Search Results for author: Chao Chen

Found 166 papers, 61 papers with code

Detector Collapse: Backdooring Object Detection to Catastrophic Overload or Blindness

no code implementations17 Apr 2024 Hangtao Zhang, Shengshan Hu, Yichen Wang, Leo Yu Zhang, Ziqi Zhou, Xianlong Wang, Yanjun Zhang, Chao Chen

This paper is dedicated to bridging this gap by introducing Detector Collapse} (DC), a brand-new backdoor attack paradigm tailored for object detection.

Autonomous Driving Backdoor Attack +3

Robust Preference Optimization with Provable Noise Tolerance for LLMs

no code implementations5 Apr 2024 Xize Liang, Chao Chen, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye

The preference alignment aims to enable large language models (LLMs) to generate responses that conform to human values, which is essential for developing general AI systems.

Text Generation

Incorporating Domain Differential Equations into Graph Convolutional Networks to Lower Generalization Discrepancy

no code implementations1 Apr 2024 Yue Sun, Chao Chen, Yuesheng Xu, Sihong Xie, Rick S. Blum, Parv Venkitasubramaniam

We theoretically derive conditions where GCNs incorporating such domain differential equations are robust to mismatched training and testing data compared to baseline domain agnostic models.

Domain Generalization Time Series Prediction

Exploring Accurate 3D Phenotyping in Greenhouse through Neural Radiance Fields

no code implementations24 Mar 2024 Junhong Zhao, Wei Ying, Yaoqiang Pan, Zhenfeng Yi, Chao Chen, Kewei Hu, Hanwen Kang

This study investigates a learning-based phenotyping method using the Neural Radiance Field to achieve accurate in-situ phenotyping of pepper plants in greenhouse environments.

Plant Phenotyping Point Cloud Registration

Gradient-based Fuzzy System Optimisation via Automatic Differentiation -- FuzzyR as a Use Case

no code implementations18 Mar 2024 Chao Chen, Christian Wagner, Jonathan M. Garibaldi

Since their introduction, fuzzy sets and systems have become an important area of research known for its versatility in modelling, knowledge representation and reasoning, and increasingly its potential within the context explainable AI.

An Iterative Associative Memory Model for Empathetic Response Generation

no code implementations28 Feb 2024 Zhou Yang, Zhaochun Ren, Yufeng Wang, Chao Chen, Haizhou Sun, Xiaofei Zhu, Xiangwen Liao

Empathetic response generation is to comprehend the cognitive and emotional states in dialogue utterances and generate proper responses.

Empathetic Response Generation Response Generation

FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting

no code implementations8 Feb 2024 Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin

Current research predominantly relies on historical solar power data or numerical weather prediction in a single-modality format, ignoring the complementary information provided in different modalities.

An invariance constrained deep learning network for PDE discovery

no code implementations6 Feb 2024 Chao Chen, Hui Li, Xiaowei Jin

However, the discovery of governing equations from sparse data with high noise is still very challenging due to the difficulty of derivatives computation and the disturbance of noise.

Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection

no code implementations NeurIPS 2023 Chao Chen, Zhihang Fu, Kai Liu, Ze Chen, Mingyuan Tao, Jieping Ye

Most existing OOD detection methods focused on exploring advanced training skills or training-free tricks to prevent the model from yielding overconfident confidence score for unknown samples.

Out-of-Distribution Detection

Sketch and Refine: Towards Fast and Accurate Lane Detection

1 code implementation26 Jan 2024 Chao Chen, Jie Liu, Chang Zhou, Jie Tang, Gangshan Wu

At the "Sketch" stage, local directions of keypoints can be easily estimated by fast convolutional layers.

Lane Detection

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology

1 code implementation22 Dec 2023 Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna

Introducing interpretability and reasoning into Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) analysis is challenging, given the complexity of gigapixel slides.

Multiple Instance Learning

SO-NeRF: Active View Planning for NeRF using Surrogate Objectives

no code implementations6 Dec 2023 Keifer Lee, Shubham Gupta, Sunglyoung Kim, Bhargav Makwana, Chao Chen, Chen Feng

Despite the great success of Neural Radiance Fields (NeRF), its data-gathering process remains vague with only a general rule of thumb of sampling as densely as possible.

SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting

1 code implementation6 Dec 2023 Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin

Moreover, we approximate the sparse regression process using a blend of a two-layer MLP and an extensive codebook.

Computational Efficiency Quantization +6

A Cyclic Small Phase Theorem

no code implementations1 Dec 2023 Chao Chen, Wei Chen, Di Zhao, Jianqi Chen, Li Qiu

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems.

Scene Summarization: Clustering Scene Videos into Spatially Diverse Frames

no code implementations28 Nov 2023 Chao Chen, Mingzhi Zhu, Ankush Pratap Singh, Yu Yan, Felix Juefei Xu, Chen Feng

It aims to summarize a long video walkthrough of a scene into a small set of frames that are spatially diverse in the scene, which has many impotant applications, such as in surveillance, real estate, and robotics.

