297 citations · 958 across the 50 of their papers we have counts for
13 papers · 1 filter
Generative Interventions for Causal Learning
Chengzhi Mao, Augustine Cha, Amogh Gupta +3
We introduce a framework for learning robust visual representations that generalize to new viewpoints, backgrounds, and scene contexts. Discriminative models often learn naturally…
Keyword-Guided Neural Conversational Model
Peixiang Zhong, Yong Liu, Hao Wang +1
We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smooth…
Learning causal representations for robust domain adaptation
Shuai Yang, Kui Yu, Fuyuan Cao +3
Domain adaptation solves the learning problem in a target domain by leveraging the knowledge in a relevant source domain. While remarkable advances have been made, almost all exist…
Neural Network Design: Learning from Neural Architecture Search
Bas van Stein, Hao Wang, Thomas Bäck
Neural Architecture Search (NAS) aims to optimize deep neural networks' architecture for better accuracy or smaller computational cost and has recently gained more research interes…
COSEA: Convolutional Code Search with Layer-wise Attention
Hao Wang, Jia Zhang, Yingce Xia +3
Semantic code search, which aims to retrieve code snippets relevant to a given natural language query, has attracted many research efforts with the purpose of accelerating software…
PP-OCR: A Practical Ultra Lightweight OCR System
Yuning Du, Chenxia Li, Ruoyu Guo +8
The Optical Character Recognition (OCR) systems have been widely used in various of application scenarios, such as office automation (OA) systems, factory automations, online educa…
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition
Hengguan Huang, Fuzhao Xue, Hao Wang +1
Lying at the core of human intelligence, relational thinking is characterized by initially relying on innumerable unconscious percepts pertaining to relations between new sensory s…
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction
Zhongkai Hao, Chengqiang Lu, Zheyuan Hu +5
Molecular property prediction (e.g., energy) is an essential problem in chemistry and biology. Unfortunately, many supervised learning methods usually suffer from the problem of sc…
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
Hao Wang, Diederick Vermetten, Furong Ye +2
Benchmarking and performance analysis play an important role in understanding the behaviour of iterative optimization heuristics (IOHs) such as local search algorithms, genetic and…
A Modular Hybridization of Particle Swarm Optimization and Differential Evolution
Rick Boks, Hao Wang, Thomas Bäck
In swarm intelligence, Particle Swarm Optimization (PSO) and Differential Evolution (DE) have been successfully applied in many optimization tasks, and a large number of variants,…
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
Diederick Vermetten, Hao Wang, Carola Doerr +1
One of the most challenging problems in evolutionary computation is to select from its family of diverse solvers one that performs well on a given problem. This algorithm selection…
Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Ruiyang Ren, Zhaoyang Liu, Yaliang Li +4
Recently, deep learning has made significant progress in the task of sequential recommendation. Existing neural sequential recommenders typically adopt a generative way trained wit…
Secret Sharing based Secure Regressions with Applications
Chaochao Chen, Liang Li, Wenjing Fang +6
Nowadays, the utilization of the ever expanding amount of data has made a huge impact on web technologies while also causing various types of security concerns. On one hand, potent…