no code implementations • NAACL (maiworkshop) 2021 • Han Ding, Li Erran Li, Zhiting Hu, Yi Xu, Dilek Hakkani-Tur, Zheng Du, Belinda Zeng
Recent vision-language understanding approaches adopt a multi-modal transformer pre-training and finetuning paradigm.
no code implementations • NAACL (ACL) 2022 • Weiyi Lu, Sunny Rajagopalan, Priyanka Nigam, Jaspreet Singh, Xiaodi Sun, Yi Xu, Belinda Zeng, Trishul Chilimbi
However, one issue that often arises in MTL is the convergence speed between tasks varies due to differences in task difficulty, so it can be a challenge to simultaneously achieve the best performance on all tasks with a single model checkpoint.
no code implementations • ECCV 2020 • Lele Chen, Guofeng Cui, Celong Liu, Zhong Li, Ziyi Kou, Yi Xu, Chenliang Xu
Monocular 3D object detection is a challenging task due to unreliable depth, resulting in a distinct performance gap between monocular and LiDAR-based approaches.
no code implementations • 30 Apr 2024 • Shuqian Sheng, Yi Xu, Tianhang Zhang, Zanwei Shen, Luoyi Fu, Jiaxin Ding, Lei Zhou, Xinbing Wang, Chenghu Zhou
Automatic evaluation metrics for generated texts play an important role in the NLG field, especially with the rapid growth of LLMs.
no code implementations • 22 Apr 2024 • Rui She, Qiyu Kang, Sijie Wang, Wee Peng Tay, Kai Zhao, Yang song, Tianyu Geng, Yi Xu, Diego Navarro Navarro, Andreas Hartmannsgruber
Point cloud registration is a fundamental technique in 3-D computer vision with applications in graphics, autonomous driving, and robotics.
no code implementations • 12 Apr 2024 • Yang Yang, Hongpeng Pan, Qing-Yuan Jiang, Yi Xu, Jinghui Tang
According to the findings, we further propose a novel importance sampling-based, element-wise joint optimization method, called Adaptively Mask Subnetworks Considering Modal Significance(AMSS).
1 code implementation • 2 Apr 2024 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
By enhancing trajectory prediction accuracy and addressing the challenges of out-of-sight objects, our work significantly contributes to improving the safety and reliability of autonomous driving in complex environments.
no code implementations • 1 Apr 2024 • Yi Xu
With the implementation of personal data privacy regulations, the field of machine learning (ML) faces the challenge of the "right to be forgotten".
no code implementations • 31 Mar 2024 • Yi Xu, Yun Fu
Trajectory prediction plays an important role in various applications, including autonomous driving, robotics, and scene understanding.
1 code implementation • 27 Mar 2024 • Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang, Chang Liu, Yi Xu, Jie Chen, Xiangyang Ji
However, these methods encounter challenges such as the lack of coordination between different part motions and difficulties for networks to understand part concepts.
Ranked #8 on Motion Synthesis on HumanML3D
no code implementations • 26 Mar 2024 • Haonan Xu, Yurui Huang, Sishun Pan, Zhihao Guan, Yi Xu, Yang Yang
For the vehicle retrieval task, we use BLIP as the base model.
no code implementations • 26 Mar 2024 • Hongpeng Pan, Yang Yang, Zhongtian Fu, Yuxuan Zhang, Shian Du, Yi Xu, Xiangyang Ji
To address this issue, we propose a simple yet effective approach called TAP with confident static points (TAPIR+), which focuses on rectifying the tracking of the static point in the videos shot by a static camera.
no code implementations • 24 Mar 2024 • Yi Xu, Weiran Shen, Xiao Zhang, Jun Xu
This poses a new challenge for existing imitation learning approaches that can only utilize data from experienced experts.
no code implementations • 21 Mar 2024 • Shuqian Sheng, Yi Xu, Luoyi Fu, Jiaxin Ding, Lei Zhou, Xinbing Wang, Chenghu Zhou
The majority of automatic metrics for evaluating NLG systems are reference-based.
1 code implementation • 15 Mar 2024 • Yi Xu, Kunyu Peng, Di Wen, Ruiping Liu, Junwei Zheng, Yufan Chen, Jiaming Zhang, Alina Roitberg, Kailun Yang, Rainer Stiefelhagen
In this study, we bridge this gap by implementing a framework that augments well-established skeleton-based human action recognition methods with label-denoising strategies from various research areas to serve as the initial benchmark.
no code implementations • 5 Mar 2024 • Xinbing Wang, Luoyi Fu, Xiaoying Gan, Ying Wen, Guanjie Zheng, Jiaxin Ding, Liyao Xiang, Nanyang Ye, Meng Jin, Shiyu Liang, Bin Lu, Haiwen Wang, Yi Xu, Cheng Deng, Shao Zhang, Huquan Kang, Xingli Wang, Qi Li, Zhixin Guo, Jiexing Qi, Pan Liu, Yuyang Ren, Lyuwen Wu, Jungang Yang, Jianping Zhou, Chenghu Zhou
The exponential growth of scientific literature requires effective management and extraction of valuable insights.
no code implementations • 3 Mar 2024 • Tianyu Luan, Zhong Li, Lele Chen, Xuan Gong, Lichang Chen, Yi Xu, Junsong Yuan
Then, we calculate the Area Under the Curve (AUC) difference between the two spectrums, so that each frequency band that captures either the overall or detailed shape is equitably considered.
1 code implementation • 29 Feb 2024 • Ziyue Feng, Huangying Zhan, Zheng Chen, Qingan Yan, Xiangyu Xu, Changjiang Cai, Bing Li, Qilun Zhu, Yi Xu
We present NARUTO, a neural active reconstruction system that combines a hybrid neural representation with uncertainty learning, enabling high-fidelity surface reconstruction.
no code implementations • 3 Feb 2024 • Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu, Belinda Zeng, Trishul Chilimbi, Han Zhao
To overcome this limitation, we propose Multi-Task Learning with Excess Risks (ExcessMTL), an excess risk-based task balancing method that updates the task weights by their distances to convergence instead.
no code implementations • 26 Jan 2024 • Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
Pre-training is known to generate universal representations for downstream tasks in large-scale deep learning such as large language models.