Clustering Scene Understanding +2

Phase Preservation of N-Port Networks under General Connections

no code implementations28 Nov 2023 Jianqi Chen, Wei Chen, Chao Chen, Li Qiu

In addition, the inverse operations of the considered connections, that is, network subtractions with correspondences are examined.

TopoSemiSeg: Enforcing Topological Consistency for Semi-Supervised Segmentation of Histopathology Images

1 code implementation28 Nov 2023 Meilong Xu, Xiaoling Hu, Saumya Gupta, Shahira Abousamra, Chao Chen

To address this issue, we propose TopoSemiSeg, the first semi-supervised method that learns the topological representation from unlabeled data.

Cycle Invariant Positional Encoding for Graph Representation Learning

1 code implementation24 Nov 2023 Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang

To efficiently encode the space of all cycles, we start with a cycle basis (i. e., a minimal set of cycles generating the cycle space) which we compute via the kernel of the 1-dimensional Hodge Laplacian of the input graph.

Graph Learning Graph Representation Learning

High-fidelity 3D Reconstruction of Plants using Neural Radiance Field

no code implementations7 Nov 2023 Kewei Hu, Ying WEI, Yaoqiang Pan, Hanwen Kang, Chao Chen

Recently, a promising development has emerged in the form of Neural Radiance Field (NeRF), a novel method that utilises neural density fields.

3D Reconstruction Plant Phenotyping

Attention-Enhancing Backdoor Attacks Against BERT-based Models

no code implementations23 Oct 2023 Weimin Lyu, Songzhu Zheng, Lu Pang, Haibin Ling, Chao Chen

Recent studies have revealed that \textit{Backdoor Attacks} can threaten the safety of natural language processing (NLP) models.

Sentiment Analysis Topic Classification

Learning to Abstain From Uninformative Data

no code implementations25 Sep 2023 Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen

Learning and decision-making in domains with naturally high noise-to-signal ratio, such as Finance or Healthcare, is often challenging, while the stakes are very high.

Decision Making Learning Theory

Client-side Gradient Inversion Against Federated Learning from Poisoning

no code implementations14 Sep 2023 Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shirui Pan, Kok-Leong Ong, Jun Zhang, Yang Xiang

For the first time, we show the feasibility of a client-side adversary with limited knowledge being able to recover the training samples from the aggregated global model.

Federated Learning

GridPull: Towards Scalability in Learning Implicit Representations from 3D Point Clouds

1 code implementation ICCV 2023 Chao Chen, Yu-Shen Liu, Zhizhong Han

However, these methods suffer from a slow inference due to the slow convergence of neural networks and the extensive calculation of distances to surface points, which limits them to small scale points.

Surface Reconstruction

Calibrating Uncertainty for Semi-Supervised Crowd Counting

no code implementations ICCV 2023 Chen Li, Xiaoling Hu, Shahira Abousamra, Chao Chen

A popular approach is to iteratively generate pseudo-labels for unlabeled data and add them to the training set.

Crowd Counting

Confidence Estimation Using Unlabeled Data

1 code implementation19 Jul 2023 Chen Li, Xiaoling Hu, Chao Chen

We stipulate that even with limited training labels, we can still reasonably approximate the confidence of model on unlabeled samples by inspecting the prediction consistency through the training process.

Active Learning Image Classification

Robust Ranking Explanations

no code implementations8 Jul 2023 Chao Chen, Chenghua Guo, Guixiang Ma, Ming Zeng, Xi Zhang, Sihong Xie

Robust explanations of machine learning models are critical to establish human trust in the models.

A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysis

no code implementations20 Jun 2023 Dongming Wu, Lulu Wen, Chao Chen, Zhaoshu Shi

To mitigate this problem, we propose a novel and simple counterfactual data augmentation method to generate opinion expressions with reversed sentiment polarity.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3

Topology-Aware Uncertainty for Image Segmentation

1 code implementation NeurIPS 2023 Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen

Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology.

Image Segmentation Segmentation +2

Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning

no code implementations21 Apr 2023 Hangtao Zhang, Zeming Yao, Leo Yu Zhang, Shengshan Hu, Chao Chen, Alan Liew, Zhetao Li

Federated learning (FL) is vulnerable to poisoning attacks, where adversaries corrupt the global aggregation results and cause denial-of-service (DoS).

Federated Learning Model Poisoning

SoftED: Metrics for Soft Evaluation of Time Series Event Detection

1 code implementation2 Apr 2023 Rebecca Salles, Janio Lima, Rafaelli Coutinho, Esther Pacitti, Florent Masseglia, Reza Akbarinia, Chao Chen, Jonathan Garibaldi, Fabio Porto, Eduardo Ogasawara

They improved event detection evaluation by associating events and their representative detections, incorporating temporal tolerance in over 36\% of experiments compared to the usual classification metrics.

Event Detection Time Series

Mask and Restore: Blind Backdoor Defense at Test Time with Masked Autoencoder

1 code implementation27 Mar 2023 Tao Sun, Lu Pang, Chao Chen, Haibin Ling

It detects possible triggers in the token space using image structural similarity and label consistency between the test image and MAE restorations.

backdoor defense Image Generation

Unsupervised Inference of Signed Distance Functions from Single Sparse Point Clouds without Learning Priors

1 code implementation CVPR 2023 Chao Chen, Yu-Shen Liu, Zhizhong Han

To resolve this issue, we present a neural network to directly infer SDFs from single sparse point clouds without using signed distance supervision, learned priors or even normals.

