29 citations · 67 across the 7 of their papers we have counts for
7 papers
A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Neural network pruning techniques reduce the number of parameters without compromising predicting ability of a network. Many algorithms have been developed for pruning both over-pa…
Personalized Visualization Recommendation
Xin Qian, Ryan A. Rossi, Fan Du +5
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These…
The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent
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. We study SGD dynamics under linea…
Clustering Degree-Corrected Stochastic Block Model with Outliers
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…
Dynamic Cell Structure via Recursive-Recurrent Neural Networks
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. We propose a novel algorithm that ca…
Multimodal Machine Translation with Reinforcement Learning
Xin Qian, Ziyi Zhong, Jieli Zhou
Multimodal machine translation is one of the applications that integrates computer vision and language processing. It is a unique task given that in the field of machine translatio…
Financial Series Prediction: Comparison Between Precision of Time Series Models and Machine Learning Methods
Xin-Yao Qian
Precise financial series predicting has long been a difficult problem because of unstableness and many noises within the series. Although Traditional time series models like ARIMA…