no code implementations • 2 May 2024 • Simon Vary, Pierre Ablin, Bin Gao, P. -A. Absil
Optimization over the set of matrices that satisfy $X^\top B X = I_p$, referred to as the generalized Stiefel manifold, appears in many applications involving sampled covariance matrices such as canonical correlation analysis (CCA), independent component analysis (ICA), and the generalized eigenvalue problem (GEVP).
1 code implementation • 4 Apr 2024 • Bin Gao, Yan Yang, Ya-xiang Yuan
As a result, the constructed subspace is able to dynamically and incrementally approximate the Hessian inverse vector product with less effort and thus leads to a favorable estimate of the hyper-gradient.
no code implementations • 23 Mar 2024 • Bin Gao, Zhuomin He, Puru Sharma, Qingxuan Kang, Djordje Jevdjic, Junbo Deng, Xingkun Yang, Zhou Yu, Pengfei Zuo
Interacting with humans through multi-turn conversations is a fundamental feature of large language models (LLMs).
1 code implementation • 16 Jan 2024 • Xu Yan, Haiming Zhang, Yingjie Cai, Jingming Guo, Weichao Qiu, Bin Gao, Kaiqiang Zhou, Yue Zhao, Huan Jin, Jiantao Gao, Zhen Li, Lihui Jiang, Wei zhang, Hongbo Zhang, Dengxin Dai, Bingbing Liu
The rise of large foundation models, trained on extensive datasets, is revolutionizing the field of AI.
no code implementations • 17 Nov 2023 • Bozhen Hu, Bin Gao, Cheng Tan, Tongle Wu, Stan Z. Li
Defect detection plays a crucial role in infrared non-destructive testing systems, offering non-contact, safe, and efficient inspection capabilities.
no code implementations • 29 Mar 2023 • Pierre Ablin, Simon Vary, Bin Gao, P. -A. Absil
Finally, our experiments demonstrate the promise of our approach to an array of machine-learning problems that involve orthogonality constraints.
1 code implementation • CVPR 2022 • Jiashuo Fan, Bin Gao, Huan Jin, Lihui Jiang
Deep neural networks (DNNs) have witnessed great successes in semantic segmentation, which requires a large number of labeled data for training.
no code implementations • 17 May 2022 • Yu Wang, Binbin Zhu, Lingsi Kong, Jianlin Wang, Bin Gao, Jianhua Wang, Dingcheng Tian, YuDong Yao
With the help of deep learning methods, the automatic identification or segmentation of nerves can be realized, assisting doctors in completing nerve block anesthesia accurately and efficiently.
1 code implementation • 30 Nov 2021 • Guohao Ying, Xin He, Bin Gao, Bo Han, Xiaowen Chu
Some recent works try to search both generator (G) and discriminator (D), but they suffer from the instability of GAN training.
Ranked #10 on Image Generation on STL-10
no code implementations • 17 Aug 2021 • Weier Wan, Rajkumar Kubendran, Clemens Schaefer, S. Burc Eryilmaz, Wenqiang Zhang, Dabin Wu, Stephen Deiss, Priyanka Raina, He Qian, Bin Gao, Siddharth Joshi, Huaqiang Wu, H. -S. Philip Wong, Gert Cauwenberghs
Realizing today's cloud-level artificial intelligence functionalities directly on devices distributed at the edge of the internet calls for edge hardware capable of processing multiple modalities of sensory data (e. g. video, audio) at unprecedented energy-efficiency.
1 code implementation • 26 Jan 2021 • Shuyu Dong, Bin Gao, Yu Guan, François Glineur
We propose new Riemannian preconditioned algorithms for low-rank tensor completion via the polyadic decomposition of a tensor.
2 code implementations • 7 Jan 2021 • Nguyen Thanh Son, P. -A. Absil, Bin Gao, Tatjana Stykel
We address the problem of computing the smallest symplectic eigenvalues and the corresponding eigenvectors of symmetric positive-definite matrices in the sense of Williamson's theorem.
Optimization and Control Spectral Theory 15A15, 15A18, 70G45
no code implementations • ICCV 2021 • Yanning Zhou, Hang Xu, Wei zhang, Bin Gao, Pheng-Ann Heng
The semi-supervised semantic segmentation methods utilize the unlabeled data to increase the feature discriminative ability to alleviate the burden of the annotated data.
1 code implementation • 28 Aug 2020 • Yu Guan, Shuyu Dong, Bin Gao, P. -A. Absil, François Glineur
The usage of graph regularization entails benefits in the learning accuracy of LRTC, but at the same time, induces coupling graph Laplacian terms that hinder the optimization of the tensor completion model.
2 code implementations • 26 Jun 2020 • Bin Gao, Nguyen Thanh Son, P. -A. Absil, Tatjana Stykel
The symplectic Stiefel manifold, denoted by $\mathrm{Sp}(2p, 2n)$, is the set of linear symplectic maps between the standard symplectic spaces $\mathbb{R}^{2p}$ and $\mathbb{R}^{2n}$.
Optimization and Control Dynamical Systems
no code implementations • ICLR 2020 • Qingtian Zhang, Bin Gao, Huaqiang Wu
In this work, we proposed the uncertainty adaptation training scheme (UATS) that tells the uncertainty to the neural network in the training process.
1 code implementation • 9 Oct 2018 • Bin Gao, Xin Liu, Ya-xiang Yuan
Numerical experiments in serial illustrate that the novel updating rule for the Lagrangian multipliers significantly accelerates the convergence of PLAM and makes it comparable with the existent feasible solvers for optimization problems with orthogonality constraints, and the performance of PCAL does not highly rely on the choice of the penalty parameter.
Optimization and Control 15A18, 65F15, 65K05, 90C06
no code implementations • 7 Apr 2016 • Fei Tian, Bin Gao, Di He, Tie-Yan Liu
We propose Sentence Level Recurrent Topic Model (SLRTM), a new topic model that assumes the generation of each word within a sentence to depend on both the topic of the sentence and the whole history of its preceding words in the sentence.
no code implementations • 29 May 2015 • Huazheng Wang, Fei Tian, Bin Gao, Jiang Bian, Tie-Yan Liu
Second, we obtain distributed representations of words and relations by leveraging a novel word embedding method that considers the multi-sense nature of words and the relational knowledge among words (or their senses) contained in dictionaries.
no code implementations • 19 May 2015 • Fei Tian, Bin Gao, Enhong Chen, Tie-Yan Liu
Although these works have achieved certain success, they have neglected some important facts about knowledge graphs: (i) many relationships in knowledge graphs are \emph{many-to-one}, \emph{one-to-many} or even \emph{many-to-many}, rather than simply \emph{one-to-one}; (ii) most head entities and tail entities in knowledge graphs come from very different semantic spaces.
no code implementations • 7 Jul 2014 • Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Tie-Yan Liu
In particular, we introduce a novel neural network architecture called KNET that leverages both contextual information and morphological word similarity built based on morphological knowledge to learn word embeddings.
no code implementations • 7 Jul 2014 • Bin Gao, Jiang Bian, Tie-Yan Liu
In this paper, we describe the details of the WordRep collection and show how to use it in different types of machine learning research related to word embedding.