1 code implementation • 31 Dec 2023 • Zhouhan Lin, Cheng Deng, Le Zhou, Tianhang Zhang, Yi Xu, Yutong Xu, Zhongmou He, Yuanyuan Shi, Beiya Dai, Yunchong Song, Boyi Zeng, Qiyuan Chen, Yuxun Miao, Bo Xue, Shu Wang, Luoyi Fu, Weinan Zhang, Junxian He, Yunqiang Zhu, Xinbing Wang, Chenghu Zhou
To our best knowledge, it is the largest language model for the geoscience domain.
no code implementations • 30 Dec 2023 • Zheng Chen, Qingan Yan, Huangying Zhan, Changjiang Cai, Xiangyu Xu, Yuzhong Huang, Weihan Wang, Ziyue Feng, Lantao Liu, Yi Xu
Through extensive experiments, we demonstrate the effectiveness of PlanarNeRF in various scenarios and remarkable improvement over existing works.
1 code implementation • 28 Dec 2023 • Zhan Li, Zhang Chen, Zhong Li, Yi Xu
Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem.
no code implementations • 8 Dec 2023 • Xiaofeng Yang, YiWen Chen, Cheng Chen, Chi Zhang, Yi Xu, Xulei Yang, Fayao Liu, Guosheng Lin
We propose a unified framework aimed at enhancing the diffusion priors for 3D generation tasks.
no code implementations • 6 Dec 2023 • Zhimiao Yu, Tiancheng Lin, Yi Xu
In this paper, we propose a new pre-training scheme for FSS via decoupling the novel classes from background, called Background Clustering Pre-Training (BCPT).
no code implementations • 15 Nov 2023 • Yixiu Mao, Hongchang Zhang, Chen Chen, Yi Xu, Xiangyang Ji
Offline reinforcement learning suffers from the out-of-distribution issue and extrapolation error.
1 code implementation • 23 Oct 2023 • Zhong Li, Liangchen Song, Zhang Chen, Xiangyu Du, Lele Chen, Junsong Yuan, Yi Xu
A DecomposeNet learns to map each ray to its SVBRDF components: albedo, normal, and roughness.
no code implementations • 9 Oct 2023 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
In summary, our approach offers a promising solution to the challenges faced by layout sequence and trajectory prediction models in real-world settings, paving the way for utilizing sensor data from mobile phones to accurately predict pedestrian bounding box trajectories.
no code implementations • 7 Oct 2023 • Zixuan Liu, Gaurush Hiranandani, Kun Qian, Eddie W. Huang, Yi Xu, Belinda Zeng, Karthik Subbian, Sheng Wang
ForeSeer transfers reviews from similar products on a large product graph and exploits these reviews to predict aspects that might emerge in future reviews.
no code implementations • NeurIPS 2023 • Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu
We begin by defining the pivotal nodes as $k$-hop starved nodes, which can be identified based on a given adjacency matrix.
1 code implementation • ICCV 2023 • Zhang Chen, Zhong Li, Liangchen Song, Lele Chen, Jingyi Yu, Junsong Yuan, Yi Xu
The spatial positions of their neural features are fixed on grid nodes and cannot well adapt to target signals.
no code implementations • 18 Sep 2023 • Xinbei Ma, Yi Xu, Hai Zhao, Zhuosheng Zhang
On the other hand, the split segments are an appropriate element of multi-turn dialogue response selection.
no code implementations • NeurIPS 2023 • Isabella Liu, Linghao Chen, Ziyang Fu, Liwen Wu, Haian Jin, Zhong Li, Chin Ming Ryan Wong, Yi Xu, Ravi Ramamoorthi, Zexiang Xu, Hao Su
We introduce OpenIllumination, a real-world dataset containing over 108K images of 64 objects with diverse materials, captured under 72 camera views and a large number of different illuminations.
no code implementations • 8 Sep 2023 • Hongyu Hu, Tiancheng Lin, Jie Wang, Zhenbang Sun, Yi Xu
To achieve this, we introduce a pre-trained LLM to generate context descriptions, and we encourage the prompts to learn from the LLM's knowledge by alignment, as well as the alignment between prompts and local image features.
no code implementations • 29 Aug 2023 • Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu, Lei Zhou, Xinbing Wang, Chenghu Zhou
To this end, we investigate the limits of historical information for temporal knowledge graph extrapolation and propose a new event forecasting model called Contrastive Event Network (CENET) based on a novel training framework of historical contrastive learning.
no code implementations • 19 Aug 2023 • Yunwen Huang, Hongyu Hu, Ying Zhu, Yi Xu
In this work, we propose a multi-modality breast tumor diagnosis model to imitate the diagnosing process of radiologists, which learns the features of both static images and dynamic video and explores the potential relationship between the two modalities.
1 code implementation • 10 Aug 2023 • Siqiao Xue, Fan Zhou, Yi Xu, Ming Jin, Qingsong Wen, Hongyan Hao, Qingyang Dai, Caigao Jiang, Hongyu Zhao, Shuo Xie, Jianshan He, James Zhang, Hongyuan Mei
We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain.
1 code implementation • 1 Aug 2023 • Jinglei Zhang, Tiancheng Lin, Yi Xu, Kai Chen, Rui Zhang
We argue that such prior contextual information can be interpreted as the relations of textual primitives due to the heterogeneous text and background, which can provide effective self-supervised labels for representation learning.
no code implementations • 31 Jul 2023 • Minyi Zhao, Yi Xu, Bingjia Li, Jie Wang, Jihong Guan, Shuigeng Zhou
Observing the quality issue of HR images, in this paper we propose a novel idea to boost STISR by first enhancing the quality of HR images and then using the enhanced HR images as supervision to do STISR.
