1 code implementation • ECCV 2020 • Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng, Xin Yuan
This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.
no code implementations • EMNLP 2020 • Zhengjue Wang, Zhibin Duan, Hao Zhang, Chaojie Wang, Long Tian, Bo Chen, Mingyuan Zhou
Abstractive document summarization is a comprehensive task including document understanding and summary generation, in which area Transformer-based models have achieved the state-of-the-art performance.
no code implementations • 29 Apr 2024 • Bo Chen, Shoukang Hu, Qi Chen, Chenpeng Du, Ran Yi, Yanmin Qian, Xie Chen
We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 3$\sim$5 minute video for training material, in comparison with previous 2D and 3D NeRF-based modeling frameworks which require hours of training and seconds of rendering per frame.
no code implementations • 28 Apr 2024 • Huanshuo Liu, Bo Chen, Menghui Zhu, Jianghao Lin, Jiarui Qin, Yang Yang, Hao Zhang, Ruiming Tang
Specifically, a knowledge base, consisting of a retrieval-oriented embedding layer and a knowledge encoder, is designed to preserve and imitate the retrieved & aggregated representations in a decomposition-reconstruction paradigm.
2 code implementations • 12 Apr 2024 • Yuqing Cheng, Bo Chen, Fanjin Zhang, Jie Tang
Therefore, we present BOND, which bootstraps the local and global informative signals to promote each other in an end-to-end regime.
no code implementations • 25 Mar 2024 • Yunjia Xi, Weiwen Liu, Jianghao Lin, Chuhan Wu, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu
The rise of large language models (LLMs) has opened new opportunities in Recommender Systems (RSs) by enhancing user behavior modeling and content understanding.
no code implementations • 25 Mar 2024 • Wei Luo, Bo Chen
This paper presents a novel quantization rectifier (QR) method for image compression that leverages image feature correlation to mitigate the impact of quantization.
2 code implementations • 19 Mar 2024 • Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang
Secondly, the existing literature's lack of detailed analysis on selection attributes, based on large-scale datasets and a thorough comparison among selection techniques and DRS backbones, restricts the generalizability of findings and impedes deployment on DRS.
1 code implementation • 8 Mar 2024 • Muyao Wang, Wenchao Chen, Bo Chen
The forecasting of Multivariate Time Series (MTS) has long been an important but challenging task.
1 code implementation • 6 Mar 2024 • Zequn Zeng, Yan Xie, Hao Zhang, Chiyu Chen, Zhengjue Wang, Bo Chen
The framework of MeaCap achieves the state-of-the-art performance on a series of zero-shot IC settings.
1 code implementation • 6 Mar 2024 • Hangyu Wang, Jianghao Lin, Bo Chen, Yang Yang, Ruiming Tang, Weinan Zhang, Yong Yu
However, in order to protect user privacy and optimize utility, it is also crucial for LLMRec to intentionally forget specific user data, which is generally referred to as recommendation unlearning.
no code implementations • 24 Feb 2024 • Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, Jie Tang
We envisage that OAG-Bench can serve as a common ground for the community to evaluate and compare algorithms in academic graph mining, thereby accelerating algorithm development and advancement in this field.
1 code implementation • 31 Jan 2024 • Hongpeng Guo, Haotian Gu, Xiaoyang Wang, Bo Chen, Eun Kyung Lee, Tamar Eilam, Deming Chen, Klara Nahrstedt
Federated learning (FL) is a machine learning paradigm that allows multiple clients to collaboratively train a shared model while keeping their data on-premise.
no code implementations • 11 Jan 2024 • Bo Chen, Xingyi Cheng, Pan Li, Yangli-ao Geng, Jing Gong, Shen Li, Zhilei Bei, Xu Tan, Boyan Wang, Xin Zeng, Chiming Liu, Aohan Zeng, Yuxiao Dong, Jie Tang, Le Song
We propose a unified protein language model, xTrimoPGLM, to address these two types of tasks simultaneously through an innovative pre-training framework.
no code implementations • 10 Jan 2024 • JianQiao Sun, Yudi Su, Hao Zhang, Ziheng Cheng, Zequn Zeng, Zhengjue Wang, Bo Chen, Xin Yuan
To address these problems, in this paper, we propose a novel VC pipeline to generate captions directly from the compressed measurement, which can be captured by a snapshot compressive sensing camera and we dub our model SnapCap.
no code implementations • 31 Dec 2023 • Chaojie Wang, Yishi Xu, Zhong Peng, Chenxi Zhang, Bo Chen, Xinrun Wang, Lei Feng, Bo An
Large language models (LLMs) have exhibited remarkable performance on various natural language processing (NLP) tasks, especially for question answering.
no code implementations • 22 Dec 2023 • Yin Luo, Qingchao Kong, Nan Xu, Jia Cao, Bao Hao, Baoyu Qu, Bo Chen, Chao Zhu, Chenyang Zhao, Donglei Zhang, Fan Feng, Feifei Zhao, Hailong Sun, Hanxuan Yang, Haojun Pan, Hongyu Liu, Jianbin Guo, Jiangtao Du, Jingyi Wang, Junfeng Li, Lei Sun, Liduo Liu, Lifeng Dong, Lili Liu, Lin Wang, Liwen Zhang, Minzheng Wang, Pin Wang, Ping Yu, Qingxiao Li, Rui Yan, Rui Zou, Ruiqun Li, Taiwen Huang, Xiaodong Wang, Xiaofei Wu, Xin Peng, Xina Zhang, Xing Fang, Xinglin Xiao, Yanni Hao, Yao Dong, Yigang Wang, Ying Liu, Yongyu Jiang, Yungan Wang, Yuqi Wang, Zhangsheng Wang, Zhaoxin Yu, Zhen Luo, Wenji Mao, Lei Wang, Dajun Zeng
As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artificial general intelligence.
