no code implementations • 22 Jan 2024 • Gregory Dexter, Borja Ocejo, Sathiya Keerthi, Aman Gupta, Ayan Acharya, Rajiv Khanna
In this paper, we delve deeper into the relationship between linear stability and sharpness.
no code implementations • 5 Sep 2023 • Kayhan Behdin, Ayan Acharya, Aman Gupta, Qingquan Song, Siyu Zhu, Sathiya Keerthi, Rahul Mazumder
Particularly noteworthy is our outlier-aware algorithm's capability to achieve near or sub-3-bit quantization of LLMs with an acceptable drop in accuracy, obviating the need for non-uniform quantization or grouping techniques, improving upon methods such as SpQR by up to two times in terms of perplexity.
no code implementations • 19 Feb 2023 • Kayhan Behdin, Qingquan Song, Aman Gupta, Sathiya Keerthi, Ayan Acharya, Borja Ocejo, Gregory Dexter, Rajiv Khanna, David Durfee, Rahul Mazumder
Modern deep learning models are over-parameterized, where different optima can result in widely varying generalization performance.
no code implementations • 7 Dec 2022 • Kayhan Behdin, Qingquan Song, Aman Gupta, David Durfee, Ayan Acharya, Sathiya Keerthi, Rahul Mazumder
To that end, this paper presents a thorough empirical evaluation of mSAM on various tasks and datasets.
no code implementations • 16 Jun 2020 • Matthew Walker, Bo Yan, Yiou Xiao, Yafei Wang, Ayan Acharya
Many tasks that rely on representations of nodes in graphs would benefit if those representations were faithful to distances between nodes in the graph.
no code implementations • 30 Dec 2015 • Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou
A gamma process dynamic Poisson factor analysis model is proposed to factorize a dynamic count matrix, whose columns are sequentially observed count vectors.