1 code implementation • 20 Jul 2023 • Zhimiao Yu, Tiancheng Lin, Yi Xu
Specifically, we iteratively perform intra-slide clustering for the regions (4096x4096 patches) within each WSI to yield the prototypes and encourage the region representations to be closer to the assigned prototypes.
1 code implementation • ICCV 2023 • Wentao Bao, Lele Chen, Libing Zeng, Zhong Li, Yi Xu, Junsong Yuan, Yu Kong
In this paper, we set up an egocentric 3D hand trajectory forecasting task that aims to predict hand trajectories in a 3D space from early observed RGB videos in a first-person view.
1 code implementation • CVPR 2023 • Tianyu Luan, Yuanhao Zhai, Jingjing Meng, Zhong Li, Zhang Chen, Yi Xu, Junsong Yuan
To capture high-frequency personalized details, we transform the 3D mesh into the frequency domain, and propose a novel frequency decomposition loss to supervise each frequency component.
1 code implementation • 8 Jun 2023 • Cheng Deng, Tianhang Zhang, Zhongmou He, Yi Xu, Qiyuan Chen, Yuanyuan Shi, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin, Junxian He
Large language models (LLMs) have achieved great success in general domains of natural language processing.
no code implementations • 8 Jun 2023 • Libing Zeng, Lele Chen, Yi Xu, Nima Kalantari
In this paper, we propose an approach to obtain a personalized generative prior with explicit control over a set of attributes.
no code implementations • 5 Jun 2023 • Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
Model pre-training on large text corpora has been demonstrated effective for various downstream applications in the NLP domain.
1 code implementation • 4 Jun 2023 • Yi Xu, Shuqian Sheng, Bo Xue, Luoyi Fu, Xinbing Wang, Chenghu Zhou
The results demonstrate that our system has broad prospects and can assist researchers in expediting the process of discovering new ideas.
no code implementations • 12 Apr 2023 • Xiangyu Xu, Lichang Chen, Changjiang Cai, Huangying Zhan, Qingan Yan, Pan Ji, Junsong Yuan, Heng Huang, Yi Xu
Direct optimization of interpolated features on multi-resolution voxel grids has emerged as a more efficient alternative to MLP-like modules.
1 code implementation • CVPR 2023 • Yi Xu, Armin Bazarjani, Hyung-gun Chi, Chiho Choi, Yun Fu
As far as we know, this is the first work to address the lack of benchmarks and techniques for trajectory imputation and prediction in a unified manner.
1 code implementation • CVPR 2023 • Ziquan Liu, Yi Xu, Xiangyang Ji, Antoni B. Chan
To better exploit the potential of pre-trained models in adversarial robustness, this paper focuses on the fine-tuning of an adversarially pre-trained model in various classification tasks.
no code implementations • 15 Mar 2023 • Chenbin Pan, Zhiqi Zhang, Senem Velipasalar, Yi Xu
Different from previous video transformers, which use the same static embedding as the class token for diverse inputs, we propose a dynamic class token generator that produces a class token for each input video by analyzing the hand-object interaction and the related motion information.
1 code implementation • 15 Mar 2023 • Liangchen Song, Zhong Li, Xuan Gong, Lele Chen, Zhang Chen, Yi Xu, Junsong Yuan
We further propose a simple-yet-effective strategy for tuning the frequency to avoid overfitting few-shot inputs: enforcing consistency among the frequency domain of rendered 2D images.
1 code implementation • CVPR 2023 • Tiancheng Lin, Zhimiao Yu, Hongyu Hu, Yi Xu, Chang Wen Chen
This deficiency is a confounder that limits the performance of existing MIL methods.
no code implementations • CVPR 2023 • Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi
Hence we advocate that the key of better performance lies in meaningful latent modality structures instead of perfect modality alignment.
Few-Shot Image Classification Open-Ended Question Answering +6
1 code implementation • 28 Jan 2023 • Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, Yun Fu
With the same perturbation magnitude, the testing reconstruction error of the normal frames lowers more than that of the abnormal frames, which contributes to mitigating the overfitting problem of reconstruction.
no code implementations • CVPR 2023 • Libing Zeng, Lele Chen, Wentao Bao, Zhong Li, Yi Xu, Junsong Yuan, Nima Khademi Kalantari
Accurate facial landmark detection on wild images plays an essential role in human-computer interaction, entertainment, and medical applications.
no code implementations • CVPR 2023 • Hyung-gun Chi, Kwonjoon Lee, Nakul Agarwal, Yi Xu, Karthik Ramani, Chiho Choi
SALF is challenging because it requires understanding the underlying physics of video observations to predict future action locations accurately.
1 code implementation • 23 Nov 2022 • Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian
We study EurNets in two important domains for image and protein structure modeling.
no code implementations • 23 Nov 2022 • Huangying Zhan, Jiyang Zheng, Yi Xu, Ian Reid, Hamid Rezatofighi
We, for the first time, present an RGB-only active vision framework using radiance field representation for active 3D reconstruction and planning in an online manner.
1 code implementation • 20 Nov 2022 • Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu
Simultaneously, it trains representations of queries to investigate whether the current moment depends more on historical or non-historical events by launching contrastive learning.