1 code implementation • 30 Oct 2023 • Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu
In this paper, we propose to conduct Fine-grained feature-level ALignment between ID-based Models and Pretrained Language Models (FLIP) for CTR prediction.
1 code implementation • NeurIPS 2023 • Ruiying Lu, Yujie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu
First, instead of learning the continuous representations, we preserve the typical normal patterns as discrete iconic prototypes, and confirm the importance of Vector Quantization in preventing the model from falling into the shortcut.
no code implementations • 13 Oct 2023 • Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang
Traditional CTR models convert the multi-field categorical data into ID features via one-hot encoding, and extract the collaborative signals among features.
no code implementations • 21 Sep 2023 • Alexander Benvenuti, Calvin Hawkins, Brandon Fallin, Bo Chen, Brendan Bialy, Miriam Dennis, Matthew Hale
We then develop an algorithm for the numerical computation of the performance loss due to privacy on a case-by-case basis.
1 code implementation • 12 Sep 2023 • Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang
Secondly, due to the distribution differences among domains, the utilization of static parameters in existing methods limits their flexibility to adapt to diverse domains.
no code implementations • 5 Sep 2023 • Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang
To address these limitations, we propose a Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendations (HierRec), which perceives implicit patterns adaptively and conducts explicit and implicit scenario modeling jointly.
1 code implementation • 22 Aug 2023 • Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang
With large language models (LLMs) achieving remarkable breakthroughs in natural language processing (NLP) domains, LLM-enhanced recommender systems have received much attention and have been actively explored currently.
1 code implementation • 18 Aug 2023 • Bo Chen, Chenyu Wang, Weipeng Li, Haiyang Fu
Results illustrate the advantages of Decoder-DeepONet and Multi-Decoder-DeepONet in handling unaligned observation data and showcase their potentials in improving prediction accuracy.
no code implementations • 14 Aug 2023 • Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
In the domain of streaming recommender systems, conventional methods for addressing new user IDs or item IDs typically involve assigning initial ID embeddings randomly.
no code implementations • ICCV 2023 • Long Tian, Jingyi Feng, Wenchao Chen, Xiaoqiang Chai, Liming Wang, Xiyang Liu, Bo Chen
Transductive Few-Shot Learning (TFSL) has recently attracted increasing attention since it typically outperforms its inductive peer by leveraging statistics of query samples.
1 code implementation • ICCV 2023 • Miaoge Li, Dongsheng Wang, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen, Mingyuan Zhou
We find that by formulating the multi-label classification as a CT problem, we can exploit the interactions between the image and label efficiently by minimizing the bidirectional CT cost.
1 code implementation • 19 Jun 2023 • Yunjia Xi, Weiwen Liu, Jianghao Lin, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu
In this work, we propose an Open-World Knowledge Augmented Recommendation Framework with Large Language Models, dubbed KAR, to acquire two types of external knowledge from LLMs -- the reasoning knowledge on user preferences and the factual knowledge on items.
1 code implementation • 9 Jun 2023 • Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Hao Zhang, Yong liu, Chuhan Wu, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang
In this paper, we conduct a comprehensive survey on this research direction from the perspective of the whole pipeline in real-world recommender systems.
no code implementations • 5 Jun 2023 • Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang
Both tabular data and converted textual data are regarded as two different modalities and are separately fed into the collaborative CTR model and pre-trained language model.
no code implementations • 17 Apr 2023 • Zhongyao Hu, Bo Chen, Rusheng Wang, Li Yu
A posterior-based SET mechanism is proposed, which determines whether to transmit data by the effect of the measurement on the posterior estimate.
no code implementations • 16 Mar 2023 • Xinyang Liu, Dongsheng Wang, Miaoge Li, Zhibin Duan, Yishi Xu, Bo Chen, Mingyuan Zhou
For downstream applications of vision-language pre-trained models, there has been significant interest in constructing effective prompts.
no code implementations • 7 Mar 2023 • Hongan Wei, Jiaqi Liu, Bo Chen, Liqun Lin, Weiling Chen, Tiesong Zhao
Second, we extend our 2D-JND model to SJND by jointly exploiting latitude projection and field of view during 360$^\circ$ display.
1 code implementation • 4 Mar 2023 • Wei Guo, Chang Meng, Enming Yuan, ZhiCheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang
However, it is challenging to explore multi-behavior data due to the unbalanced data distribution and sparse target behavior, which lead to the inadequate modeling of high-order relations when treating multi-behavior data ''as features'' and gradient conflict in multitask learning when treating multi-behavior data ''as labels''.
1 code implementation • CVPR 2023 • Zequn Zeng, Hao Zhang, Zhengjue Wang, Ruiying Lu, Dongsheng Wang, Bo Chen
Zero-shot capability has been considered as a new revolution of deep learning, letting machines work on tasks without curated training data.
