Search Results for author: Hai Zhu

Found 10 papers, 2 papers with code

Query-LIFE: Query-aware Language Image Fusion Embedding for E-Commerce Relevance

no code implementations26 Nov 2023 Hai Zhu, Yuankai Guo, Ronggang Dou, Kai Liu

Query-LIFE utilizes a query-based multimodal fusion to effectively incorporate the image and title based on the product types.

Contrastive Learning

BeamAttack: Generating High-quality Textual Adversarial Examples through Beam Search and Mixed Semantic Spaces

no code implementations9 Mar 2023 Hai Zhu, Qingyang Zhao, Yuren Wu

These adversarial examples are imperceptible to human readers but can mislead models to make the wrong predictions.

Robust Diversified Graph Contrastive Network for Incomplete Multi-view Clustering

1 code implementation ACM International Conference on Multimedia 2022 Zhe Xue, Junping Du, Hai Zhu, Zhongchao Guan, Yunfei Long, Yu Zang, Meiyu Liang

To address these issues, we propose a Robust Diversified Graph Contrastive Network (RDGC) for incomplete multi-view clustering, which integrates multi-view representation learning and diversified graph contrastive regularization into a unified framework.

Clustering Contrastive Learning +2

Pitch Preservation In Singing Voice Synthesis

no code implementations11 Oct 2021 Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang

For the phoneme encoder, based on the analysis that same phonemes corresponding to varying pitches can produce similar pronunciations, this encoder is followed by an adversarially trained pitch classifier to enforce the identical phonemes with different pitches mapping into the same phoneme feature space.

Singing Voice Synthesis

Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments

no code implementations10 Feb 2021 Hai Zhu, Francisco Martinez Claramunt, Bruno Brito, Javier Alonso-Mora

In this paper, we introduce a novel trajectory prediction model based on recurrent neural networks (RNN) that can learn multi-robot motion behaviors from demonstrated trajectories generated using a centralized sequential planner.

Collision Avoidance Model Predictive Control +2

Edge Computing Assisted Autonomous Flight for UAV: Synergies between Vision and Communications

no code implementations10 Dec 2020 Quan Chen, Hai Zhu, Lei Yang, Xiaoqian Chen, Sofie Pollin, Evgenii Vinogradov

By proposing a framework of Edge Computing Assisted Autonomous Flight (ECAAF), we illustrate that vision and communications can interact with and assist each other with the aid of edge computing and offloading, and further speed up the UAV mission completion.

Edge-computing Trajectory Planning Networking and Internet Architecture Robotics Systems and Control Systems and Control

With Whom to Communicate: Learning Efficient Communication for Multi-Robot Collision Avoidance

no code implementations25 Sep 2020 Álvaro Serra-Gómez, Bruno Brito, Hai Zhu, Jen Jen Chung, Javier Alonso-Mora

Decentralized multi-robot systems typically perform coordinated motion planning by constantly broadcasting their intentions as a means to cope with the lack of a central system coordinating the efforts of all robots.

Collision Avoidance Motion Planning

Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

no code implementations21 Mar 2019 Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei zhang, Abraham Bernstein, Huajun Chen

We also evaluate the efficiency of rule learning and quality of rules from IterE compared with AMIE+, showing that IterE is capable of generating high quality rules more efficiently.

Entity Embeddings Knowledge Graphs +1

Label-Free Distant Supervision for Relation Extraction via Knowledge Graph Embedding

no code implementations EMNLP 2018 Guanying Wang, Wen Zhang, Ruoxu Wang, Yalin Zhou, Xi Chen, Wei zhang, Hai Zhu, Huajun Chen

This paper proposes a label-free distant supervision method, which makes no use of the relation labels under this inadequate assumption, but only uses the prior knowledge derived from the KG to supervise the learning of the classifier directly and softly.

Knowledge Graph Embedding Relation +3

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