1 code implementation • 18 Nov 2022 • Yitian Zhang, Yue Bai, Huan Wang, Yi Xu, Yun Fu
To tackle this problem, we propose Ample and Focal Network (AFNet), which is composed of two branches to utilize more frames but with less computation.
no code implementations • 28 Oct 2022 • Liangchen Song, Anpei Chen, Zhong Li, Zhang Chen, Lele Chen, Junsong Yuan, Yi Xu, Andreas Geiger
Visually exploring in a real-world 4D spatiotemporal space freely in VR has been a long-term quest.
no code implementations • 25 Oct 2022 • Zhiqi Zhang, Nitin Bansal, Changjiang Cai, Pan Ji, Qingan Yan, Xiangyu Xu, Yi Xu
To this end, we propose CLIP-FLow, a semi-supervised iterative pseudo-labeling framework to transfer the pretraining knowledge to the target real domain.
no code implementations • 12 Oct 2022 • Qi Qi, Shervin Ardeshir, Yi Xu, Tianbao Yang
Improving fairness between privileged and less-privileged sensitive attribute groups (e. g, {race, gender}) has attracted lots of attention.
no code implementations • 27 Sep 2022 • Jiaming Shen, Bolin Song, Zirui Wu, Yi Xu
3D reconstruction from images has wide applications in Virtual Reality and Automatic Driving, where the precision requirement is very high.
no code implementations • 22 Sep 2022 • Yi Xu, Luoyi Fu, Zhouhan Lin, Jiexing Qi, Xinbing Wang
As a fully unsupervised framework, INFINITY is empirically verified to outperform state-of-the-art baselines for G2T and T2G tasks.
no code implementations • 18 Jul 2022 • Runze Li, Pan Ji, Yi Xu, Bir Bhanu
As compared to outdoor environments, estimating depth of monocular videos for indoor environments, using self-supervised methods, results in two additional challenges: (i) the depth range of indoor video sequences varies a lot across different frames, making it difficult for the depth network to induce consistent depth cues for training; (ii) the indoor sequences recorded with handheld devices often contain much more rotational motions, which cause difficulties for the pose network to predict accurate relative camera poses.
1 code implementation • 18 Jul 2022 • Canqian Yang, Meiguang Jin, Yi Xu, Rui Zhang, Ying Chen, Huaida Liu
Image-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms.
Ranked #5 on Image Enhancement on MIT-Adobe 5k (PSNR on proRGB metric)
no code implementations • 22 Jun 2022 • Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis
The effectiveness in our framework is achieved by applying stage-wise fine-tuning of the BERT model first with heterogenous graph information and then with a GNN model.
no code implementations • 21 Jun 2022 • Nitin Bansal, Pan Ji, Junsong Yuan, Yi Xu
Multi-task learning (MTL) paradigm focuses on jointly learning two or more tasks, aiming for significant improvement w. r. t model's generalizability, performance, and training/inference memory footprint.
no code implementations • 7 Jun 2022 • Xiaodi Sun, Sunny Rajagopalan, Priyanka Nigam, Weiyi Lu, Yi Xu, Belinda Zeng, Trishul Chilimbi
In this paper, we propose an improvement to prompt-based fine-tuning that addresses these two issues.
no code implementations • CVPR 2023 • Changjiang Cai, Pan Ji, Qingan Yan, Yi Xu
At the pixel level, we propose to break the symmetry of the Siamese network (which is typically used in MVS to extract image features) by introducing a transformer block to the reference image (but not to the source images).
1 code implementation • 26 May 2022 • Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li, Zhenbang Sun, Jian Tang, Yi Xu, Bingbing Ni
This framework aims to learn multiple semantic representations for each image, and these representations are structured to encode image semantics from fine-grained to coarse-grained.
no code implementations • 25 May 2022 • Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan
With our empirical result obtained from 1, 330 models, we provide the following main observations: 1) ERM combined with data augmentation can achieve state-of-the-art performance if we choose a proper pre-trained model respecting the data property; 2) specialized algorithms further improve the robustness on top of ERM when handling a specific type of distribution shift, e. g., GroupDRO for spurious correlation and CORAL for large-scale out-of-distribution data; 3) Comparing different pre-training modes, architectures and data sizes, we provide novel observations about pre-training on distribution shift, which sheds light on designing or selecting pre-training strategy for different kinds of distribution shifts.
no code implementations • 5 May 2022 • Qingan Yan, Pan Ji, Nitin Bansal, Yuxin Ma, Yuan Tian, Yi Xu
In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner.
no code implementations • 5 May 2022 • Pan Ji, Yuan Tian, Qingan Yan, Yuxin Ma, Yi Xu
The CNN depth effectively bootstraps the back-end optimization of SLAM and meanwhile the CNN uncertainty adaptively weighs the contribution of each feature point to the back-end optimization.
no code implementations • 3 May 2022 • Pan Ji, Qingan Yan, Yuxin Ma, Yi Xu
We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences.
1 code implementation • CVPR 2022 • Canqian Yang, Meiguang Jin, Xu Jia, Yi Xu, Ying Chen
They adopt a sub-optimal uniform sampling point allocation, limiting the expressiveness of the learned LUTs since the (tri-)linear interpolation between uniform sampling points in the LUT transform might fail to model local non-linearities of the color transform.
Ranked #2 on Photo Retouching on MIT-Adobe 5k
no code implementations • NAACL 2022 • Minyi Zhao, Lu Zhang, Yi Xu, Jiandong Ding, Jihong Guan, Shuigeng Zhou
However, to the best of our knowledge, most existing methods consider only either the diversity or the quality of augmented data, thus cannot fully mine the potential of DA for NLP.
