Search Results for author:
Found 8 papers, 2 papers with code
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding
Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks.
AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices
We report extensive experiments on diverse datasets, scenarios, and platforms and demonstrate the superiority of AdaEnlight compared with state-of-the-art low-light image and video enhancement solutions.
Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
In the abstract environment, complex dynamics such as physical manipulation are removed, making abstract trajectories easier to generate.
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
Although the solution based on Local Differential Privacy (LDP) addresses the above problems, it leads to the low accuracy of the trained model.
Soft Retargeting Network for Click Through Rate Prediction
In this paper, we focus on a new type of user interest, i. e., user retargeting interest.
Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction
Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction.
An AI-based Approach for Tracing Content Requirements in Financial Documents
Then, FITI uses a combination of rule-based and data-centric approaches, by leveraging information retrieval (IR) and machine learning (ML) techniques that analyze the words, sentences, and contexts related to an information type, to rank candidate sentences.
Deep Learning in Software Engineering
To answer these questions, we conduct a bibliography analysis on 98 research papers in SE that use deep learning techniques.
Software Engineering