Surface Reconstruction

EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning

1 code implementation22 Mar 2023 Chao Chen, Haoyu Geng, Nianzu Yang, Xiaokang Yang, Junchi Yan

Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics directly in continuous time domain for its flexibility.

Dynamic Link Prediction Dynamic Node Classification +4

Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation

no code implementations ICCV 2023 Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna

We propose a novel approach to learn enhanced modality-agnostic representations by employing a meta-learning strategy in training, even when only limited full modality samples are available.

Brain Tumor Segmentation Image Generation +4

Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution

1 code implementation8 Feb 2023 Chao Chen, Haoyu Geng, Gang Zeng, Zhaobing Han, Hua Chai, Xiaokang Yang, Junchi Yan

Inductive one-bit matrix completion is motivated by modern applications such as recommender systems, where new users would appear at test stage with the ratings consisting of only ones and no zeros.

Matrix Completion Recommendation Systems

Rate-Perception Optimized Preprocessing for Video Coding

no code implementations25 Jan 2023 Chengqian Ma, Zhiqiang Wu, Chunlei Cai, Pengwei Zhang, Yi Wang, Long Zheng, Chao Chen, Quan Zhou

In the past decades, lots of progress have been done in the video compression field including traditional video codec and learning-based video codec.

Image Quality Assessment Video Compression

Provable Robust Saliency-based Explanations

no code implementations28 Dec 2022 Chao Chen, Chenghua Guo, Guixiang Ma, Ming Zeng, Xi Zhang, Sihong Xie

Robust explanations of machine learning models are critical to establishing human trust in the models.

FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning

1 code implementation1 Dec 2022 Yulei Qin, Xingyu Chen, Chao Chen, Yunhang Shen, Bo Ren, Yun Gu, Jie Yang, Chunhua Shen

Most existing methods focus on learning noise-robust models from web images while neglecting the performance drop caused by the differences between web domain and real-world domain.

Contrastive Learning Representation Learning

From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-Resolution

1 code implementation30 Nov 2022 Jie Liu, Chao Chen, Jie Tang, Gangshan Wu

In the fine area, we use an Intra-Patch Self-Attention (IPSA) module to model long-range pixel dependencies in a local patch, and then a $3\times3$ convolution is applied to process the finest details.

Image Super-Resolution

Backdoor Cleansing with Unlabeled Data

1 code implementation CVPR 2023 Lu Pang, Tao Sun, Haibin Ling, Chao Chen

In experiments, we show that our method, trained without labels, is on-par with state-of-the-art defense methods trained using labels.

Knowledge Distillation

ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement

1 code implementation25 Sep 2022 Dongli Tan, Jiang-Jiang Liu, Xingyu Chen, Chao Chen, Ruixin Zhang, Yunhang Shen, Shouhong Ding, Rongrong Ji

In this paper, we propose an efficient structure named Efficient Correspondence Transformer (ECO-TR) by finding correspondences in a coarse-to-fine manner, which significantly improves the efficiency of functional correspondence model.

Outlier Detection

Feedback Stability Analysis via Dissipativity with Dynamic Supply Rates

no code implementations17 Sep 2022 Sei Zhen Khong, Chao Chen

In this paper, we propose a notion of dissipativity with dynamic supply rates for nonlinear differential input-state-output equations via the use of auxiliary systems.


Deep Anomaly Detection and Search via Reinforcement Learning

no code implementations31 Aug 2022 Chao Chen, Dawei Wang, Feng Mao, Zongzhang Zhang, Yang Yu

Semi-supervised Anomaly Detection (AD) is a kind of data mining task which aims at learning features from partially-labeled datasets to help detect outliers.

Ensemble Learning Partially Labeled Datasets +4

Self-Supervised Visual Place Recognition by Mining Temporal and Feature Neighborhoods

no code implementations19 Aug 2022 Chao Chen, Xinhao Liu, Xuchu Xu, Yiming Li, Li Ding, Ruoyu Wang, Chen Feng

Inspired by noisy label learning, we propose a novel self-supervised framework named \textit{TF-VPR} that uses temporal neighborhoods and learnable feature neighborhoods to discover unknown spatial neighborhoods.

Data Augmentation Representation Learning +1

A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction

no code implementations9 Aug 2022 Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang, Chao Chen

Deep-learning-based clinical decision support using structured electronic health records (EHR) has been an active research area for predicting risks of mortality and diseases.

Mortality Prediction

HOB-CNN: Hallucination of Occluded Branches with a Convolutional Neural Network for 2D Fruit Trees

no code implementations28 Jul 2022 Zijue Chen, Keenan Granland, Rhys Newbury, Chao Chen

We further validated HOB-CNN against two different types of 2D trees, and HOB-CNN shows generalization across different trees and robustness under different occluded conditions.

Hallucination Position +1

UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View

2 code implementations ICCV 2023 Zequn Qin, Jingyu Chen, Chao Chen, Xiaozhi Chen, Xi Li

Bird's eye view (BEV) representation is a new perception formulation for autonomous driving, which is based on spatial fusion.

