193 citations · 1.5k across the 86 of their papers we have counts for
10 papers · 1 filter
Universal Model in Online Customer Service
Shu-Ting Pi, Cheng-Ping Hsieh, Qun Liu +1
Building machine learning models can be a time-consuming process that often takes several months to implement in typical business scenarios. To ensure consistent model performance…
Teacher-Student Learning on Complexity in Intelligent Routing
Shu-Ting Pi, Michael Yang, Yuying Zhu +1
Customer service is often the most time-consuming aspect for e-commerce websites, with each contact typically taking 10-15 minutes. Effectively routing customers to appropriate age…
Contact Complexity in Customer Service
Shu-Ting Pi, Michael Yang, Qun Liu
Customers who reach out for customer service support may face a range of issues that vary in complexity. Routing high-complexity contacts to junior agents can lead to multiple tran…
Improved OOD Generalization via Adversarial Training and Pre-training
Mingyang Yi, Lu Hou, Jiacheng Sun +4
Recently, learning a model that generalizes well on out-of-distribution (OOD) data has attracted great attention in the machine learning community. In this paper, after defining OO…
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
Mingyang Yi, Lu Hou, Lifeng Shang +3
Data augmentation is an effective technique to improve the generalization of deep neural networks. However, previous data augmentation methods usually treat the augmented samples e…
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching
Qun Liu, Matthew Shreve, Raja Bala
Although data is abundant, data labeling is expensive. Semi-supervised learning methods combine a few labeled samples with a large corpus of unlabeled data to effectively train mod…
Deep Learning-Based Feature-Aware Data Modeling for Complex Physics Simulations
Qun Liu, Subhashis Hazarika, John M. Patchett +2
Data modeling and reduction for in situ is important. Feature-driven methods for in situ data analysis and reduction are a priority for future exascale machines as there are curren…
Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks
Qun Liu, Lihua Fu, Meng Zhang
Reconstruction of seismic data with missing traces is a long-standing issue in seismic data processing. In recent years, rank reduction operations are being commonly utilized to ov…
Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation
Qun Liu, Supratik Mukhopadhyay, Yimin Zhu +3
Route Choice Models predict the route choices of travelers traversing an urban area. Most of the route choice models link route characteristics of alternative routes to those chose…
SafeRNet: Safe Transportation Routing in the era of Internet of Vehicles and Mobile Crowd Sensing
Qun Liu, Suman Kumar, Vijay Mago
World wide road traffic fatality and accident rates are high, and this is true even in technologically advanced countries like the USA. Despite the advances in Intelligent Transpor…