aim at providing consistency and predictability, typically by pegging the token's value to that of a real world asset. Designing resilient decentralized stablecoins is a challenge, and prominent stabl
Externí odkaz:
http://arxiv.org/abs/2410.21446
In this paper, we consider a K-user interference channel where interference among the users is neither too strong nor too weak, a scenario that is relatively underexplored in the literature. We propose a novel deep learning-based approach to design t
Externí odkaz:
http://arxiv.org/abs/2407.15054
At the core of both successful generative and self-supervised representation learning models there is a reconstruction objective that incorporates some form of image corruption. Diffusion models implement this approach through a scheduled Gaussian co
Externí odkaz:
http://arxiv.org/abs/2406.17688
Autor:
Roush, Allen, Shabazz, Yusuf, Balaji, Arvind, Zhang, Peter, Mezza, Stefano, Zhang, Markus, Basu, Sanjay, Vishwanath, Sriram, Fatemi, Mehdi, Shwartz-Ziv, Ravid
We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate community. This dataset includes over 3.5 million documents with rich metadata, making it one of the most exte
Externí odkaz:
http://arxiv.org/abs/2406.14657
Autor:
Kale, Kaan, Esfahanizadeh, Homa, Elias, Noel, Baser, Oguzhan, Medard, Muriel, Vishwanath, Sriram
With the exponential growth in data volume and the emergence of data-intensive applications, particularly in the field of machine learning, concerns related to resource utilization, privacy, and fairness have become paramount. This paper focuses on t
Externí odkaz:
http://arxiv.org/abs/2402.05132
We study the incentives behind double-spend attacks on Nakamoto-style Proof-of-Work cryptocurrencies. In these systems, miners are allowed to choose which transactions to reference with their block, and a common strategy for selecting transactions is
Externí odkaz:
http://arxiv.org/abs/2312.07709
Neural networks perform exceedingly well across various machine learning tasks but are not immune to adversarial perturbations. This vulnerability has implications for real-world applications. While much research has been conducted, the underlying re
Externí odkaz:
http://arxiv.org/abs/2309.16878
Autor:
Yu, Haoxiang, Chen, Hsiao-Yuan, Lee, Sangsu, Vishwanath, Sriram, Zheng, Xi, Julien, Christine
With the rising emergence of decentralized and opportunistic approaches to machine learning, end devices are increasingly tasked with training deep learning models on-devices using crowd-sourced data that they collect themselves. These approaches are
Externí odkaz:
http://arxiv.org/abs/2304.05354
There are a multitude of Blockchain-based physical infrastructure systems, operating on a crypto-currency enabled token economy, where infrastructure suppliers are rewarded with tokens for enabling, validating, managing and/or securing the system. Ho
Externí odkaz:
http://arxiv.org/abs/2210.12881