1 code implementation • 23 Feb 2023 • Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, Xiaoyan Li, Yuxiao Dong, Jie Tang
The toolkit is at https://github. com/THUDM/WhoIsWho.
no code implementations • 7 Feb 2023 • Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang
Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual improvement among tasks considering their shared knowledge.
no code implementations • 6 Feb 2023 • Wangzhuo Yang, Bo Chen, Yijun Shen, Jiong Liu, Li Yu
To overcome these challenges, a multi-layer multi-fusion strategy framework is proposed in this paper, i. e., the server adopts the network layer parameters of each client upload model as the basic unit of fusion for information-sharing calculation.
1 code implementation • 20 Jan 2023 • Bo Chen, Calvin Hawkins, Mustafa O. Karabag, Cyrus Neary, Matthew Hale, Ufuk Topcu
We synthesize policies that are robust to privacy by reducing the value of the total correlation.
no code implementations • 19 Jan 2023 • Zheming Wang, Raphaël M. Jungers, Mihály Petreczky, Bo Chen, Li Yu
In this paper, we propose an algorithm for deciding stability of switched linear systems under arbitrary switching based purely on observed output data.
no code implementations • 19 Jan 2023 • Shan Wu, Chunlei Xin, Bo Chen, Xianpei Han, Le Sun
Since the meaning representations are detailed and accurate annotations which express fine-grained sequence-level semtantics, it is usually hard to train discriminative semantic parsers via Maximum Likelihood Estimation (MLE) in an autoregressive fashion.
no code implementations • 30 Dec 2022 • Bo Chen, Pindi Weng, Daniel W. C. Ho, Li Yu
This paper is concerned with the problem of secure multi-sensors fusion estimation for cyber-physical systems, where sensor measurements may be tampered with by false data injection (FDI) attacks.
no code implementations • 27 Dec 2022 • Bo Chen, Zhiwei Hu, Zhilong Ji, Jinfeng Bai, WangMeng Zuo
The main challenge of this task is to understand the visual and linguistic content simultaneously and to find the referred object accurately among all instances in the image.
1 code implementation • 27 Dec 2022 • Zhiwei Hu, Bo Chen, Yuan Gao, Zhilong Ji, Jinfeng Bai
The task of referring video object segmentation aims to segment the object in the frames of a given video to which the referring expressions refer.
1 code implementation • 20 Dec 2022 • Rodrigo Hernangómez, Alexandros Palaios, Cara Watermann, Daniel Schäufele, Philipp Geuer, Rafail Ismayilov, Mohammad Parvini, Anton Krause, Martin Kasparick, Thomas Neugebauer, Oscar D. Ramos-Cantor, Hugues Tchouankem, Jose Leon Calvo, Bo Chen, Gerhard Fettweis, Sławomir Stańczak
This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+), together with detailed information about the two captured datasets.
1 code implementation • 26 Oct 2022 • Hengyu Zhang, Enming Yuan, Wei Guo, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang
Sequential recommendation (SR) plays an important role in personalized recommender systems because it captures dynamic and diverse preferences from users' real-time increasing behaviors.
2 code implementations • 18 Oct 2022 • Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, JinXing Liu, Zhenhua Dong, Ruiming Tang
FE-Block module performs fine-grained and early feature interactions to capture the interactive signals between user and item towers explicitly and CIR module leverages a contrastive interaction regularization to further enhance the interactions implicitly.
1 code implementation • 16 Oct 2022 • Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou
With the tree-likeness property of hyperbolic space, the underlying semantic hierarchy among words and topics can be better exploited to mine more interpretable topics.
no code implementations • 20 Sep 2022 • Bo Chen, Jiayi Liu, Mieradilijiang Maimaiti, Xing Gao, Ji Zhang
A multi-aspect attentive network is proposed to automatically attend to different aspects in a review and ensure most of the issues are tackled.
1 code implementation • 20 Sep 2022 • Dongsheng Wang, Yishi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou
We propose a Bayesian generative model for incorporating prior domain knowledge into hierarchical topic modeling.
no code implementations • 12 Sep 2022 • Dongsheng Wang, Chaojie Wang, Bo Chen, Mingyuan Zhou
To build recommender systems that not only consider user-item interactions represented as ordinal variables, but also exploit the social network describing the relationships between the users, we develop a hierarchical Bayesian model termed ordinal graph factor analysis (OGFA), which jointly models user-item and user-user interactions.
no code implementations • 24 Aug 2022 • Liang Du, Xiaoqing Ye, Xiao Tan, Edward Johns, Bo Chen, Errui Ding, xiangyang xue, Jianfeng Feng
A feasible method is investigated to construct conceptual scenes without external datasets.
no code implementations • 11 Aug 2022 • Yuxiang Shi, Yue Ding, Bo Chen, YuYang Huang, Yule Wang, Ruiming Tang, Dong Wang
In this paper, we propose a Task aligned Meta-learning based Augmented Graph (TMAG) to address cold-start recommendation.
no code implementations • 3 Aug 2022 • Rusheng Wang, Bo Chen, Zhongyao Hu, Li Yu
This paper studies the event-triggered distributed fusion estimation problems for a class of nonlinear networked multisensor fusion systems without noise statistical characteristics.
no code implementations • 1 Jun 2022 • Yuchen Zhang, Bo Chen, Li Yu, Daniel W. C. Ho
By merging these subsystem-level stability conditions and the optimization-based estimator gain design, the distributed, stable and optimal estimators are proposed.
no code implementations • 4 Apr 2022 • Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang
Deep recommender systems (DRS) are critical for current commercial online service providers, which address the issue of information overload by recommending items that are tailored to the user's interests and preferences.
no code implementations • 9 Mar 2022 • Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Ng, Tat-Jun Chin
In this paper, we consider the scenario where retraining can be done on the server side based on a copy of the DNN model, with only the necessary data transmitted to the edge to update the deployed model.
