Search Results for author: Shuo Yang

Found 52 papers, 16 papers with code

Dataset Pruning: Reducing Training Data by Examining Generalization Influence

no code implementations19 May 2022 Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li

To answer these, we propose dataset pruning, an optimization-based sample selection method that can (1) examine the influence of removing a particular set of training samples on model's generalization ability with theoretical guarantee, and (2) construct a smallest subset of training data that yields strictly constrained generalization gap.

Entity-aware and Motion-aware Transformers for Language-driven Action Localization in Videos

no code implementations12 May 2022 Shuo Yang, Xinxiao wu

Language-driven action localization in videos is a challenging task that involves not only visual-linguistic matching but also action boundary prediction.

Action Localization Frame +1

ELODI: Ensemble Logit Difference Inhibition for Positive-Congruent Training

no code implementations12 May 2022 Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, Stefano Soatto

We present a method to train a classification system that achieves paragon performance in both error rate and NFR, at the inference cost of a single model.

Reliable Label Correction is a Good Booster When Learning with Extremely Noisy Labels

no code implementations30 Apr 2022 Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You

This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.

Learning with noisy labels

CAFE: Learning to Condense Dataset by Aligning Features

1 code implementation3 Mar 2022 Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You

Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.

An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022

1 code implementation1 Mar 2022 Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi

Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area.

Graph Learning Link Prediction

Sample Efficiency of Data Augmentation Consistency Regularization

no code implementations24 Feb 2022 Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei

Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.

Data Augmentation

Semantically Contrastive Learning for Low-light Image Enhancement

1 code implementation13 Dec 2021 Dong Liang, Ling Li, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou

Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images.

Contrastive Learning Low-Light Image Enhancement +1

Does Preprocessing Help Training Over-parameterized Neural Networks?

no code implementations NeurIPS 2021 Zhao Song, Shuo Yang, Ruizhe Zhang

The classical training method requires paying $\Omega(mnd)$ cost for both forward computation and backward computation, where $m$ is the width of the neural network, and we are given $n$ training points in $d$-dimensional space.

Speeding up Deep Model Training by Sharing Weights and Then Unsharing

no code implementations8 Oct 2021 Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou

Our approach exploits the special structure of BERT that contains a stack of repeated modules (i. e., transformer encoders).

Objects in Semantic Topology

no code implementations ICLR 2022 Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu

A more realistic object detection paradigm, Open-World Object Detection, has arisen increasing research interests in the community recently.

Incremental Learning Language Modelling +1

Theoretical Analysis of Consistency Regularization with Limited Augmented Data

no code implementations29 Sep 2021 Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S Dhillon, Sujay Sanghavi, Qi Lei

Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.

Data Augmentation Generalization Bounds

Semi-TCL: Semi-Supervised Track Contrastive Representation Learning

no code implementations6 Jul 2021 Wei Li, Yuanjun Xiong, Shuo Yang, Mingze Xu, Yongxin Wang, Wei Xia

We design a new instance-to-track matching objective to learn appearance embedding that compares a candidate detection to the embedding of the tracks persisted in the tracker.

Multiple Object Tracking Representation Learning

Estimating Instance-dependent Label-noise Transition Matrix using DNNs

no code implementations27 May 2021 Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu

Traditionally, the transition from clean distribution to noisy distribution (i. e., clean label transition matrix) has been widely exploited to learn a clean label classifier by employing the noisy data.

Compatibility-aware Heterogeneous Visual Search

no code implementations CVPR 2021 Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, Stefano Soatto

Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery images.

Neural Architecture Search

An Efficient Multitask Neural Network for Face Alignment, Head Pose Estimation and Face Tracking

no code implementations13 Mar 2021 Jiahao Xia, Haimin Zhang, Shiping Wen, Shuo Yang, Min Xu

Moreover, we generate a cheap heatmap based on the face alignment result and fuse it with features to improve the performance of the other two tasks.

Face Alignment Face Detection +1

Linear Bandit Algorithms with Sublinear Time Complexity

no code implementations3 Mar 2021 Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi

We propose to accelerate existing linear bandit algorithms to achieve per-step time complexity sublinear in the number of arms $K$.

Combinatorial Bandits without Total Order for Arms

no code implementations3 Mar 2021 Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi

Specifically, we focus on a challenging setting where 1) the reward distribution of an arm depends on the set $s$ it is part of, and crucially 2) there is \textit{no total order} for the arms in $\mathcal{A}$.

