1 code implementation • 15 Dec 2023 • Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature.
no code implementations • 16 Sep 2023 • Hayden Helm, Carey E. Priebe, Weiwei Yang
Implicit in these efforts is an assumption that the generation properties of a human are different from that of the machine.
no code implementations • 16 Mar 2023 • Ning Qi, Peng Li, Lin Cheng, Ziyi Zhang, Wenrui Huang, Weiwei Yang
Energy storage (ES) and virtual energy storage (VES) are key components to realizing power system decarbonization.
no code implementations • 27 Feb 2023 • Hayden S. Helm, Ashwin De Silva, Joshua T. Vogelstein, Carey E. Priebe, Weiwei Yang
We propose a class of models based on Fisher's Linear Discriminant (FLD) in the context of domain adaptation.
1 code implementation • 30 Nov 2022 • Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang
Off-policy and Offline RL methods have been proposed to reduce the number of interactions with the physical environment by learning control policies from historical data.
no code implementations • 28 May 2022 • Li Chen, Ningyuan Huang, Cong Mu, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe
Our hierarchical approach improves upon regular deep neural networks in learning with label noise.
no code implementations • 25 Feb 2022 • Guodong Chen, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe
We consider the problem of extracting features from passive, multi-channel electroencephalogram (EEG) devices for downstream inference tasks related to high-level mental states such as stress and cognitive load.
no code implementations • 19 Jan 2022 • Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan, Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
We conjecture that certain sequences of tasks are not retrospectively learnable (in which the data distribution is fixed), but are prospectively learnable (in which distributions may be dynamic), suggesting that prospective learning is more difficult in kind than retrospective learning.
1 code implementation • 1 Nov 2021 • Wenqi Cui, Weiwei Yang, Baosen Zhang
System topology and fault information are encoded by taking a multi-dimensional Fourier transform, allowing us to leverage the fact that the trajectories are sparse both in time and spatial frequencies.
no code implementations • 23 Jun 2021 • Hayden S. Helm, Marah Abdin, Benjamin D. Pedigo, Shweti Mahajan, Vince Lyzinski, Youngser Park, Amitabh Basu, Piali~Choudhury, Christopher M. White, Weiwei Yang, Carey E. Priebe
In modern ranking problems, different and disparate representations of the items to be ranked are often available.
no code implementations • 16 Mar 2021 • Vivek Kurien George, Vikash Morar, Weiwei Yang, Jonathan Larson, Bryan Tower, Shweti Mahajan, Arkin Gupta, Christopher White, Gabriel A. Silva
The success of state-of-the-art machine learning is essentially all based on different variations of gradient descent algorithms that minimize some version of a cost or loss function.
no code implementations • 20 Feb 2021 • Hayden S. Helm, Weiwei Yang, Sujeeth Bharadwaj, Kate Lytvynets, Oriana Riva, Christopher White, Ali Geisa, Carey E. Priebe
In applications where categorical labels follow a natural hierarchy, classification methods that exploit the label structure often outperform those that do not.
no code implementations • 12 Nov 2020 • Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Weiwei Yang, Christoper M. White, Ali Geisa, Joshua T. Vogelstein, Carey E. Priebe
Herein we define a measure of similarity between classification distributions that is both principled from the perspective of statistical pattern recognition and useful from the perspective of machine learning practitioners.
1 code implementation • 23 Aug 2020 • Guodong Chen, Jesús Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
We examine two related, complementary inference tasks: the detection of anomalous graphs within a time series, and the detection of temporally anomalous vertices.
Methodology
1 code implementation • 15 Jun 2020 • Yize Chen, Weiwei Yang, Baosen Zhang
In this work, we focus on the problem of load forecasting.
2 code implementations • 20 May 2020 • Hayden S. Helm, Amitabh Basu, Avanti Athreya, Youngser Park, Joshua T. Vogelstein, Carey E. Priebe, Michael Winding, Marta Zlatic, Albert Cardona, Patrick Bourke, Jonathan Larson, Marah Abdin, Piali Choudhury, Weiwei Yang, Christopher W. White
Learning to rank -- producing a ranked list of items specific to a query and with respect to a set of supervisory items -- is a problem of general interest.
1 code implementation • 27 Apr 2020 • Joshua T. Vogelstein, Jayanta Dey, Hayden S. Helm, Will LeVine, Ronak D. Mehta, Ali Geisa, Haoyin Xu, Gido M. van de Ven, Emily Chang, Chenyu Gao, Weiwei Yang, Bryan Tower, Jonathan Larson, Christopher M. White, Carey E. Priebe
But striving to avoid forgetting sets the goal unnecessarily low: the goal of lifelong learning, whether biological or artificial, should be to improve performance on all tasks (including past and future) with any new data.
no code implementations • IJCNLP 2019 • Weiwei Yang, Jordan Boyd-Graber, Philip Resnik
Multilingual topic models (MTMs) learn topics on documents in multiple languages.
no code implementations • EMNLP 2017 • Weiwei Yang, Jordan Boyd-Graber, Philip Resnik
Models work best when they are optimized taking into account the evaluation criteria that people care about.