1 code implementation • 20 Apr 2022 • Daniel R. van Niekerk, Anqi Xu, Branislav Gerazov, Paul K. Krug, Peter Birkholz, Yi Xu
High-quality articulatory speech synthesis has many potential applications in speech science and technology.
no code implementations • 20 Apr 2022 • Renhui Zhang, Tiancheng Lin, Rui Zhang, Yi Xu
Benchmark datasets for visual recognition assume that data is uniformly distributed, while real-world datasets obey long-tailed distribution.
no code implementations • 20 Apr 2022 • Tiancheng Lin, Hongteng Xu, Canqian Yang, Yi Xu
When applying multi-instance learning (MIL) to make predictions for bags of instances, the prediction accuracy of an instance often depends on not only the instance itself but also its context in the corresponding bag.
no code implementations • 18 Apr 2022 • Yangrun Hu, Yuanfan Guo, Fan Zhang, Mingda Wang, Tiancheng Lin, Rong Wu, Yi Xu
Based on the insight that mass data is sufficient and shares the same knowledge structure with non-mass data of identifying the malignancy of a lesion based on the ultrasound image, we propose a novel transfer learning framework to enhance the generalizability of the DNN model for non-mass BUS with the help of mass BUS.
no code implementations • 18 Apr 2022 • Yuanfan Guo, Canqian Yang, Tiancheng Lin, Chunxiao Li, Rui Zhang, Yi Xu
Since an ultrasound image only describes a partial 2D projection of a 3D lesion, such paradigm ignores the semantic relationship between different views of a lesion, which is inconsistent with the traditional diagnosis where sonographers analyze a lesion from at least two views.
no code implementations • CVPR 2022 • Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang
In this work, we aim to learn representations by leveraging more abundant information in untrimmed videos.
1 code implementation • CVPR 2022 • Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
However, conventional pruning methods have limitations in that: they are restricted to pruning process only, and they require a fully pre-trained large model.
1 code implementation • 23 Mar 2022 • Ze Yang, Chi Zhang, Ruibo Li, Yi Xu, Guosheng Lin
Upon this baseline, we devise an initializer named knowledge inheritance (KI) to reliably initialize the novel weights for the box classifier, which effectively facilitates the knowledge transfer process and boosts the adaptation speed.
no code implementations • CVPR 2022 • Jiachen Liu, Pan Ji, Nitin Bansal, Changjiang Cai, Qingan Yan, Xiaolei Huang, Yi Xu
The semantic plane detection branch is based on a single-view plane detection framework but with differences.
1 code implementation • 12 Mar 2022 • Sudhir Yarram, Jialian Wu, Pan Ji, Yi Xu, Junsong Yuan
To improve the training efficiency, we propose Deformable VisTR, leveraging spatio-temporal deformable attention module that only attends to a small fixed set of key spatio-temporal sampling points around a reference point.
no code implementations • CVPR 2022 • Yi Xu, Lichen Wang, Yizhou Wang, Yun Fu
To the best of our knowledge, our work is the pioneer which fills the gap in benchmarks and techniques for practical pedestrian trajectory prediction across different domains.
no code implementations • CVPR 2022 • Jiali Duan, Liqun Chen, Son Tran, Jinyu Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
Aligning signals from different modalities is an important step in vision-language representation learning as it affects the performance of later stages such as cross-modality fusion.
1 code implementation • CVPR 2022 • Jinyu Yang, Jiali Duan, Son Tran, Yi Xu, Sampath Chanda, Liqun Chen, Belinda Zeng, Trishul Chilimbi, Junzhou Huang
Besides CMA, TCL introduces an intra-modal contrastive objective to provide complementary benefits in representation learning.
Ranked #3 on Zero-Shot Cross-Modal Retrieval on COCO 2014
2 code implementations • CVPR 2022 • Yuanfan Guo, Minghao Xu, Jiawen Li, Bingbing Ni, Xuanyu Zhu, Zhenbang Sun, Yi Xu
In this framework, a set of hierarchical prototypes are constructed and also dynamically updated to represent the hierarchical semantic structures underlying the data in the latent space.
no code implementations • 7 Dec 2021 • Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
Although rigorous convergence analysis exists for Adam, they impose specific requirements on the update of the adaptive step size, which are not generic enough to cover many other variants of Adam.
no code implementations • 3 Dec 2021 • Shengjia Zhang, Tiancheng Lin, Yi Xu
To avoid overfitting on source domain, at the second stage, we propose a curriculum learning strategy to adaptively control the weighting between losses from the two domains so that the focus of the training stage is gradually shifted from source distribution to target distribution with prediction confidence boosted on the target domain.
1 code implementation • 25 Nov 2021 • Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu
Next we add adversarial perturbation to the transformed features to decrease their softmax scores of the predicted labels and design anomaly scores based on the predictive uncertainties of the classifier on these perturbed features.
no code implementations • 24 Nov 2021 • Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni Chan, Rong Jin
The generalization result of using pre-training data shows that the excess risk bound on a target task can be improved when the appropriate pre-training data is included in fine-tuning.
2 code implementations • 23 Nov 2021 • Hao Luo, Pichao Wang, Yi Xu, Feng Ding, Yanxin Zhou, Fan Wang, Hao Li, Rong Jin
We first investigate self-supervised learning (SSL) methods with Vision Transformer (ViT) pretrained on unlabelled person images (the LUPerson dataset), and empirically find it significantly surpasses ImageNet supervised pre-training models on ReID tasks.
Ranked #1 on Unsupervised Person Re-Identification on Market-1501 (using extra training data)
no code implementations • 30 Oct 2021 • Xuanli He, Iman Keivanloo, Yi Xu, Xiang He, Belinda Zeng, Santosh Rajagopalan, Trishul Chilimbi
To achieve this, we propose a novel idea, Magic Pyramid (MP), to reduce both width-wise and depth-wise computation via token pruning and early exiting for Transformer-based models, particularly BERT.
no code implementations • NeurIPS 2021 • Yi Xu, Jiandong Ding, Lu Zhang, Shuigeng Zhou
Extensive experiments on four standard SSL benchmarks show that DP-SSL can provide reliable labels for unlabeled data and achieve better classification performance on test sets than existing SSL methods, especially when only a small number of labeled samples are available.