Free Lunch for Few-shot Learning: Distribution Calibration

2 code implementations ICLR 2021 Shuo Yang, Lu Liu, Min Xu

In this paper, we calibrate the distribution of these few-sample classes by transferring statistics from the classes with sufficient examples, then an adequate number of examples can be sampled from the calibrated distribution to expand the inputs to the classifier.

Few-Shot Learning

Speeding up Deep Learning Training by Sharing Weights and Then Unsharing

no code implementations1 Jan 2021 Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou

It has been widely observed that increasing deep learning model sizes often leads to significant performance improvements on a variety of natural language processing and computer vision tasks.

Unsupervised Word Alignment via Cross-Lingual Contrastive Learning

no code implementations1 Jan 2021 Di wu, Liang Ding, Shuo Yang, DaCheng Tao

Recently, the performance of the neural word alignment models has exceeded that of statistical models.

Contrastive Learning Translation +1

Real-space construction of crystalline topological superconductors and insulators in 2D interacting fermionic systems

no code implementations31 Dec 2020 Jian-Hao Zhang, Shuo Yang, Yang Qi, Zheng-Cheng Gu

The construction and classification of crystalline symmetry protected topological (SPT) phases in interacting bosonic and fermionic systems have been intensively studied in the past few years.

Strongly Correlated Electrons Mesoscale and Nanoscale Physics Mathematical Physics Mathematical Physics

The ANTARES Astronomical Time-Domain Event Broker

no code implementations24 Nov 2020 Thomas Matheson, Carl Stubens, Nicholas Wolf, Chien-Hsiu Lee, Gautham Narayan, Abhijit Saha, Adam Scott, Monika Soraisam, Adam S. Bolton, Benjamin Hauger, David R. Silva, John Kececioglu, Carlos Scheidegger, Richard Snodgrass, Patrick D. Aleo, Eric Evans-Jacquez, Navdeep Singh, Zhe Wang, Shuo Yang, Zhenge Zhao

We describe the Arizona-NOIRLab Temporal Analysis and Response to Events System (ANTARES), a software instrument designed to process large-scale streams of astronomical time-domain alerts.

Instrumentation and Methods for Astrophysics

Positive-Congruent Training: Towards Regression-Free Model Updates

no code implementations CVPR 2021 Sijie Yan, Yuanjun Xiong, Kaustav Kundu, Shuo Yang, Siqi Deng, Meng Wang, Wei Xia, Stefano Soatto

Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error.

Image Classification

SMOT: Single-Shot Multi Object Tracking

1 code implementation30 Oct 2020 Wei Li, Yuanjun Xiong, Shuo Yang, Siqi Deng, Wei Xia

We combine this scheme with SSD detectors by proposing a novel tracking anchor assignment module.

Frame Multi-Object Tracking

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

2 code implementations CVPR 2020 Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun

When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.

Graph Matching Person Re-Identification

Adaptive Semantic-Visual Tree for Hierarchical Embeddings

no code implementations8 Mar 2020 Shuo Yang, Wei Yu, Ying Zheng, Hongxun Yao, Tao Mei

To solve this new problem, we propose a hierarchical adaptive semantic-visual tree (ASVT) to depict the architecture of merchandise categories, which evaluates semantic similarities between different semantic levels and visual similarities within the same semantic class simultaneously.

Image Retrieval

Single-View 3D Object Reconstruction from Shape Priors in Memory

no code implementations CVPR 2021 Shuo Yang, Min Xu, Haozhe Xie, Stuart Perry, Jiahao Xia

Inspired by this, we propose a novel method, named Mem3D, that explicitly constructs shape priors to supplement the missing information in the image.

3D Object Reconstruction 3D Reconstruction +3

Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space

no code implementations NeurIPS 2019 Shuo Yang, Yanyao Shen, Sujay Sanghavi

In this paper, we provide a new algorithm - Interaction Hard Thresholding (IntHT) which is the first one to provably accurately solve this problem in sub-quadratic time and space.

Learning Actions from Human Demonstration Video for Robotic Manipulation

no code implementations10 Sep 2019 Shuo Yang, Wei zhang, Weizhi Lu, Hesheng Wang, Yibin Li

However, the general video captioning methods focus more on the understanding of the full frame, lacking of consideration on the specific object of interests in robotic manipulations.

