43 citations · 95 across the 6 of their papers we have counts for
6 papers
Cross-Language Binary-Source Code Matching with Intermediate Representations
Yi Gui, Yao Wan, Hongyu Zhang +5
Binary-source code matching plays an important role in many security and software engineering related tasks such as malware detection, reverse engineering and vulnerability assessm…
FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
Dezhong Yao, Wanning Pan, Michael J O'Neill +4
One underlying assumption of recent federated learning (FL) paradigms is that all local models usually share the same network architecture and size, which becomes impractical for d…
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations
Yu Song, Jianxun Lian, Shuai Sun +4
User interest exploration is an important and challenging topic in recommender systems, which alleviates the closed-loop effects between recommendation models and user-item interac…
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data
Dezhong Yao, Wanning Pan, Yutong Dai +5
Federated learning enables multiple clients to collaboratively learn a global model by periodically aggregating the clients' models without transferring the local data. However, du…
Multi-Task Representation Learning with Multi-View Graph Convolutional Networks
Hong Huang, Yu Song, Yao Wu +3
Link prediction and node classification are two important downstream tasks of network representation learning. Existing methods have achieved acceptable results but they perform th…
NaturalCC: A Toolkit to Naturalize the Source Code Corpus
Yao Wan, Yang He, Jian-Guo Zhang +5
We present NaturalCC, an efficient and extensible toolkit to bridge the gap between natural language and programming language, and facilitate the research on big code analysis. Usi…