2 code implementations • ICLR 2022 • Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou
This paper introduces a new topic-modeling framework where each document is viewed as a set of word embedding vectors and each topic is modeled as an embedding vector in the same embedding space.
no code implementations • 2 Mar 2022 • Daqi Liu, Alvaro Parra, Yasir Latif, Bo Chen, Tat-Jun Chin, Ian Reid
Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range.
no code implementations • 1 Mar 2022 • Ruiying Lu, Ziheng Cheng, Bo Chen, Xin Yuan
Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compresses them into a single measurement.
1 code implementation • 14 Feb 2022 • Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang
As the final stage of the multi-stage recommender system (MRS), re-ranking directly affects user experience and satisfaction by rearranging the input ranking lists, and thereby plays a critical role in MRS. With the advances in deep learning, neural re-ranking has become a trending topic and been widely applied in industrial applications.
no code implementations • 8 Feb 2022 • Guhong Nie, Lirui Xiao, Menglong Zhu, Dongliang Chu, Yue Shen, Peng Li, Kang Yang, Li Du, Bo Chen
For binary neural networks (BNNs) to become the mainstream on-device computer vision algorithm, they must achieve a superior speed-vs-accuracy tradeoff than 8-bit quantization and establish a similar degree of general applicability in vision tasks.
1 code implementation • 7 Feb 2022 • Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
This paper introduces a graph generative process to model how the observed edges are generated by aggregating the node interactions over a set of overlapping node communities, each of which contributes to the edges via a logical OR mechanism.
no code implementations • 3 Dec 2021 • Andrew Du, Yee Wei Law, Michele Sasdelli, Bo Chen, Ken Clarke, Michael Brown, Tat-Jun Chin
In fact, advanced EO satellites perform deep learning-based cloud detection on board the satellites and downlink only clear-sky data to save precious bandwidth.
no code implementations • 30 Nov 2021 • Wei Guo, Can Zhang, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang
With the help of two novel CNN-based multi-interest extractors, self-supervision signals are discovered with full considerations of different interest representations (point-wise and union-wise), interest dependencies (short-range and long-range), and interest correlations (inter-item and intra-item).
1 code implementation • 5 Nov 2021 • Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu
To address these three issues mentioned above, we propose Automatic Interaction Machine (AIM) with three core components, namely, Feature Interaction Search (FIS), Interaction Function Search (IFS) and Embedding Dimension Search (EDS), to select significant feature interactions, appropriate interaction functions and necessary embedding dimensions automatically in a unified framework.
2 code implementations • Proceedings of the 30th ACM International Conference on Information & Knowledge Management 2021 • Bo Chen, Yichao Wang, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He
The state-of-the-art deep CTR models with parallel structure (e. g., DCN) learn explicit and implicit feature interactions through independent parallel networks.
1 code implementation • NeurIPS 2021 • Zhibin Duan, Yishi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou
Existing deep hierarchical topic models are able to extract semantically meaningful topics from a text corpus in an unsupervised manner and automatically organize them into a topic hierarchy.
no code implementations • 27 Oct 2021 • Zhongyao Hu, Bo Chen, Yuchen Zhang, Li Yu
When considering linear dynamic systems, a conservative estimation error covariance with adjustable parameters is constructed by matrix inequality, and then an optimal filter gain is derived by minimizing its trace.
1 code implementation • 22 Oct 2021 • Bo Chen, Tat-Jun Chin, Marius Klimavicius
State-of-the-art (SOTA) object pose estimators take a two-stage approach, where the first stage predicts 2D landmarks using a deep network and the second stage solves for 6DOF pose from 2D-3D correspondences.
Ranked #2 on 6D Pose Estimation using RGB on YCB-Video
1 code implementation • NeurIPS 2021 • Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou
Existing methods for unsupervised domain adaptation often rely on minimizing some statistical distance between the source and target samples in the latent space.
no code implementations • 13 Oct 2021 • Zhongyao Hu, Bo Chen, Wen-An Zhang, Li Yu
For this criterion, it is proved that the fusion results are not affected by the fusion structure, and thus the fusion performance can be guaranteed.
no code implementations • 29 Sep 2021 • Shujian Zhang, Zhibin Duan, Huangjie Zheng, Pengcheng He, Bo Chen, Weizhu Chen, Mingyuan Zhou
Crossformer with states sharing not only provides the desired cross-layer guidance and regularization but also reduces the memory requirement.
no code implementations • 29 Sep 2021 • Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
In this paper, we introduce a relational graph generative process to model how the observed edges are generated by aggregating the node interactions over multiple overlapping node communities, each of which represents a particular type of relation that contributes to the edges via a logical OR mechanism.
no code implementations • 28 Sep 2021 • Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang
In this paper, we propose a novel time-aware sequential recommendation framework called Social Temporal Excitation Networks (STEN), which introduces temporal point processes to model the fine-grained impact of friends' behaviors on the user s dynamic interests in an event-level direct paradigm.
