Feature engineering ≈ Feature engineering
View article
Wide & Deep Learning for Recommender Systems Open
Generalized linear models with nonlinear feature transformations are widely used for large-scale regression and classification problems with sparse inputs. Memorization of feature interactions through a wide set of cross-product feature tr…
View article
Deep learning for healthcare: review, opportunities and challenges Open
Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, includi…
View article
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Open
Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems. Despite great progress, existing methods seem to have a strong bias towards low- or high-order interactions, or requir…
View article
Review of Deep Learning Algorithms and Architectures Open
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pai…
View article
Deep & Cross Network for Ad Click Predictions Open
Feature engineering has been the key to the success of many prediction models. However, the process is nontrivial and often requires manual feature engineering or exhaustive searching. DNNs are able to automatically learn feature interacti…
View article
xDeepFM Open
Combinatorial features are essential for the success of many commercial models. Manually crafting these features usually comes with high cost due to the variety, volume and velocity of raw data in web-scale systems. Factorization based mod…
View article
Recurrent Attention Network on Memory for Aspect Sentiment Analysis Open
We propose a novel framework based on neural networks to identify the sentiment of opinion targets in a comment/review. Our framework adopts multiple-attention mechanism to capture sentiment features separated by a long distance, so that i…
View article
Convolutional Networks on Graphs for Learning Molecular Fingerprints Open
We introduce a convolutional neural network that operates directly on graphs. These networks allow end-to-end learning of prediction pipelines whose inputs are graphs of arbitrary size and shape. The architecture we present generalizes sta…
View article
Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches † Open
Background: With the development of smart grids, accurate electric load forecasting has become increasingly important as it can help power companies in better load scheduling and reduce excessive electricity production. However, developing…
View article
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks Open
Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions. Despite effectiveness, FM can be hindered by its modelling of all feature int…
View article
Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things Open
A network traffic classifier (NTC) is an important part of current network monitoring systems, being its task to infer the network service that is currently used by a communication flow (e.g., HTTP and SIP). The detection is based on a num…
View article
Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning Open
Automatic and accurate estimation of disease severity is essential for food security, disease management, and yield loss prediction. Deep learning, the latest breakthrough in computer vision, is promising for fine-grained disease severity …
View article
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations Open
We present a simple and effective scheme for dependency parsing which is based on bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector representing the token in its sentential context, and feature vectors a…
View article
Enhancing deep learning sentiment analysis with ensemble techniques in social applications Open
Deep learning techniques for Sentiment Analysis have become very popular. They provide automatic feature extraction and both richer representation capabilities and better performance than traditional feature based techniques (i.e., surface…
View article
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Open
Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems. Despite great progress, existing methods seem to have a strong bias towards low- or high-order interactions, or requir…
View article
DeepInf Open
Social and information networking activities such as on Facebook, Twitter,\nWeChat, and Weibo have become an indispensable part of our everyday life, where\nwe can easily access friends' behaviors and are in turn influenced by them.\nConse…
View article
Robust Intelligent Malware Detection Using Deep Learning Open
Security breaches due to attacks by malicious software (malware) continue to escalate posing a major security concern in this digital age. With many computer users, corporations, and governments affected due to an exponential growth in mal…
View article
Multi-Scale Convolutional Neural Networks for Time Series Classification Open
Time series classification (TSC), the problem of predicting class labels of time series, has been around for decades within the community of data mining and machine learning, and found many important applications such as biomedical enginee…
View article
A Convolutional Approach for Misinformation Identification Open
The fast expanding of social media fuels the spreading of misinformation which disrupts people's normal lives. It is urgent to achieve goals of misinformation identification and early detection in social media. In dynamic and complicated s…
View article
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition Open
This paper describes a novel method called Deep Dynamic Neural Networks (DDNN) for multimodal gesture recognition. A semi-supervised hierarchical dynamic framework based on a Hidden Markov Model (HMM) is proposed for simultaneous gesture s…
View article
Scaling tree-based automated machine learning to biomedical big data with a feature set selector Open
Motivation Automated machine learning (AutoML) systems are helpful data science assistants designed to scan data for novel features, select appropriate supervised learning models and optimize their parameters. For this purpose, Tree-based …
View article
An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition Open
Motivation In biomedical research, chemical is an important class of entities, and chemical named entity recognition (NER) is an important task in the field of biomedical information extraction. However, most popular chemical NER methods a…
View article
The State of the Art of Data Science and Engineering in Structural Health Monitoring Open
Structural health monitoring (SHM) is a multi-discipline field that involves the automatic sensing of structural loads and response by means of a large number of sensors and instruments, followed by a diagnosis of the structural health bas…
View article
Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices Open
This Methods/Protocols article is intended for materials scientists interested in performing machine learning-centered research. Herein, we cover broad guidelines and best practices regarding the obtaining and treatment of data, feature en…
View article
Target-Dependent Sentiment Classification With BERT Open
Research on machine assisted text analysis follows the rapid development of digital media, and sentiment analysis is among the prevalent applications. Traditional sentiment analysis methods require complex feature engineering, and embeddin…
View article
Asm2Vec: Boosting Static Representation Robustness for Binary Clone Search against Code Obfuscation and Compiler Optimization Open
Reverse engineering is a manually intensive but necessary technique for understanding the inner workings of new malware, finding vulnerabilities in existing systems, and detecting patent infringements in released software. An assembly clon…
View article
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data Open
Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks. Such models are typically trained on free-form NL text, hence may not be suitable for tasks like seman…
View article
Deep learning with multimodal representation for pancancer prognosis prediction Open
Motivation Estimating the future course of patients with cancer lesions is invaluable to physicians; however, current clinical methods fail to effectively use the vast amount of multimodal data that is available for cancer patients. To tac…
View article
Machine learning based approaches for detecting COVID-19 using clinical text data Open
Technology advancements have a rapid effect on every field of life, be it medical field or any other field. Artificial intelligence has shown the promising results in health care through its decision making by analysing the data. COVID-19 …
View article
Deep Neural Solver for Math Word Problems Open
This paper presents a deep neural solver to automatically solve math word problems. In contrast to previous statistical learning approaches, we directly translate math word problems to equation templates using a recurrent neural network (R…