Autonomous Driving

Latent Partition Implicit with Surface Codes for 3D Representation

1 code implementation18 Jul 2022 Chao Chen, Yu-Shen Liu, Zhizhong Han

Our insight here is that both the part learning and the part blending can be conducted much easier in the latent space than in the spatial space.


MDOE: A Spatiotemporal Event Representation Considering the Magnitude and Density of Events

no code implementations RA-L 2022 Fuqiang Gu, Yong Lee, Yuan Zhuang, You Li, Jingbin Liu, Fangwen Yu, Ruiyuan Li, Chao Chen

Event-based sensors (e. g., DVS cameras) are capable of higher dynamic range, higher temporal resolution, lower time latency, and better power efficiency compared to conventional devices (e. g., RGB cameras).

On the Convergence of Optimizing Persistent-Homology-Based Losses

no code implementations6 Jun 2022 Yikai Zhang, Jiachen Yao, Yusu Wang, Chao Chen

Topological loss based on persistent homology has shown promise in various applications.

Learning Probabilistic Topological Representations Using Discrete Morse Theory

no code implementations3 Jun 2022 Xiaoling Hu, Dimitris Samaras, Chao Chen

We use discrete Morse theory and persistent homology to construct an one-parameter family of structures as the topological/structural representation space.

Image Segmentation Semantic Segmentation

Nuclear Norm Maximization Based Curiosity-Driven Learning

no code implementations21 May 2022 Chao Chen, Zijian Gao, Kele Xu, Sen yang, Yiying Li, Bo Ding, Dawei Feng, Huaimin Wang

To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in handy for pursuing the rewards in the future, such as encouraging the agent to visit novel states.

Atari Games

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

1 code implementation2 Apr 2022 Jing He, Yiyi Zhou, Qi Zhang, Jun Peng, Yunhang Shen, Xiaoshuai Sun, Chao Chen, Rongrong Ji

Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation.

Image Generation regression

End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation

1 code implementation1 Apr 2022 Mingrui Wu, Jiaxin Gu, Yunhang Shen, Mingbao Lin, Chao Chen, Xiaoshuai Sun

Extensive experiments on HICO-Det dataset demonstrate that our model discovers potential interactive pairs and enables the recognition of unseen HOIs.

Human-Object Interaction Detection Knowledge Distillation +4

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation

1 code implementation30 Mar 2022 Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang

User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data.

Dynamic Link Prediction Sequential Recommendation

SeqTR: A Simple yet Universal Network for Visual Grounding

3 code implementations30 Mar 2022 Chaoyang Zhu, Yiyi Zhou, Yunhang Shen, Gen Luo, Xingjia Pan, Mingbao Lin, Chao Chen, Liujuan Cao, Xiaoshuai Sun, Rongrong Ji

In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e. g., phrase localization, referring expression comprehension (REC) and segmentation (RES).

Referring Expression Referring Expression Comprehension +1

Discovering Governing Equations by Machine Learning implemented with Invariance

no code implementations29 Mar 2022 Chao Chen, Xiaowei Jin, Hui Li

The partial differential equation (PDE) plays a significantly important role in many fields of science and engineering.

BIG-bench Machine Learning

A Manifold View of Adversarial Risk

no code implementations24 Mar 2022 Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris Metaxas

Assuming data lies in a manifold, we investigate two new types of adversarial risk, the normal adversarial risk due to perturbation along normal direction, and the in-manifold adversarial risk due to perturbation within the manifold.

Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations

no code implementations CVPR 2022 Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna

In our method, a self-attention based Temporal Convolutional Network (TCN) is used to learn a representation that is most reflective of the disease trajectory.

severity prediction

A Topology-Attention ConvLSTM Network and Its Application to EM Images

no code implementations7 Feb 2022 Jiaqi Yang, Xiaoling Hu, Chao Chen, Chialing Tsai

We propose a novel TopologyAttention ConvLSTM Network (TACNet) for 3D image segmentation in order to achieve high structural accuracy for 3D segmentation tasks.

Image Segmentation Segmentation +1

Neural Approximation of Graph Topological Features

1 code implementation28 Jan 2022 Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods.

Graph Learning Graph Representation Learning +1

Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation

1 code implementation18 Jan 2022 Chao Chen, Yibing Zhan, Baosheng Yu, Liu Liu, Yong Luo, Bo Du

To address this problem, we propose Resistance Training using Prior Bias (RTPB) for the scene graph generation.

Graph Generation Unbiased Scene Graph Generation

DIFNet: Boosting Visual Information Flow for Image Captioning

no code implementations CVPR 2022 Mingrui Wu, Xuying Zhang, Xiaoshuai Sun, Yiyi Zhou, Chao Chen, Jiaxin Gu, Xing Sun, Rongrong Ji

Current Image captioning (IC) methods predict textual words sequentially based on the input visual information from the visual feature extractor and the partially generated sentence information.