1 code implementation • 11 Sep 2021 • Ruiying Lu, Bo Chen, Guanliang Liu, Ziheng Cheng, Mu Qiao, Xin Yuan
In this paper, we propose an optical flow-aided recurrent neural network for dual video SCI systems, which provides high-quality decoding in seconds.
1 code implementation • 26 Aug 2021 • Andrew Du, Bo Chen, Tat-Jun Chin, Yee Wei Law, Michele Sasdelli, Ramesh Rajasegaran, Dillon Campbell
In this work, we demonstrate one of the first efforts on physical adversarial attacks on aerial imagery, whereby adversarial patches were optimised, fabricated and installed on or near target objects (cars) to significantly reduce the efficacy of an object detector applied on overhead images.
2 code implementations • 17 Aug 2021 • Bo Chen, Jing Zhang, Xiaokang Zhang, Yuxiao Dong, Jian Song, Peng Zhang, Kaibo Xu, Evgeny Kharlamov, Jie Tang
To achieve the contrastive objective, we design a graph neural network encoder that can infer and further remove suspicious links during message passing, as well as learn the global context of the input graph.
no code implementations • 10 Aug 2021 • Chao Duan, Guna Bharati, Pratyush Chakraborty, Bo Chen, Takashi Nishikawa, Adilson E. Motter
We report on a real-time demand response experiment with 100 controllable devices.
1 code implementation • ACL 2021 • Zhibin Duan, Hao Zhang, Chaojie Wang, Zhengjue Wang, Bo Chen, Mingyuan Zhou
As a result, the backbone learns the shared knowledge among all clusters while modulated weights extract the cluster-specific features.
no code implementations • 19 Jul 2021 • Ning Bian, Xianpei Han, Bo Chen, Hongyu Lin, Ben He, Le Sun
In this paper, we propose a new framework for unsupervised MRC.
1 code implementation • 30 Jun 2021 • Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou
However, they often assume in the prior that the topics at each layer are independently drawn from the Dirichlet distribution, ignoring the dependencies between the topics both at the same layer and across different layers.
no code implementations • 15 Jun 2021 • Dung Anh Hoang, Bo Chen, Tat-Jun Chin
We also provide evaluations with state-of-the-art methods in object detection and instance segmentation as a benchmark for the dataset.
no code implementations • ACL 2021 • Shan Wu, Bo Chen, Chunlei Xin, Xianpei Han, Le Sun, Weipeng Zhang, Jiansong Chen, Fan Yang, Xunliang Cai
During synchronous decoding: the utterance paraphrasing is constrained by the structure of the logical form, therefore the canonical utterance can be paraphrased controlledly; the semantic decoding is guided by the semantics of the canonical utterance, therefore its logical form can be generated unsupervisedly.
no code implementations • 9 Jun 2021 • Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Attention-based neural networks have achieved state-of-the-art results on a wide range of tasks.
1 code implementation • 10 May 2021 • Dandan Guo, Ruiying Lu, Bo Chen, Zequn Zeng, Mingyuan Zhou
Inspired by recent successes in integrating semantic topics into this task, this paper develops a plug-and-play hierarchical-topic-guided image paragraph generation framework, which couples a visual extractor with a deep topic model to guide the learning of a language model.
no code implementations • 21 Apr 2021 • Shiwen Lei, Jing Tian, Zhipeng Lin, Haoquan Hu, Bo Chen, Wei Yang, Pu Tang, Xiangdong Qiu
This paper proposes two algorithms to maximize the minimum array power gain in a wide-beam mainlobe by solving the power gain pattern synthesis (PGPS) problem with and without sidelobe constraints.
2 code implementations • CVPR 2021 • Ziheng Cheng, Bo Chen, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang, Xin Yuan
With the knowledge of masks, optimization algorithms or deep learning methods are employed to reconstruct the desired high-speed video frames from this snapshot measurement.
2 code implementations • CVPR 2021 • Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan
To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks and then compressed to a snapshot measurement.
no code implementations • 18 Feb 2021 • Parham Gohari, Bo Chen, Bo Wu, Matthew Hale, Ufuk Topcu
We then develop a kickstarted deep reinforcement learning algorithm for the student that is privacy-aware because we calibrate its objective with the parameters of the teacher's privacy mechanism.
no code implementations • 4 Jan 2021 • Ning Bian, Xianpei Han, Bo Chen, Le Sun
Experiments show that: (1) Our knowledge-to-text framework is effective and achieves state-of-the-art performance on CommonsenseQA dataset, providing a simple and strong knowledge-enhanced baseline for CQA; (2) The potential of knowledge is still far from being fully exploited in CQA -- there is a significant performance gap from current models to our models with golden knowledge; and (3) Context-sensitive knowledge selection, heterogeneous knowledge exploitation, and commonsense-rich language models are promising CQA directions.
no code implementations • 1 Jan 2021 • Ruiying Lu, Bo Chen, Dan dan Guo, Dongsheng Wang, Mingyuan Zhou
Moving beyond conventional Transformers that ignore longer-range word dependencies and contextualize their word representations at the segment level, the proposed method not only captures global semantic coherence of all segments and global word concurrence patterns, but also enriches the representation of each token by adapting it to its local context, which is not limited to the segment it resides in and can be flexibly defined according to the task.