Frame Video Captioning

Region Proposal by Guided Anchoring

2 code implementations CVPR 2019 Jiaqi Wang, Kai Chen, Shuo Yang, Chen Change Loy, Dahua Lin

State-of-the-art detectors mostly rely on a dense anchoring scheme, where anchors are sampled uniformly over the spatial domain with a predefined set of scales and aspect ratios.

Object Detection Region Proposal

Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data

no code implementations2 Nov 2018 Shuo Yang

It also demonstrates the outstanding performance of these proposed models as well as other state of the art machine learning models when applied to medical research problems and other real-world large-scale systems, reveals the great potential of statistical relational learning for exploring the structured health-related data to facilitate medical research.

Medical Diagnosis Relational Reasoning

Integrating Episodic Memory into a Reinforcement Learning Agent using Reservoir Sampling

no code implementations ICLR 2018 Kenny J. Young, Richard S. Sutton, Shuo Yang

We suggest one advantage of this particular type of memory is the ability to easily assign credit to a specific state when remembered information is found to be useful.


Look at Boundary: A Boundary-Aware Face Alignment Algorithm

2 code implementations CVPR 2018 Wayne Wu, Chen Qian, Shuo Yang, Quan Wang, Yici Cai, Qiang Zhou

By utilising boundary information of 300-W dataset, our method achieves 3. 92% mean error with 0. 39% failure rate on COFW dataset, and 1. 25% mean error on AFLW-Full dataset.

Ranked #2 on Face Alignment on AFLW-19 (using extra training data)

Face Alignment Facial Landmark Detection

Optimizing Video Object Detection via a Scale-Time Lattice

1 code implementation CVPR 2018 Kai Chen, Jiaqi Wang, Shuo Yang, Xingcheng Zhang, Yuanjun Xiong, Chen Change Loy, Dahua Lin

High-performance object detection relies on expensive convolutional networks to compute features, often leading to significant challenges in applications, e. g. those that require detecting objects from video streams in real time.

Video Object Detection

Face Detection through Scale-Friendly Deep Convolutional Networks

no code implementations9 Jun 2017 Shuo Yang, Yuanjun Xiong, Chen Change Loy, Xiaoou Tang

Specifically, our method achieves 76. 4 average precision on the challenging WIDER FACE dataset and 96% recall rate on the FDDB dataset with 7 frames per second (fps) for 900 * 1300 input image.

Face Detection

Residual Attention Network for Image Classification

14 code implementations CVPR 2017 Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang

In this work, we propose "Residual Attention Network", a convolutional neural network using attention mechanism which can incorporate with state-of-art feed forward network architecture in an end-to-end training fashion.

Classification General Classification +2

Hand3D: Hand Pose Estimation using 3D Neural Network

no code implementations7 Apr 2017 Xiaoming Deng, Shuo Yang, yinda zhang, Ping Tan, Liang Chang, Hongan Wang

We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image.

3D Hand Pose Estimation

Faceness-Net: Face Detection through Deep Facial Part Responses

no code implementations29 Jan 2017 Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang

We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision.

Face Detection

Joint Hand Detection and Rotation Estimation by Using CNN

no code implementations8 Dec 2016 Xiaoming Deng, Ye Yuan, Yinda Zhang, Ping Tan, Liang Chang, Shuo Yang, Hongan Wang

Hand detection is essential for many hand related tasks, e. g. parsing hand pose, understanding gesture, which are extremely useful for robotics and human-computer interaction.

General Classification Hand Detection +1

Application of Statistical Relational Learning to Hybrid Recommendation Systems

no code implementations4 Jul 2016 Shuo Yang, Mohammed Korayem, Khalifeh Aljadda, Trey Grainger, Sriraam Natarajan

In this paper, we proposed a way to adapt the state-of-the-art in SRL learning approaches to construct a real hybrid recommendation system.

Collaborative Filtering Feature Engineering +2

From Facial Parts Responses to Face Detection: A Deep Learning Approach

2 code implementations ICCV 2015 Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang

In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding performance on FDDB, PASCAL Face, and AFW.

Face Detection

DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection

no code implementations11 Sep 2014 Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang

In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty.

Object Detection

Cannot find the paper you are looking for? You can Submit a new open access paper.