200 citations · 1.6k across the 79 of their papers we have counts for
19 papers · 1 filter
Variance Reduced Local SGD with Lower Communication Complexity
Xianfeng Liang, Shuheng Shen, Jingchang Liu +3
To accelerate the training of machine learning models, distributed stochastic gradient descent (SGD) and its variants have been widely adopted, which apply multiple workers in para…
Estimating Early Fundraising Performance of Innovations via Graph-based Market Environment Model
Likang Wu, Zhi Li, Hongke Zhao +3
Well begun is half done. In the crowdfunding market, the early fundraising performance of the project is a concerned issue for both creators and platforms. However, estimating the…
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
Junliang Guo, Xu Tan, Linli Xu +3
Non-autoregressive translation (NAT) models remove the dependence on previous target tokens and generate all target tokens in parallel, resulting in significant inference speedup b…
A Machine Learning-enhanced Robust P-Phase Picker for Real-time Seismic Monitoring
Dazhong Shen, Qi Zhang, Tong Xu +7
Identifying the arrival times of seismic P-phases plays a significant role in real-time seismic monitoring, which provides critical guidance for emergency response activities. Whil…
Long-term Joint Scheduling for Urban Traffic
Xianfeng Liang, Likang Wu, Joya Chen +7
Recently, the traffic congestion in modern cities has become a growing worry for the residents. As presented in Baidu traffic report, the commuting stress index has reached surpris…
Balanced One-shot Neural Architecture Optimization
Renqian Luo, Tao Qin, Enhong Chen
The ability to rank candidate architectures is the key to the performance of neural architecture search~(NAS). One-shot NAS is proposed to reduce the expense but shows inferior per…
Is Heuristic Sampling Necessary in Training Deep Object Detectors?
Joya Chen, Dong Liu, Tong Xu +3
To train accurate deep object detectors under the extreme foreground-background imbalance, heuristic sampling methods are always necessary, which either re-sample a subset of all t…
Residual Objectness for Imbalance Reduction
Joya Chen, Dong Liu, Bin Luo +3
For a long time, object detectors have suffered from extreme imbalance between foregrounds and backgrounds. While several sampling/reweighting schemes have been explored to allevia…
STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control
Yanan Wang, Tong Xu, Xin Niu +3
The development of intelligent traffic light control systems is essential for smart transportation management. While some efforts have been made to optimize the use of individual t…
Neural Cognitive Diagnosis for Intelligent Education Systems
Fei Wang, Qi Liu, Enhong Chen +5
Cognitive diagnosis is a fundamental issue in intelligent education, which aims to discover the proficiency level of students on specific knowledge concepts. Existing approaches us…
Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems
Binbin Jin, Enhong Chen, Hongke Zhao +4
In the area of community question answering (CQA), answer selection and answer ranking are two tasks which are applied to help users quickly access valuable answers. Existing solut…
Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach
Min Hou, Le Wu, Enhong Chen +3
In fashion recommender systems, each product usually consists of multiple semantic attributes (e.g., sleeves, collar, etc). When making cloth decisions, people usually show prefere…
EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
Qi Liu, Zhenya Huang, Yu Yin +4
For offering proactive services to students in intelligent education, one of the fundamental tasks is predicting their performance (e.g., scores) on future exercises, where it is n…
Chinese Embedding via Stroke and Glyph Information: A Dual-channel View
Hanqing Tao, Shiwei Tong, Tong Xu +2
Recent studies have consistently given positive hints that morphology is helpful in enriching word embeddings. In this paper, we argue that Chinese word embeddings can be substanti…
Budgeted Policy Learning for Task-Oriented Dialogue Systems
Zhirui Zhang, Xiujun Li, Jianfeng Gao +1
This paper presents a new approach that extends Deep Dyna-Q (DDQ) by incorporating a Budget-Conscious Scheduling (BCS) to best utilize a fixed, small amount of user interactions (b…
MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network
Hao Wang, Tong Xu, Qi Liu +5
Recently, the Network Representation Learning (NRL) techniques, which represent graph structure via low-dimension vectors to support social-oriented application, have attracted wid…
Transcribing Content from Structural Images with Spotlight Mechanism
Yu Yin, Zhenya Huang, Enhong Chen +4
Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal str…
QuesNet: A Unified Representation for Heterogeneous Test Questions
Yu Yin, Qi Liu, Zhenya Huang +4
Understanding learning materials (e.g. test questions) is a crucial issue in online learning systems, which can promote many applications in education domain. Unfortunately, many s…
Exploiting Cognitive Structure for Adaptive Learning
Qi Liu, Shiwei Tong, Chuanren Liu +4
Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to…