Image Captioning Sentence

A General Framework for Debiasing in CTR Prediction

no code implementations6 Dec 2021 Wenjie Chu, Shen Li, Chao Chen, Longfei Xu, Hengbin Cui, Kaikui Liu

Most of the existing methods for debaising in click-through rate (CTR) prediction depend on an oversimplified assumption, i. e., the click probability is the product of observation probability and relevance probability.

Click-Through Rate Prediction

Multi-objective Explanations of GNN Predictions

no code implementations29 Nov 2021 Yifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, Sihong Xie

We design a user study to investigate such joint effects and use the findings to design a multi-objective optimization (MOO) algorithm to find Pareto optimal explanations that are well-balanced in simulatability and counterfactual.

counterfactual Decision Making +1

Federated Learning with Domain Generalization

no code implementations20 Nov 2021 Liling Zhang, Xinyu Lei, Yichun Shi, Hongyu Huang, Chao Chen

Federated Learning (FL) enables a group of clients to jointly train a machine learning model with the help of a centralized server.

Domain Generalization Federated Learning

R4: A Framework for Route Representation and Route Recommendation

no code implementations20 Oct 2021 Ran Cheng, Chao Chen, Longfei Xu, Shen Li, Lei Wang, Hengbin Cui, Kaikui Liu, Xiaolong Li

For user representation, we utilize a series of historical navigation to extract user preference.


Trigger Hunting with a Topological Prior for Trojan Detection

1 code implementation ICLR 2022 Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen

Despite their success and popularity, deep neural networks (DNNs) are vulnerable when facing backdoor attacks.

Cycle Representation Learning for Inductive Relation Prediction

1 code implementation6 Oct 2021 Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen

In this paper, we consider rules as cycles and show that the space of cycles has a unique structure based on the mathematics of algebraic topology.

Graph Representation Learning Inductive Relation Prediction +1

A Frequency-Domain Approach to Nonlinear Negative Imaginary Systems Analysis

no code implementations30 Sep 2021 Di Zhao, Chao Chen, Sei Zhen Khong

In this study, we extend the theory of negative imaginary (NI) systems to a nonlinear framework using a frequency-domain approach.

Learning to Abstain in the Presence of Uninformative Data

no code implementations29 Sep 2021 Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Yuriy Nevmyvaka, Chao Chen

Learning and decision making in domains with naturally high noise-to-signal ratios – such as Finance or Public Health – can be challenging and yet extremely important.

Decision Making Learning Theory

Self-learn to Explain Siamese Networks Robustly

no code implementations15 Sep 2021 Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie

Learning to compare two objects are essential in applications, such as digital forensics, face recognition, and brain network analysis, especially when labeled data is scarce and imbalanced.

Face Recognition Fairness +1

The Singular Angle of Nonlinear Systems

no code implementations3 Sep 2021 Chao Chen, Wei Chen, Di Zhao, Sei Zhen Khong, Li Qiu

It is, thus, different from the recently appeared nonlinear system phase which adopts the complexification of real-valued signals using the Hilbert transform.

Convolutional Block Design for Learned Fractional Downsampling

no code implementations20 May 2021 Li-Heng Chen, Christos G. Bampis, Zhi Li, Chao Chen, Alan C. Bovik

The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values.

SSIM Video Compression

Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning

1 code implementation AAAI 2021 Chao Chen, Dongsheng Li, Junchi Yan, Hanchi Huang, Xiaokang Yang

One-bit matrix completion is an important class of positiveunlabeled (PU) learning problems where the observations consist of only positive examples, eg, in top-N recommender systems.

Collaborative Ranking Matrix Completion +1

Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey

no code implementations13 May 2021 XiaoYu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, Yang Xiang

This survey presents the most recent findings of privacy attacks and defenses appeared in cloud-based neural network services.

Cloud Computing

TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer

1 code implementation13 May 2021 Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen

Characterization of breast parenchyma on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures.

Structure Guided Lane Detection

1 code implementation12 May 2021 Jinming Su, Chao Chen, Ke Zhang, Junfeng Luo, Xiaoming Wei, Xiaolin Wei

Next, multi-level structural constraints are used to improve the perception of lanes.

Autonomous Driving Lane Detection

NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering

no code implementations15 Apr 2021 Dongsheng Li, Haodong Liu, Chao Chen, Yingying Zhao, Stephen M. Chu, Bo Yang

In collaborative filtering (CF) algorithms, the optimal models are usually learned by globally minimizing the empirical risks averaged over all the observed data.

Collaborative Filtering Ensemble Learning

Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets

1 code implementation4 Apr 2021 Chao Chen, Catalina Raymond, Bill Speier, Xinyu Jin, Timothy F. Cloughesy, Dieter Enzmann, Benjamin M. Ellingson, Corey W. Arnold

To alleviate the data imbalance problem between normal tissues and the tumor regions, we introduce a local loss to improve the contribution of the tumor regions, which leads to better enhancement results on tumors.

Vocal Bursts Intensity Prediction

Topology-Aware Segmentation Using Discrete Morse Theory

no code implementations ICLR 2021 Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen

In the segmentation of fine-scale structures from natural and biomedical images, per-pixel accuracy is not the only metric of concern.