1 code implementation • 16 Dec 2020 • Huifeng Guo, Bo Chen, Ruiming Tang, Weinan Zhang, Zhenguo Li, Xiuqiang He
In this paper, we propose a novel embedding learning framework for numerical features in CTR prediction (AutoDis) with high model capacity, end-to-end training and unique representation properties preserved.
2 code implementations • 14 Dec 2020 • Bo Chen, Jing Zhang, Xiaokang Zhang, Xiaobin Tang, Lingfan Cai, Hong Chen, Cuiping Li, Peng Zhang, Jie Tang
In this paper, we propose CODE, which first pre-trains an expert linking model by contrastive learning on AMiner such that it can capture the representation and matching patterns of experts without supervised signals, then it is fine-tuned between AMiner and external sources to enhance the models transferability in an adversarial manner.
no code implementations • NeurIPS 2020 • Chaojie Wang, Hao Zhang, Bo Chen, Dongsheng Wang, Zhengjue Wang, Mingyuan Zhou
To analyze a collection of interconnected documents, relational topic models (RTMs) have been developed to describe both the link structure and document content, exploring their underlying relationships via a single-layer latent representation with limited expressive capability.
1 code implementation • NeurIPS 2020 • Wenchao Chen, Chaojie Wang, Bo Chen, Yicheng Liu, Hao Zhang, Mingyuan Zhou
Incorporating the natural document-sentence-word structure into hierarchical Bayesian modeling, we propose convolutional Poisson gamma dynamical systems (PGDS) that introduce not only word-level probabilistic convolutions, but also sentence-level stochastic temporal transitions.
1 code implementation • NeurIPS 2020 • Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou
Attention modules, as simple and effective tools, have not only enabled deep neural networks to achieve state-of-the-art results in many domains, but also enhanced their interpretability.
no code implementations • 12 Oct 2020 • Jing Zhang, Bo Chen, Lingxi Zhang, Xirui Ke, Haipeng Ding
On the contrary, the recent advances of deep learning promote neural reasoning on knowledge graphs, which is robust to the ambiguous and noisy data, but lacks interpretability compared to symbolic reasoning.
no code implementations • 28 Sep 2020 • Dandan Guo, Bo Chen, Wenchao Chen, Chaojie Wang, Hongwei Liu, Mingyuan Zhou
We develop a recurrent gamma belief network (rGBN) for radar automatic target recognition (RATR) based on high-resolution range profile (HRRP), which characterizes the temporal dependence across the range cells of HRRP.
1 code implementation • CVPR 2020 • Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc Le
Efficient Neural Architecture Search methods based on weight sharing have shown good promise in democratizing Neural Architecture Search for computer vision models.
no code implementations • 24 Jun 2020 • Steve Alpern, Bo Chen
Each juror has an ability in [0, 1], which is proportional to the probability of A given a positive signal, an analog of Condorcet's p for binary signals.
no code implementations • 15 Jun 2020 • Hao Zhang, Bo Chen, Yulai Cong, Dandan Guo, Hongwei Liu, Mingyuan Zhou
Given a posterior sample of the global parameters, in order to efficiently infer the local latent representations of a document under DATM across all stochastic layers, we propose a Weibull upward-downward variational encoder that deterministically propagates information upward via a deep neural network, followed by a Weibull distribution based stochastic downward generative model.
1 code implementation • 10 May 2020 • Lizhen Shi, Bo Chen
Graph clustering is widely used in analysis of biological networks, social networks and etc.
4 code implementations • CVPR 2021 • Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen
By incorporating regular convolutions in the search space and directly optimizing the network architectures for object detection, we obtain a family of object detection models, MobileDets, that achieve state-of-the-art results across mobile accelerators.
no code implementations • 21 Mar 2020 • Daqi Liu, Bo Chen, Tat-Jun Chin, Mark Rutten
In this paper, we propose a novel multi-target detection technique based on topological sweep, to find GEO objects from a short sequence of optical images.
no code implementations • 5 Mar 2020 • Yichen Zhang, Chen Chen, Tianqi Hong, Bai Cui, Bo Chen, Feng Qiu
The capability to switch between grid-connected and islanded modes has promoted adoption of microgrid technology for powering remote locations.
no code implementations • 16 Jan 2020 • Bo Chen, Youde Wang
We follow the idea of Wang \cite{W} to show the existence of global weak solutions to the Cauchy problems of Landau-Lifshtiz type equations and related heat flows from a $n$-dimensional Euclidean domain $\Om$ or a $n$-dimensional closed Riemannian manifold $M$ into a 2-dimensional unit sphere $\U^{2}$.
Analysis of PDEs
1 code implementation • ICML 2020 • Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou
To simultaneously capture syntax and global semantics from a text corpus, we propose a new larger-context recurrent neural network (RNN) based language model, which extracts recurrent hierarchical semantic structure via a dynamic deep topic model to guide natural language generation.