1 code implementation • EMNLP 2021 • Lu Zhang, Jiandong Ding, Yi Xu, Yingyao Liu, Shuigeng Zhou
Among them, keyword-driven methods are the mainstream where user-provided keywords are exploited to generate pseudo-labels for unlabeled texts.
no code implementations • 29 Sep 2021 • Yi Xu, Lichen Wang, Yizhou Wang, Can Qin, Yulun Zhang, Yun Fu
In this paper, we propose a novel framework, MemREIN, which considers Memorized, Restitution, and Instance Normalization for cross-domain few-shot learning.
no code implementations • 29 Sep 2021 • Zhixuan Chu, Tan Yan, Yue Wu, Yi Xu, Cheng Zhang, Yulin kang
Time series forecasting has historically been a key area of academic research and industrial applications.
no code implementations • 25 Sep 2021 • Haotong Qin, Xiangguo Zhang, Ruihao Gong, Yifu Ding, Yi Xu, Xianglong Liu
We present a novel Distribution-sensitive Information Retention Network (DIR-Net) that retains the information in the forward and backward propagation by improving internal propagation and introducing external representations.
no code implementations • 24 Sep 2021 • Tarik Arici, Mehmet Saygin Seyfioglu, Tal Neiman, Yi Xu, Son Train, Trishul Chilimbi, Belinda Zeng, Ismail Tutar
Vision-and-Language Pre-training (VLP) improves model performance for downstream tasks that require image and text inputs.
no code implementations • 1 Sep 2021 • Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin
In this work we develop a simple yet powerful framework, whose key idea is to select a subset of training examples from the unlabeled data when performing existing SSL methods so that only the unlabeled examples with pseudo labels related to the labeled data will be used to train models.
no code implementations • 4 Aug 2021 • Minyi Zhao, Yi Xu, Shuigeng Zhou
A number of deep learning based algorithms have been proposed to recover high-quality videos from low-quality compressed ones.
no code implementations • ICCV 2021 • Pan Ji, Runze Li, Bir Bhanu, Yi Xu
The effectiveness of each module is shown through a carefully conducted ablation study and the demonstration of the state-of-the-art performance on three indoor datasets, \ie, EuRoC, NYUv2, and 7-scenes.
1 code implementation • 2 Jul 2021 • Junya Chen, Zhe Gan, Xuan Li, Qing Guo, Liqun Chen, Shuyang Gao, Tagyoung Chung, Yi Xu, Belinda Zeng, Wenlian Lu, Fan Li, Lawrence Carin, Chenyang Tao
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years.
1 code implementation • 22 Jun 2021 • Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang, Yun Fu
The intuition is that gradient with momentum contains more accurate directional information and therefore its second moment estimation is a more favorable option for learning rate scaling than that of the raw gradient.
1 code implementation • ICLR 2022 • Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
It addresses the shortcomings of the previous works by repeatedly growing a subset of layers to dense and then pruning them back to sparse after some training.
1 code implementation • Findings (ACL) 2021 • Yi Xu, Hai Zhao
Pre-trained language models (PrLM) has been shown powerful in enhancing a broad range of downstream tasks including various dialogue related ones.
no code implementations • 31 May 2021 • Yi Xu, Minyi Zhao, Jing Liu, Xinjian Zhang, Longwen Gao, Shuigeng Zhou, Huyang Sun
Many deep learning based video compression artifact removal algorithms have been proposed to recover high-quality videos from low-quality compressed videos.
no code implementations • 25 May 2021 • Chen Shi, Xiangtai Li, Yanran Wu, Yunhai Tong, Yi Xu
Representation of semantic context and local details is the essential issue for building modern semantic segmentation models.
no code implementations • 15 May 2021 • Zhong Li, Liangchen Song, Celong Liu, Junsong Yuan, Yi Xu
In this paper, we present an efficient and robust deep learning solution for novel view synthesis of complex scenes.
no code implementations • 13 May 2021 • Yi Xu, Qi Qian, Hao Li, Rong Jin
Stochastic gradient descent (SGD) has become the most attractive optimization method in training large-scale deep neural networks due to its simplicity, low computational cost in each updating step, and good performance.
no code implementations • 30 Apr 2021 • Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
Our analysis exhibits that an increasing or large enough "momentum" parameter for the first-order moment used in practice is sufficient to ensure Adam and its many variants converge under a mild boundness condition on the adaptive scaling factor of the step size.
1 code implementation • 21 Apr 2021 • Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng Li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, XiaoYu Zhang, Linjie Zhou, Sixin Lin, Ru Wang
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.
no code implementations • 8 Apr 2021 • Yi Xu, Qi Qian, Hao Li, Rong Jin
Noisy labels are very common in deep supervised learning.
1 code implementation • 9 Feb 2021 • Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Deep AUC (area under the ROC curve) Maximization (DAM) has attracted much attention recently due to its great potential for imbalanced data classification.
no code implementations • 12 Jan 2021 • Asaf Noy, Yi Xu, Yonathan Aflalo, Lihi Zelnik-Manor, Rong Jin
We show that convergence to a global minimum is guaranteed for networks with widths quadratic in the sample size and linear in their depth at a time logarithmic in both.
1 code implementation • 13 Dec 2020 • Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang
In this paper, we present a simple yet effective provable method (named ABSGD) for addressing the data imbalance or label noise problem in deep learning.
1 code implementation • 12 Dec 2020 • Yuliang Guo, Zhong Li, Zekun Li, Xiangyu Du, Shuxue Quan, Yi Xu
In this paper, a real-time method called PoP-Net is proposed to predict multi-person 3D poses from a depth image.
no code implementations • 3 Oct 2020 • Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin
To this end, we develop two novel algorithms, termed "AugDrop" and "MixLoss", to correct the data bias in the data augmentation.
1 code implementation • 26 Sep 2020 • Yi Xu, Hai Zhao, Zhuosheng Zhang
In the retrieval-based multi-turn dialogue modeling, it remains a challenge to select the most appropriate response according to extracting salient features in context utterances.
no code implementations • 15 Aug 2020 • Xiang Li, Yuan Tian, Fuyao Zhang, Shuxue Quan, Yi Xu
Ordinary object detection approaches process information from the images only, and they are oblivious to the camera pose with regard to the environment and the scale of the environment.