Image Segmentation Segmentation +1

Compiler-Guided Throughput Scheduling for Many-core Machines

no code implementations11 Mar 2021 Girish Mururu, Chao Chen, Chris Porter, Santosh Pande, Ada Gavrilovska

Typical schedulers in multi-tenancy environments make use of reactive, feedback-oriented mechanisms based on performance counters to avoid resource contention but suffer from detection lag and loss of performance.

Distributed, Parallel, and Cluster Computing

Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey

2 code implementations16 Feb 2021 Yuantian Miao, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, Yang Xiang

Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years.

BIG-bench Machine Learning

Stability of SGD: Tightness Analysis and Improved Bounds

no code implementations10 Feb 2021 Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami

This raises the question: is the stability analysis of [18] tight for smooth functions, and if not, for what kind of loss functions and data distributions can the stability analysis be improved?

Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach

1 code implementation9 Feb 2021 Yikai Zhang, Hui Qu, Qi Chang, Huidong Liu, Dimitris Metaxas, Chao Chen

A federatedGAN jointly trains a centralized generator and multiple private discriminators hosted at different sites.

Federated Learning

Ricci-GNN: Defending Against Structural Attacks Through a Geometric Approach

no code implementations1 Jan 2021 Ze Ye, Tengfei Ma, Chien-Chun Ni, Kin Sum Liu, Jie Gao, Chao Chen

We propose a novel GNN defense algorithm against structural attacks that maliciously modify graph topology.

Revisiting the Stability of Stochastic Gradient Descent: A Tightness Analysis

no code implementations1 Jan 2021 Yikai Zhang, Samuel Bald, Wenjia Zhang, Vamsi Pritham Pingali, Chao Chen, Mayank Goswami

We provide empirical evidence that this condition holds for several loss functions, and provide theoretical evidence that the known tight SGD stability bounds for convex and non-convex loss functions can be circumvented by HC loss functions, thus partially explaining the generalization of deep neural networks.

Exponential degradation

Unsupervised Learning of Fine Structure Generation for 3D Point Clouds by 2D Projections Matching

1 code implementation ICCV 2021 Chao Chen, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker

Our method pushes the neural network to generate a 3D point cloud whose 2D projections match the irregular point supervision from different view angles.

Point Cloud Generation

Localization in the Crowd with Topological Constraints

1 code implementation23 Dec 2020 Shahira Abousamra, Minh Hoai, Dimitris Samaras, Chao Chen

Due to various challenges, a localization method is prone to spatial semantic errors, i. e., predicting multiple dots within a same person or collapsing multiple dots in a cluttered region.

Crowd Counting

Phase of Nonlinear Systems

no code implementations30 Nov 2020 Chao Chen, Di Zhao, Wei Chen, Sei Zhen Khong, Li Qiu

A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems.

Error-Bounded Correction of Noisy Labels

3 code implementations ICML 2020 Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen

To be robust against label noise, many successful methods rely on the noisy classifiers (i. e., models trained on the noisy training data) to determine whether a label is trustworthy.

Image Classification

RCHOL: Randomized Cholesky Factorization for Solving SDD Linear Systems

2 code implementations16 Nov 2020 Chao Chen, Tianyu Liang, George Biros

We introduce a randomized algorithm, namely RCHOL, to construct an approximate Cholesky factorization for a given Laplacian matrix (a. k. a., graph Laplacian).

Numerical Analysis Mathematical Software Numerical Analysis

Minimizing Labeling Effort for Tree Skeleton Segmentation using an Automated Iterative Training Methodology

no code implementations16 Oct 2020 Keenan Granland, Rhys Newbury, David Ting, Chao Chen

It is shown that in our application, the new Automating-the-Loop method greatly reduces the labeling effort while producing comparable performance to both human-in-the-loop and complete manual labeling methods.

Segmentation Semantic Segmentation

Semantic Segmentation for Partially Occluded Apple Trees Based on Deep Learning

no code implementations14 Oct 2020 Zijue Chen, David Ting, Rhys Newbury, Chao Chen

DeepLabv3 outperforms the other models at Binary accuracy, Mean IoU and Boundary F1 score, but is surpassed by Pix2Pix (without discriminator) and U-Net in Occluded branch recall.

Generative Adversarial Network Hallucination +1

Deep Variational Instance Segmentation

1 code implementation NeurIPS 2020 Jialin Yuan, Chao Chen, Li Fuxin

Specifically, we propose a variational relaxation of instance segmentation as minimizing an optimization functional for a piecewise-constant segmentation problem, which can be used to train an FCN end-to-end.

Instance Segmentation Segmentation +1

Object Tracking by Least Spatiotemporal Searches

no code implementations18 Jul 2020 Zhiyong Yu, Lei Han, Chao Chen, Wenzhong Guo, Zhiwen Yu

This paper proposes a strategy named IHMs (Intermediate Searching at Heuristic Moments): each step we figure out which moment is the best to search according to a heuristic indicator, then at that moment search locations one by one in descending order of predicted appearing probabilities, until a search hits; iterate this step until we get the object's current location.

Management Object +1

Learn distributed GAN with Temporary Discriminators

1 code implementation ECCV 2020 Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas

Our proposed method tackles the challenge of training GAN in the federated learning manner: How to update the generator with a flow of temporary discriminators?

