1 code implementation • 20 Dec 2023 • Hen Emuna, Nadav Borenstein, Xin Qian, Hyeonsu Kang, Joel Chan, Aniket Kittur, Dafna Shahaf
We release data and code; we view BARcode as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.
no code implementations • 20 May 2021 • Xin Qian, Diego Klabjan
Neural network pruning techniques reduce the number of parameters without compromising predicting ability of a network.
no code implementations • 23 Mar 2021 • Chen Zhao, Chenyan Xiong, Xin Qian, Jordan Boyd-Graber
DELFT's advantage comes from both the high coverage of its free-text knowledge graph-more than double that of dbpedia relations-and the novel graph neural network which reasons on the rich but noisy free-text evidence.
no code implementations • 10 Mar 2021 • Xin Qian, Jungwoo Shin, Yaodong Tu, James Han Zhang, Gang Chen
This work also presents a comprehensive model with a coupled analysis of mass transfer and reaction kinetics in a porous electrode that can accurately capture the flow rate dependence of power density and energy conversion efficiency.
Applied Physics Classical Physics
no code implementations • 12 Feb 2021 • Xin Qian, Ryan A. Rossi, Fan Du, Sungchul Kim, Eunyee Koh, Sana Malik, Tak Yeon Lee, Nesreen K. Ahmed
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback.
no code implementations • 1 Jan 2021 • Xin Qian, Diego Klabjan
We study mini-batch stochastic gradient descent (SGD) dynamics under linear regression and deep linear networks by focusing on the variance of the gradients only given the initial weights and mini-batch size, which is the first study of this nature.
no code implementations • 25 Sep 2020 • Xin Qian, Ryan A. Rossi, Fan Du, Sungchul Kim, Eunyee Koh, Sana Malik, Tak Yeon Lee, Joel Chan
Finally, we observed a strong preference by the human experts in our user study towards the visualizations recommended by our ML-based system as opposed to the rule-based system (5. 92 from a 7-point Likert scale compared to only 3. 45).
no code implementations • 27 Apr 2020 • Xin Qian, Diego Klabjan
The mini-batch stochastic gradient descent (SGD) algorithm is widely used in training machine learning models, in particular deep learning models.
no code implementations • 7 Jun 2019 • Xin Qian, Yudong Chen, Andreea Minca
For the degree corrected stochastic block model in the presence of arbitrary or even adversarial outliers, we develop a convex-optimization-based clustering algorithm that includes a penalization term depending on the positive deviation of a node from the expected number of edges to other inliers.
no code implementations • 25 May 2019 • Xin Qian, Matthew Kennedy, Diego Klabjan
In a recurrent setting, conventional approaches to neural architecture search find and fix a general model for all data samples and time steps.
1 code implementation • 17 Mar 2019 • Xiangpan Ji, Wenqiang Gu, Xin Qian, Hanyu Wei, Chao Zhang
We describe an approximation to the widely-used Poisson-likelihood chi-square using a linear combination of Neyman's and Pearson's chi-squares, namely "combined Neyman-Pearson chi-square" ($\chi^2_{\mathrm{CNP}}$).
Data Analysis, Statistics and Probability High Energy Physics - Experiment Nuclear Experiment
no code implementations • 7 May 2018 • Xin Qian, Ziyi Zhong, Jieli Zhou
We present a novel algorithm based on the Advantage Actor-Critic (A2C) algorithm that specifically cater to the multimodal machine translation task of the EMNLP 2018 Third Conference on Machine Translation (WMT18).
1 code implementation • 4 Feb 2016 • Yichen Li, Craig Thorn, Wei Tang, Jyoti Joshi, Xin Qian, Milind Diwan, Steve Kettell, William Morse, Triveni Rao, James Stewart, Thomas Tsang, Lige Zhang
We describe the design of a 20-liter test stand constructed to study fundamental properties of liquid argon (LAr).
Instrumentation and Detectors High Energy Physics - Experiment