1 code implementation • 16 Jul 2020 • Lele Chen, Guofeng Cui, Celong Liu, Zhong Li, Ziyi Kou, Yi Xu, Chenliang Xu
When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information.
no code implementations • 24 Jun 2020 • Yamin Li, Jiancheng Yang, Yi Xu, Jingwei Xu, Xiaodan Ye, Guangyu Tao, Xueqian Xie, Guixue Liu
It is achieved by predicting future displacement field of each voxel with a WarpNet.
no code implementations • 20 Jun 2020 • Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin
Label smoothing regularization (LSR) has a great success in training deep neural networks by stochastic algorithms such as stochastic gradient descent and its variants.
1 code implementation • NeurIPS 2021 • Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang
In this paper, we propose a practical online method for solving a class of distributionally robust optimization (DRO) with non-convex objectives, which has important applications in machine learning for improving the robustness of neural networks.
no code implementations • 20 May 2020 • Branislav Gerazov, Daniel van Niekerk, Anqi Xu, Paul Konstantin Krug, Peter Birkholz, Yi Xu
One of the crucial parameters in these simulations is the choice of features and a metric to evaluate the acoustic error between the synthesised sound and the reference target.
no code implementations • 12 Apr 2020 • Jiancheng Yang, Haoran Deng, Xiaoyang Huang, Bingbing Ni, Yi Xu
In this study, we propose a multiple instance learning (MIL) approach and empirically prove the benefit to learn the relations between multiple nodules.
no code implementations • 9 Apr 2020 • Tiancheng Lin, Yuanfan Guo, Canqian Yang, Jiancheng Yang, Yi Xu
Early diagnosis of signet ring cell carcinoma dramatically improves the survival rate of patients.
no code implementations • CVPR 2020 • Qiuyu Chen, Wei zhang, Ning Zhou, Peng Lei, Yi Xu, Yu Zheng, Jianping Fan
Specifically, the fractional dilated kernel is adaptively constructed according to the image aspect ratios, where the interpolation of nearest two integers dilated kernels is used to cope with the misalignment of fractional sampling.
no code implementations • NeurIPS 2020 • Yan Yan, Yi Xu, Qihang Lin, Wei Liu, Tianbao Yang
In this paper, we bridge this gap by providing a sharp analysis of epoch-wise stochastic gradient descent ascent method (referred to as Epoch-GDA) for solving strongly convex strongly concave (SCSC) min-max problems, without imposing any additional assumption about smoothness or the function's structure.
no code implementations • 11 Feb 2020 • Xin Wang, Ruisheng Su, Weiyi Xie, Wenjin Wang, Yi Xu, Ritse Mann, Jungong Han, Tao Tan
Such performance gain is more pronounced with transfer learning or in the case of limited training data.
7 code implementations • 21 Jan 2020 • Youren Shen, Hongliang Tian, Yu Chen, Kang Chen, Runji Wang, Yi Xu, Yubin Xia
SFI is a software instrumentation technique for sandboxing untrusted modules (called domains).
Operating Systems Hardware Architecture Cryptography and Security
1 code implementation • CVPR 2020 • Xuan Zhang, Shaofei Qin, Yi Xu, Hongteng Xu
We propose a novel quaternion product unit (QPU) to represent data on 3D rotation groups.
no code implementations • ICCV 2019 • Yi Xu, Longwen Gao, Kai Tian, Shuigeng Zhou, Huyang Sun
Video compression artifact reduction aims to recover high-quality videos from low-quality compressed videos.
no code implementations • 20 Oct 2019 • Jiancheng Yang, Rongyao Fang, Bingbing Ni, Yamin Li, Yi Xu, Linguo Li
The final diagnosis is obtained by combining the ambiguity prior sample and lesion representation, and the whole network named $DenseSharp^{+}$ is end-to-end trainable.
no code implementations • WS 2019 • Vikas Raunak, Sang Keun Choe, Quanyang Lu, Yi Xu, Florian Metze
Leveraging the visual modality effectively for Neural Machine Translation (NMT) remains an open problem in computational linguistics.
no code implementations • 13 Sep 2019 • Xiaoyang Huang, Jiancheng Yang, Linguo Li, Haoran Deng, Bingbing Ni, Yi Xu
Emergence of artificial intelligence techniques in biomedical applications urges the researchers to pay more attention on the uncertainty quantification (UQ) in machine-assisted medical decision making.
no code implementations • ICML 2020 • Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang
In this paper, we study a family of non-convex and possibly non-smooth inf-projection minimization problems, where the target objective function is equal to minimization of a joint function over another variable.
no code implementations • 31 Jul 2019 • Yi Xu, Shanglin Yang, Wei Sun, Li Tan, Kefeng Li, Hui Zhou
The predicted landmarks are used for estimating sizing information of the garment.
no code implementations • 17 Jun 2019 • Wei Sun, Jawadul H. Bappy, Shanglin Yang, Yi Xu, Tianfu Wu, Hui Zhou
In order to formulate the framework, we employ one generator and two discriminators for image synthesis.
1 code implementation • 17 May 2019 • Xiao Wu, Yi Xu, Bradley P. Carlin
In developing products for rare diseases, statistical challenges arise due to the limited number of patients available for participation in drug trials and other clinical research.
Applications Computation Methodology
no code implementations • 23 Apr 2019 • Yan Yan, Yi Xu, Qihang Lin, Lijun Zhang, Tianbao Yang
The main contribution of this paper is the design and analysis of new stochastic primal-dual algorithms that use a mixture of stochastic gradient updates and a logarithmic number of deterministic dual updates for solving a family of convex-concave problems with no bilinear structure assumed.
