research
∙
03/19/2021
Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond
Deep neural networks have been well-known for their superb performance i...
share
research
∙
03/08/2021
Model Complexity of Deep Learning: A Survey
Model complexity is a fundamental problem in deep learning. In this pape...
research
∙
02/15/2021
REST: Relational Event-driven Stock Trend Forecasting
Stock trend forecasting, aiming at predicting the stock future trends, i...
research
∙
01/22/2021
Applications of artificial intelligence in drug development using real-world data
The US Food and Drug Administration (FDA) has been actively promoting th...
research
∙
12/24/2020
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations
Multi-agent reinforcement learning (MARL) has been increasingly explored...
research
∙
12/11/2020
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Stock trend forecasting has become a popular research direction that att...
research
∙
10/19/2020
COSEA: Convolutional Code Search with Layer-wise Attention
Semantic code search, which aims to retrieve code snippets relevant to a...
research
∙
10/17/2020
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler
Imbalanced learning (IL), i.e., learning unbiased models from class-imba...
research
∙
09/22/2020
Qlib: An AI-oriented Quantitative Investment Platform
Quantitative investment aims to maximize the return and minimize the ris...
research
∙
07/10/2020
Learn to Use Future Information in Simultaneous Translation
Simultaneous neural machine translation (briefly, NMT) has attracted muc...
research
∙
07/09/2020
Learning to Teach with Deep Interactions
Machine teaching uses a meta/teacher model to guide the training of a st...
research
∙
07/05/2020
When text simplification is not enough: could a graph-based visualization facilitate consumers' comprehension of dietary supplement information?
Dietary supplements (DSs) are popular but not always safe. Consumers usu...
research
∙
06/16/2020
Measuring Model Complexity of Neural Networks with Curve Activation Functions
It is fundamental to measure model complexity of deep neural networks. T...
research
∙
06/10/2020
MC-BERT: Efficient Language Pre-Training via a Meta Controller
Pre-trained contextual representations (e.g., BERT) have become the foun...
research
∙
05/12/2020
Invertible Image Rescaling
High-resolution digital images are usually downscaled to fit various dis...
research
∙
11/05/2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Distributional Reinforcement Learning (RL) differs from traditional RL i...
research
∙
10/01/2019
Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods
Cardiotoxicity related to cancer therapies has become a serious issue, d...
research
∙
09/08/2019
Self-paced Ensemble for Highly Imbalanced Massive Data Classification
Many real-world applications reveal difficulties in learning classifiers...
research
∙
09/08/2019
Training Effective Ensemble on Imbalanced Data by Self-paced Harmonizing Classification Hardness
Many real-world applications reveal difficulties in learning classifiers...
research
∙
08/25/2019
LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm
Multiclass decomposition splits a multiclass classification problem into...
research
∙
07/16/2019
Light Multi-segment Activation for Model Compression
Model compression has become necessary when applying neural networks (NN...
research
∙
07/06/2019
Mining Twitter to Assess the Determinants of Health Behavior towards Human Papillomavirus Vaccination in the United States
Objectives To test the feasibility of using Twitter data to assess deter...
research
∙
06/24/2019
Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network: A Colorectal Cancer Clinical Trial
Existing trials had not taken enough consideration of their population r...
research
∙
06/07/2019
Analyzing Social Media Data to Understand Consumers' Information Needs on Dietary Supplements
Despite the high consumption of dietary supplements (DS), there are not ...
research
∙
05/22/2019
Understanding Perceptions and Attitudes in Breast Cancer Discussions on Twitter
Among American women, the rate of breast cancer is only second to lung c...
research
∙
04/28/2019
Enhancing Prediction Models for One-Year Mortality in Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome
Predicting the risk of mortality for patients with acute myocardial infa...
research
∙
04/16/2019
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction
Most existing event extraction (EE) methods merely extract event argumen...
research
∙
03/02/2019
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network
Resource balancing within complex transportation networks is one of the ...
research
∙
12/12/2018
Building Computational Models to Predict One-Year Mortality in ICU Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome
Heart disease remains the leading cause of death in the United States. C...
research
∙
02/20/2018
A survey on trajectory clustering analysis
This paper comprehensively surveys the development of trajectory cluster...
research
∙
02/01/2018
Automatic Safety Helmet Wearing Detection
Surveillance is essential for the safety of power substation. The detect...
research
∙
07/03/2017
Dual Supervised Learning
Many supervised learning tasks are emerged in dual forms, e.g., English-...
research
∙
02/28/2017
Learning What Data to Learn
Machine learning is essentially the sciences of playing with data. An ad...
research
∙
06/02/2016
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks
Parallelization framework has become a necessity to speed up the trainin...
research
∙
04/23/2014
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks
Click prediction is one of the fundamental problems in sponsored search....
research
∙
03/15/2012
