1 code implementation • 16 Oct 2018 • Yanfu Zhang, Wenshan Wang, Rogerio Bonatti, Daniel Maturana, Sebastian Scherer
The first-stage network learns feature representations of the environment using low-level LiDAR statistics and the second-stage network combines those learned features with kinematics data.
1 code implementation • 17 Feb 2021 • Bin Gu, Guodong Liu, yanfu Zhang, Xiang Geng, Heng Huang
Modern machine learning algorithms usually involve tuning multiple (from one to thousands) hyperparameters which play a pivotal role in terms of model generalizability.
1 code implementation • 21 Mar 2024 • Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, yanfu Zhang, Xiaoqian Wang, Heng Huang
Current techniques for deep neural network (DNN) pruning often involve intricate multi-step processes that require domain-specific expertise, making their widespread adoption challenging.
1 code implementation • 4 Apr 2024 • Tiantian Geng, Teng Wang, yanfu Zhang, Jinming Duan, Weili Guan, Feng Zheng
Video localization tasks aim to temporally locate specific instances in videos, including temporal action localization (TAL), sound event detection (SED) and audio-visual event localization (AVEL).
no code implementations • 28 Aug 2018 • Rogerio Bonatti, yanfu Zhang, Sanjiban Choudhury, Wenshan Wang, Sebastian Scherer
Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios.
no code implementations • 26 Mar 2019 • Wenshan Wang, Aayush Ahuja, Yanfu Zhang, Rogerio Bonatti, Sebastian Scherer
We show that by leveraging unlabeled sequences, the amount of labeled data required can be significantly reduced.
no code implementations • ICML 2020 • lei luo, yanfu Zhang, Heng Huang
Nonnegative Matrix Factorization (NMF) has become an increasingly important research topic in machine learning.
no code implementations • ICCV 2021 • yanfu Zhang, Shangqian Gao, Heng Huang
In this paper, we focus on the discrimination-aware compression of Convolutional Neural Networks (CNNs).
no code implementations • ICCV 2021 • yanfu Zhang, Lei Luo, Wenhan Xian, Heng Huang
However, pair-wise methods involve expensive training costs, while proxy-based methods are less accurate in characterizing the relationships between data points.
no code implementations • NeurIPS 2021 • Wenhan Xian, Feihu Huang, yanfu Zhang, Heng Huang
We prove that our DM-HSGD algorithm achieves stochastic first-order oracle (SFO) complexity of $O(\kappa^3 \epsilon^{-3})$ for decentralized stochastic nonconvex-strongly-concave problem to search an $\epsilon$-stationary point, which improves the exiting best theoretical results.
no code implementations • ICCV 2023 • Shangqian Gao, Zeyu Zhang, yanfu Zhang, Feihu Huang, Heng Huang
To mitigate this gap, we first learn a target sub-network during the model training process, and then we use this sub-network to guide the learning of model weights through partial regularization.