Federated Learning

DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images

no code implementations ICML 2020 Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker

To optimize 3D shape parameters, current renderers rely on pixel-wise losses between rendered images of 3D reconstructions and ground truth images from corresponding viewpoints.

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19

no code implementations28 Jun 2020 Abdelkader Nasreddine Belkacem, Sofia Ouhbi, Abderrahmane Lakas, Elhadj Benkhelifa, Chao Chen

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus.

Local Causal Structure Learning and its Discovery Between Type 2 Diabetes and Bone Mineral Density

no code implementations27 Jun 2020 Wei Wang, Gangqiang Hu, Bo Yuan, Shandong Ye, Chao Chen, YaYun Cui, Xi Zhang, Liting Qian

To illustrate the importance of prior knowledge, the result of the algorithm without prior knowledge is also investigated.

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment

1 code implementation30 May 2020 Chao Chen, Zhihong Chen, Xinyu Jin, Lanjuan Li, William Speier, Corey W. Arnold

However, training with the global image underutilizes discriminative local information, while providing extra annotations is expensive and subjective.

Age Estimation regression

Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data

1 code implementation CVPR 2020 Qi Chang, Hui Qu, Yikai Zhang, Mert Sabuncu, Chao Chen, Tong Zhang, Dimitris Metaxas

In this paper, we propose a data privacy-preserving and communication efficient distributed GAN learning framework named Distributed Asynchronized Discriminator GAN (AsynDGAN).

Privacy Preserving

Rigorous Explanation of Inference on Probabilistic Graphical Models

no code implementations21 Apr 2020 Yifei Liu, Chao Chen, Xi Zhang, Sihong Xie

There is no existing method to rigorously attribute the inference outcomes to the contributing factors of the graphical models.

Attribute Decision Making

Real-Time Fruit Recognition and Grasping Estimation for Autonomous Apple Harvesting

no code implementations30 Mar 2020 Hanwen Kang, Chao Chen

In this research, a fully neural network based visual perception framework for autonomous apple harvesting is proposed.

Instance Segmentation Robotic Grasping +1

Visual Perception and Modelling in Unstructured Orchard for Apple Harvesting Robots

no code implementations29 Dec 2019 Hanwen Kang, Chao Chen

This paper develops a framework of visual perception and modelling for robotic harvesting of fruits in the orchard environments.

Pose Estimation

HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation

1 code implementation27 Dec 2019 Chao Chen, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua

In particular, our proposed HoMM can perform arbitrary-order moment tensor matching, we show that the first-order HoMM is equivalent to Maximum Mean Discrepancy (MMD) and the second-order HoMM is equivalent to Correlation Alignment (CORAL).

Unsupervised Domain Adaptation

Fruit Detection, Segmentation and 3D Visualisation of Environments in Apple Orchards

no code implementations28 Nov 2019 Hanwen Kang, Chao Chen

The robustness and efficiency of the DaSNet-V2 in detection and segmentation are validated by the experiments in the real-environment of apple orchard.

Computational Efficiency Instance Segmentation +2

Point Cloud Processing via Recurrent Set Encoding

no code implementations25 Nov 2019 Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas

The spatial layout of the beams is regular, and this allows the beam features to be further fed into an efficient 2D convolutional neural network (CNN) for hierarchical feature aggregation.

SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation

no code implementations20 Nov 2019 Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua

In this paper, we propose a novel Semi-supervised Self-pace Adversarial Hashing method, named SSAH to solve the above problems in a unified framework.

Deep Hashing Generative Adversarial Network

A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network

no code implementations25 Sep 2019 Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang, Zhu Han

In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories.


Label Cleaning with Likelihood Ratio Test

no code implementations25 Sep 2019 Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen

To collect large scale annotated data, it is inevitable to introduce label noise, i. e., incorrect class labels.

Scalable Explanation of Inferences on Large Graphs

no code implementations13 Aug 2019 Chao Chen, Yifei Liu, Xi Zhang, Sihong Xie

Probabilistic inferences distill knowledge from graphs to aid human make important decisions.

ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences

no code implementations31 Jul 2019 Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker

Specifically, ShapeCaptioner aggregates the parts detected in multiple colored views using our novel part class specific aggregation to represent a 3D shape, and then, employs a sequence to sequence model to generate the caption.

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types

no code implementations9 Jul 2019 Shahira Abousamra, Le Hou, Rajarsi Gupta, Chao Chen, Dimitris Samaras, Tahsin Kurc, Rebecca Batiste, Tianhao Zhao, Shroyer Kenneth, Joel Saltz

This allows for a much larger training set, that reflects visual variability across multiple cancer types and thus training of a single network which can be automatically applied to each cancer type without human adjustment.

General Classification

DeepSquare: Boosting the Learning Power of Deep Convolutional Neural Networks with Elementwise Square Operators

no code implementations12 Jun 2019 Sheng Chen, Xu Wang, Chao Chen, Yifan Lu, Xijin Zhang, Linfu Wen

In this paper, we pursue very efficient neural network modules which can significantly boost the learning power of deep convolutional neural networks with negligible extra computational cost.