1 code implementation • ECCV 2018 • Xuanyu Zhu, Yi Xu, Hongteng Xu, Changjian Chen
Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years.
no code implementations • 27 Feb 2019 • Zhenyu Duan, Martin Renqiang Min, Li Erran Li, Mingbo Cai, Yi Xu, Bingbing Ni
In spite of achieving revolutionary successes in machine learning, deep convolutional neural networks have been recently found to be vulnerable to adversarial attacks and difficult to generalize to novel test images with reasonably large geometric transformations.
no code implementations • 17 Dec 2018 • Jieli Zhou, Yuntao Zhou, Yi Xu
ASE combines recent theories and methods from Computational Analogy and Natural Language Processing to go beyond keyword-based lexical search and discover the deeper analogical relationships among research paper abstracts.
no code implementations • 28 Nov 2018 • Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang
In this paper, we propose new stochastic optimization algorithms and study their first-order convergence theories for solving a broad family of DC functions.
no code implementations • ECCV 2018 • Jie Zhang, Yi Xu, Bingbing Ni, Zhenyu Duan
The main contributions of the proposed frame- work are highlighted in two facets: (1) We put forward a multiple-task learning framework with mutually interlinked sub-structures between lane segmentation and lane boundary detection to improve overall performance.
no code implementations • ICML 2018 • Zaiyi Chen, Yi Xu, Enhong Chen, Tianbao Yang
Although the convergence rates of existing variants of ADAGRAD have a better dependence on the number of iterations under the strong convexity condition, their iteration complexities have a explicitly linear dependence on the dimensionality of the problem.
1 code implementation • 22 Jun 2018 • Branislav Gerazov, Gérard Bailly, Omar Mohammed, Yi Xu, Philip N. Garner
Our work bridges between a comprehensive generative model of intonation and state-of-the-art AI techniques.
1 code implementation • CVPR 2018 • Zan Shen, Yi Xu, Bingbing Ni, Minsi Wang, Jianguo Hu, Xiaokang Yang
Crowd counting or density estimation is a challenging task in computer vision due to large scale variations, perspective distortions and serious occlusions, etc.
Ranked #4 on Crowd Counting on WorldExpo’10
no code implementations • CVPR 2018 • Peng Zhou, Bingbing Ni, Cong Geng, Jianguo Hu, Yi Xu
Scale problem lies in the heart of object detection.
no code implementations • 21 May 2018 • Yi Xu, Shenghuo Zhu, Sen yang, Chi Zhang, Rong Jin, Tianbao Yang
Learning with a {\it convex loss} function has been a dominating paradigm for many years.
no code implementations • 4 Dec 2017 • Yi Xu, Rong Jin, Tianbao Yang
Accelerated gradient (AG) methods are breakthroughs in convex optimization, improving the convergence rate of the gradient descent method for optimization with smooth functions.
no code implementations • NeurIPS 2017 • Yi Xu, Qihang Lin, Tianbao Yang
The most studied error bound is the quadratic error bound, which generalizes strong convexity and is satisfied by a large family of machine learning problems.
no code implementations • NeurIPS 2017 • Yi Xu, Mingrui Liu, Qihang Lin, Tianbao Yang
The novelty of the proposed scheme lies at that it is adaptive to a local sharpness property of the objective function, which marks the key difference from previous adaptive scheme that adjusts the penalty parameter per-iteration based on certain conditions on iterates.
no code implementations • NeurIPS 2018 • Yi Xu, Rong Jin, Tianbao Yang
Two classes of methods have been proposed for escaping from saddle points with one using the second-order information carried by the Hessian and the other adding the noise into the first-order information.
no code implementations • 13 Sep 2017 • Lixue Zhuang, Yi Xu, Bingbing Ni, Hongteng Xu
In this work, we reveal an important fact that binarizing different layers has a widely-varied effect on the compression ratio of network and the loss of performance.
no code implementations • ICML 2017 • Yi Xu, Qihang Lin, Tianbao Yang
In this paper, a new theory is developed for first-order stochastic convex optimization, showing that the global convergence rate is sufficiently quantified by a local growth rate of the objective function in a neighborhood of the optimal solutions.
no code implementations • CVPR 2017 • Rui Yang, Bingbing Ni, Chao Ma, Yi Xu, Xiaokang Yang
We introduce a Multiple Granularity Analysis framework for video segmentation in a coarse-to-fine manner.
no code implementations • 6 Dec 2016 • Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang
Previously, oblivious random projection based approaches that project high dimensional features onto a random subspace have been used in practice for tackling high-dimensionality challenge in machine learning.
no code implementations • NeurIPS 2016 • Yi Xu, Yan Yan, Qihang Lin, Tianbao Yang
To the best of our knowledge, this is the lowest iteration complexity achieved so far for the considered non-smooth optimization problems without strong convexity assumption.
no code implementations • NeurIPS 2016 • Yi Xu, Yan Yan, Qihang Lin, Tianbao Yang
In this work, we will show that the proposed HOPS achieved a lower iteration complexity of $\widetilde O(1/\epsilon^{1-\theta})$\footnote{$\widetilde O()$ suppresses a logarithmic factor.}
no code implementations • 4 Jul 2016 • Yi Xu, Qihang Lin, Tianbao Yang
In particular, if the objective function $F(\mathbf w)$ in the $\epsilon$-sublevel set grows as fast as $\|\mathbf w - \mathbf w_*\|_2^{1/\theta}$, where $\mathbf w_*$ represents the closest optimal solution to $\mathbf w$ and $\theta\in(0, 1]$ quantifies the local growth rate, the iteration complexity of first-order stochastic optimization for achieving an $\epsilon$-optimal solution can be $\widetilde O(1/\epsilon^{2(1-\theta)})$, which is optimal at most up to a logarithmic factor.
no code implementations • 20 Oct 2014 • Chang Liu, Yi Xu
We propose a filter method for unsupervised feature selection which is based on the Confidence Machine.