2 code implementations • CVPR 2020 • Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adams, Quoc V. Le
We propose MnasFPN, a mobile-friendly search space for the detection head, and combine it with latency-aware architecture search to produce efficient object detection models.
Ranked #230 on Object Detection on COCO test-dev
no code implementations • 22 Nov 2019 • Bo Chen, Decai Li, Yuqing He, Chunsheng Hua
In temporal dimension, we designed a knowledge graph based causal reasoning module and map the past actions to temporal causal features through Diffusion RNN.
no code implementations • 25 Sep 2019 • Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou
To simultaneously capture syntax and semantics from a text corpus, we propose a new larger-context language model that extracts recurrent hierarchical semantic structure via a dynamic deep topic model to guide natural language generation.
2 code implementations • CVPR 2020 • Bo Chen, Alvaro Parra, Jiewei Cao, Nan Li, Tat-Jun Chin
To seamlessly combine deep learning and geometric vision, it is vital to perform learning and geometric optimization end-to-end.
Ranked #1 on 6D Pose Estimation using RGB on LineMOD (Accuracy metric)
1 code implementation • 30 Aug 2019 • Bo Chen, Jiewei Cao, Alvaro Parra, Tat-Jun Chin
We propose an approach to estimate the 6DOF pose of a satellite, relative to a canonical pose, from a single image.
1 code implementation • ACL 2019 • Sheng Lin, Luye Zheng, Bo Chen, Siliang Tang, Yueting Zhuang, Fei Wu, Zhigang Chen, Guoping Hu, Xiang Ren
Fine-grained Entity Typing is a tough task which suffers from noise samples extracted from distant supervision.
1 code implementation • ICLR 2020 • Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou
For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that integrates a probabilistic text decoder, probabilistic image encoder, and GAN into a coherent end-to-end multi-modality learning framework.
1 code implementation • 14 May 2019 • Chaojie Wang, Bo Chen, Sucheng Xiao, Mingyuan Zhou
For text analysis, one often resorts to a lossy representation that either completely ignores word order or embeds each word as a low-dimensional dense feature vector.
61 code implementations • ICCV 2019 • Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam
We achieve new state of the art results for mobile classification, detection and segmentation.
Ranked #9 on Dichotomous Image Segmentation on DIS-TE1
no code implementations • ICLR 2019 • Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou
To extract and relate visual and linguistic concepts from images and textual descriptions for text-based zero-shot learning (ZSL), we develop variational hetero-encoder (VHE) that decodes text via a deep probabilisitic topic model, the variational posterior of whose local latent variables is encoded from an image via a Weibull distribution based inference network.
no code implementations • 15 Apr 2019 • Sergei Alyamkin, Matthew Ardi, Alexander C. Berg, Achille Brighton, Bo Chen, Yiran Chen, Hsin-Pai Cheng, Zichen Fan, Chen Feng, Bo Fu, Kent Gauen, Abhinav Goel, Alexander Goncharenko, Xuyang Guo, Soonhoi Ha, Andrew Howard, Xiao Hu, Yuanjun Huang, Donghyun Kang, Jaeyoun Kim, Jong Gook Ko, Alexander Kondratyev, Junhyeok Lee, Seungjae Lee, Suwoong Lee, Zichao Li, Zhiyu Liang, Juzheng Liu, Xin Liu, Yang Lu, Yung-Hsiang Lu, Deeptanshu Malik, Hong Hanh Nguyen, Eunbyung Park, Denis Repin, Liang Shen, Tao Sheng, Fei Sun, David Svitov, George K. Thiruvathukal, Baiwu Zhang, Jingchi Zhang, Xiaopeng Zhang, Shaojie Zhuo
In addition to mobile phones, many autonomous systems rely on visual data for making decisions and some of these systems have limited energy (such as unmanned aerial vehicles also called drones and mobile robots).
no code implementations • NAACL 2019 • Bo Chen, Xiaotao Gu, Yu-Feng Hu, Siliang Tang, Guoping Hu, Yueting Zhuang, Xiang Ren
Recently, distant supervision has gained great success on Fine-grained Entity Typing (FET).
no code implementations • 12 Mar 2019 • Chen Feng, Tao Sheng, Zhiyu Liang, Shaojie Zhuo, Xiaopeng Zhang, Liang Shen, Matthew Ardi, Alexander C. Berg, Yiran Chen, Bo Chen, Kent Gauen, Yung-Hsiang Lu
The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015 that encourages joint hardware and software solutions for computer vision systems with low latency and power.
no code implementations • ACL 2016 • Bo Chen, Le Sun, Xianpei Han, Bo An
A major challenge of semantic parsing is the vocabulary mismatch problem between natural language and target ontology.
no code implementations • NeurIPS 2018 • Dandan Guo, Bo Chen, Hao Zhang, Mingyuan Zhou
We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequentially observed multivariate count data, improving previously proposed models by not only mining deep hierarchical latent structure from the data, but also capturing both first-order and long-range temporal dependencies.
no code implementations • 3 Oct 2018 • Sergei Alyamkin, Matthew Ardi, Achille Brighton, Alexander C. Berg, Yiran Chen, Hsin-Pai Cheng, Bo Chen, Zichen Fan, Chen Feng, Bo Fu, Kent Gauen, Jongkook Go, Alexander Goncharenko, Xuyang Guo, Hong Hanh Nguyen, Andrew Howard, Yuanjun Huang, Donghyun Kang, Jaeyoun Kim, Alexander Kondratyev, Seungjae Lee, Suwoong Lee, Junhyeok Lee, Zhiyu Liang, Xin Liu, Juzheng Liu, Zichao Li, Yang Lu, Yung-Hsiang Lu, Deeptanshu Malik, Eunbyung Park, Denis Repin, Tao Sheng, Liang Shen, Fei Sun, David Svitov, George K. Thiruvathukal, Baiwu Zhang, Jingchi Zhang, Xiaopeng Zhang, Shaojie Zhuo
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing. ieee. org/lpirc) is an annual competition started in 2015.