Efficient Neural Network

Topology-Preserving Deep Image Segmentation

2 code implementations NeurIPS 2019 Xiaoling Hu, Li Fuxin, Dimitris Samaras, Chao Chen

Segmentation algorithms are prone to make topological errors on fine-scale structures, e. g., broken connections.

Image Segmentation Segmentation +1

Automatic Long-Term Deception Detection in Group Interaction Videos

no code implementations15 May 2019 Chongyang Bai, Maksim Bolonkin, Judee Burgoon, Chao Chen, Norah Dunbar, Bharat Singh, V. S. Subrahmanian, Zhe Wu

Most work on automated deception detection (ADD) in video has two restrictions: (i) it focuses on a video of one person, and (ii) it focuses on a single act of deception in a one or two minute video.

Deception Detection

Strain engineering of epitaxial oxide heterostructures beyond substrate limitations

no code implementations3 May 2019 Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu

The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.

Materials Science

Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation

no code implementations13 Apr 2019 Chao Chen, Zhihang Fu, Zhihong Chen, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua

Recent advances in unsupervised domain adaptation mainly focus on learning shared representations by global distribution alignment without considering class information across domains.

Unsupervised Domain Adaptation

PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication

3 code implementations6 Mar 2019 Ruoxi Wang, Chao Chen, Jonghyun Lee, Eric Darve

We introduce a parallel method that provably requires $O(N)$ operations to reduce the computation cost.

Mathematical Software

An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations

1 code implementation9 Jan 2019 Léopold Cambier, Chao Chen, Erik G Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, Eric Darve

We evaluate the algorithm on some large problems show it exhibits near-linear scaling.

Numerical Analysis

Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions

no code implementations11 Dec 2018 Weikai Chen, Xiaoguang Han, Guanbin Li, Chao Chen, Jun Xing, Yajie Zhao, Hao Li

Three-dimensional object recognition has recently achieved great progress thanks to the development of effective point cloud-based learning frameworks, such as PointNet and its extensions.

3D Object Recognition

Collaborative Filtering with Stability

no code implementations6 Nov 2018 Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen M. Chu

Collaborative filtering (CF) is a popular technique in today's recommender systems, and matrix approximation-based CF methods have achieved great success in both rating prediction and top-N recommendation tasks.

Collaborative Filtering Recommendation Systems

Parameter Transfer Extreme Learning Machine based on Projective Model

1 code implementation4 Sep 2018 Chao Chen, Boyuan Jiang, Xinyu Jin

Unlike the existing parameter transfer approaches, which incorporate the source model information into the target by regularizing the di erence between the source and target domain parameters, an intuitively appealing projective-model is proposed to bridge the source and target model parameters.

Domain Adaptation feature selection +1

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation

1 code implementation28 Aug 2018 Chao Chen, Zhihong Chen, Boyuan Jiang, Xinyu Jin

Recently, considerable effort has been devoted to deep domain adaptation in computer vision and machine learning communities.

Domain Adaptation

A Topological Regularizer for Classifiers via Persistent Homology

no code implementations27 Jun 2018 Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang

In particular, our measurement of topological complexity incorporates the importance of topological features (e. g., connected components, handles, and so on) in a meaningful manner, and provides a direct control over spurious topological structures.

An Approximate Bayesian Long Short-Term Memory Algorithm for Outlier Detection

no code implementations23 Dec 2017 Chao Chen, Xiao Lin, Gabriel Terejanu

In this study, we propose an approximate estimation of the weights uncertainty using Ensemble Kalman Filter, which is easily scalable to a large number of weights.

Outlier Detection

Mixture-Rank Matrix Approximation for Collaborative Filtering

1 code implementation NeurIPS 2017 Dongsheng Li, Chao Chen, Wei Liu, Tun Lu, Ning Gu, Stephen Chu

However, our studies show that submatrices with different ranks could coexist in the same user-item rating matrix, so that approximations with fixed ranks cannot perfectly describe the internal structures of the rating matrix, therefore leading to inferior recommendation accuracy.

Collaborative Filtering

Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection

no code implementations31 Oct 2017 Changzhe Jiao, Chao Chen, Ronald G. McGarvey, Stephanie Bohlman, Licheng Jiao, Alina Zare

The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented.

Multiple Instance Learning

Partial Membership Latent Dirichlet Allocation

2 code implementations28 Dec 2016 Chao Chen, Alina Zare, Huy Trinh, Gbeng Omotara, J. Tory Cobb, Timotius Lagaunne

Topic models (e. g., pLSA, LDA, sLDA) have been widely used for segmenting imagery.

Topic Models

Partial Membership Latent Dirichlet Allocation

2 code implementations9 Nov 2015 Chao Chen, Alina Zare, J. Tory Cobb

Topic models (e. g., pLSA, LDA, SLDA) have been widely used for segmenting imagery.

Topic Models

Mode Estimation for High Dimensional Discrete Tree Graphical Models

no code implementations NeurIPS 2014 Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao

Though the mode finding problem is generally intractable in high dimensions, this paper unveils that, if the distribution can be approximated well by a tree graphical model, mode characterization is significantly easier.

Vocal Bursts Intensity Prediction

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