no code implementations • 1 Feb 2024 • Hsiang Hsu, Guihong Li, Shaohan Hu, Chun-Fu, Chen
Predictive multiplicity refers to the phenomenon in which classification tasks may admit multiple competing models that achieve almost-equally-optimal performance, yet generate conflicting outputs for individual samples.
no code implementations • 29 Mar 2023 • El Amine Cherrat, Snehal Raj, Iordanis Kerenidis, Abhishek Shekhar, Ben Wood, Jon Dee, Shouvanik Chakrabarti, Richard Chen, Dylan Herman, Shaohan Hu, Pierre Minssen, Ruslan Shaydulin, Yue Sun, Romina Yalovetzky, Marco Pistoia
Quantum machine learning has the potential for a transformative impact across industry sectors and in particular in finance.
no code implementations • 18 Oct 2022 • Chun-Fu Chen, Shaohan Hu, Zhonghao Shi, Prateek Gulati, Bill Moriarty, Marco Pistoia, Vincenzo Piuri, Pierangela Samarati
The recent rapid advances in machine learning technologies largely depend on the vast richness of data available today, in terms of both the quantity and the rich content contained within.
no code implementations • 9 Sep 2021 • Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur Rattew, Yue Sun, Romina Yalovetzky
In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term.
no code implementations • 5 Jun 2020 • Abhishek Gupta, Shaohan Hu, Weida Zhong, Adel Sadek, Lu Su, Chunming Qiao
Estimates of road grade/slope can add another dimension of information to existing 2D digital road maps.
no code implementations • 21 Oct 2019 • Arthur G. Rattew, Shaohan Hu, Marco Pistoia, Richard Chen, Steve Wood
Variational quantum algorithms have shown promise in numerous fields due to their versatility in solving problems of scientific and commercial interest.
1 code implementation • 21 Feb 2019 • Shuochao Yao, Ailing Piao, Wenjun Jiang, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Jinyang Li, Tianshi Wang, Shaohan Hu, Lu Su, Jiawei Han, Tarek Abdelzaher
IoT applications, however, often measure physical phenomena, where the underlying physics (such as inertia, wireless signal propagation, or the natural frequency of oscillation) are fundamentally a function of signal frequencies, offering better features in the frequency domain.
no code implementations • 11 Apr 2018 • Boheng Zhang, Shenglei Huang, Shaohan Hu
Existing supervised approaches didn't make use of the low-level features which are actually effective to this task.
1 code implementation • 7 Nov 2016 • Shuochao Yao, Shaohan Hu, Yiran Zhao, Aston Zhang, Tarek Abdelzaher
For many mobile applications, it is hard to find a distribution that exactly describes the noise in practice.