1 code implementation • ACL 2018 • Bo Chen, Le Sun, Xianpei Han
This paper proposes a neural semantic parsing approach -- Sequence-to-Action, which models semantic parsing as an end-to-end semantic graph generation process.
no code implementations • COLING 2018 • Bo Chen, Bo An, Le Sun, Xianpei Han
Semantic parsers critically rely on accurate and high-coverage lexicons.
28 code implementations • CVPR 2019 • Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le
In this paper, we propose an automated mobile neural architecture search (MNAS) approach, which explicitly incorporate model latency into the main objective so that the search can identify a model that achieves a good trade-off between accuracy and latency.
Ranked #833 on Image Classification on ImageNet (using extra training data)
no code implementations • NAACL 2018 • Bo An, Bo Chen, Xianpei Han, Le Sun
Previous representation learning techniques for knowledge graph representation usually represent the same entity or relation in different triples with the same representation, without considering the ambiguity of relations and entities.
4 code implementations • ECCV 2018 • Tien-Ju Yang, Andrew Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam
This work proposes an algorithm, called NetAdapt, that automatically adapts a pre-trained deep neural network to a mobile platform given a resource budget.
1 code implementation • ICLR 2018 • Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou
To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid autoencoding inference (WHAI) for deep latent Dirichlet allocation, which infers posterior samples via a hybrid of stochastic-gradient MCMC and autoencoding variational Bayes.
22 code implementations • CVPR 2018 • Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, Dmitry Kalenichenko
The rising popularity of intelligent mobile devices and the daunting computational cost of deep learning-based models call for efficient and accurate on-device inference schemes.
3 code implementations • CVPR 2018 • Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, Edward Choi
We present MorphNet, an approach to automate the design of neural network structures.
no code implementations • WS 2017 • Kees van Deemter, Le Sun, Rint Sybesma, Xiao Li, Bo Chen, Muyun Yang
East Asian languages are thought to handle reference differently from languages such as English, particularly in terms of the marking of definiteness and number.
no code implementations • Pattern Recognition Letters 2017 • Fei Li, Meishan Zhang, Bo Tian, Bo Chen, Guohong Fu, Donghong Ji
We evaluate our models on two datasets for recognizing regular and irreg- ular biomedical entities.
no code implementations • ICML 2017 • Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou
It is challenging to develop stochastic gradient based scalable inference for deep discrete latent variable models (LVMs), due to the difficulties in not only computing the gradients, but also adapting the step sizes to different latent factors and hidden layers.
no code implementations • 30 Apr 2017 • Ganbin Zhou, Ping Luo, Rongyu Cao, Yijun Xiao, Fen Lin, Bo Chen, Qing He
Then, with a proposed tree-structured search method, the model is able to generate the most probable responses in the form of dependency trees, which are finally flattened into sequences as the system output.
155 code implementations • 17 Apr 2017 • Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam
We present a class of efficient models called MobileNets for mobile and embedded vision applications.
Ranked #238 on Object Detection on COCO test-dev
1 code implementation • CVPR 2017 • Bo Chen, Pietro Perona
Images are formed by counting how many photons traveling from a given set of directions hit an image sensor during a given time interval.
no code implementations • 9 Dec 2015 • Mingyuan Zhou, Yulai Cong, Bo Chen
To infer multilayer deep representations of high-dimensional discrete and nonnegative real vectors, we propose an augmentable gamma belief network (GBN) that factorizes each of its hidden layers into the product of a sparse connection weight matrix and the nonnegative real hidden units of the next layer.
no code implementations • NeurIPS 2015 • Mingyuan Zhou, Yulai Cong, Bo Chen
Example results on text analysis illustrate interesting relationships between the width of the first layer and the inferred network structure, and demonstrate that the PGBN, whose hidden units are imposed with correlated gamma priors, can add more layers to increase its performance gains over Poisson factor analysis, given the same limit on the width of the first layer.
6 code implementations • CVPR 2014 • Jiang Wang, Yang song, Thomas Leung, Chuck Rosenberg, Jinbin Wang, James Philbin, Bo Chen, Ying Wu
This paper proposes a deep ranking model that employs deep learning techniques to learn similarity metric directly from images. It has higher learning capability than models based on hand-crafted features.
no code implementations • NeurIPS 2011 • Bo Chen, Vidhya Navalpakkam, Pietro Perona
A model of human visual search is proposed.
no code implementations • NeurIPS 2011 • Bo Chen, David E. Carlson, Lawrence Carin
Nonparametric Bayesian methods are developed for analysis of multi-channel spike-train data, with the feature learning and spike sorting performed jointly.