no code implementations • 26 Apr 2024 • Zhaohui Huang, Zhaocheng Wang, Sheng Chen
To address this highly complex programming using sub-6GHz information, a novel heterogeneous graph neural network (HGNN) architecture is proposed to learn the intrinsic relationship between sub-6GHz and mmWave and design the hybrid beamformers for mmWave BSs.
no code implementations • 4 Feb 2024 • Liyang Lu, Zhaocheng Wang, Zhen Gao, Sheng Chen, H. Vincent Poor
This work explores the fundamental problem of the recoverability of a sparse tensor being reconstructed from its compressed embodiment.
no code implementations • 17 Dec 2023 • Qingxuan Lv, Yuezun Li, Junyu Dong, Sheng Chen, Hui Yu, Huiyu Zhou, Shu Zhang
Specifically, our strategy considers both forward and backward adaptation, to transfer the forgery knowledge from the source domain to the target domain in forward adaptation and then reverse the adaptation from the target domain to the source domain in backward adaptation.
1 code implementation • 16 Nov 2023 • Yuliang Liu, Xiangru Tang, Zefan Cai, Junjie Lu, Yichi Zhang, Yanjun Shao, Zexuan Deng, Helan Hu, Kaikai An, Ruijun Huang, Shuzheng Si, Sheng Chen, Haozhe Zhao, Liang Chen, Yan Wang, Tianyu Liu, Zhiwei Jiang, Baobao Chang, Yujia Qin, Wangchunshu Zhou, Yilun Zhao, Arman Cohan, Mark Gerstein
While Large Language Models (LLMs) have demonstrated proficiency in code generation benchmarks, translating these results into practical development scenarios - where leveraging existing repository-level libraries is the norm - remains challenging.
no code implementations • 8 Nov 2023 • Fan Zhang, Tianqi Mao, Ruiqi Liu, Zhu Han, Sheng Chen, Zhaocheng Wang
For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communications according to prior knowledge of the communication channel.
1 code implementation • 30 Oct 2023 • Shuang Peng, Fei Yang, Ning Sun, Sheng Chen, Yanfeng Jiang, Aimin Pan
In summary, our study introduces an innovative PTQ method for ProteinLMs, addressing specific quantization challenges and potentially leading to the development of more efficient ProteinLMs with significant implications for various protein-related applications.
no code implementations • 22 Oct 2023 • Yong Du, Jiahui Zhan, Shengfeng He, Xinzhe Li, Junyu Dong, Sheng Chen, Ming-Hsuan Yang
In this paper, we propose a novel translation model, UniTranslator, for transforming representations between visually distinct domains under conditions of limited training data and significant visual differences.
no code implementations • 15 Aug 2023 • Wen Zan, Yaopeng Han, Xiaotian Jiang, Yao Xiao, Yang Yang, Dayao Chen, Sheng Chen
At pretraining stage, we propose an effective pretraining method that employs both query and multiple fields of document as inputs, including an effective information compression method for lengthy fields.
no code implementations • 27 Apr 2023 • Sheng Chen, Zihao Tang, Dongnan Liu, Ché Fornusek, Michael Barnett, Chenyu Wang, Mariano Cabezas, Weidong Cai
However, due to the insufficient amount of precise annotations, thigh muscle masks generated by deep learning approaches tend to misclassify intra-muscular fat (IMF) as muscle impacting the analysis of muscle volumetrics.
no code implementations • 7 Apr 2023 • Liyang Lu, Zhaocheng Wang, Sheng Chen
We consider the greedy algorithms for the joint recovery of high-dimensional sparse signals based on the block multiple measurement vector (BMMV) model in compressed sensing (CS).
no code implementations • 1 Jan 2023 • Fuwang Dong, Wei Wang, Xin Li, Fan Liu, Sheng Chen, Lajos Hanzo
The dual-functional radar and communication (DFRC) technique constitutes a promising next-generation wireless solution, due to its benefits in terms of power consumption, physical hardware, and spectrum exploitation.
no code implementations • 12 Jul 2022 • Yanbo J. Wang, Yuming Li, Hui Qin, Yuhang Guan, Sheng Chen
As a rising star in the field of natural language processing, question answering systems (Q&A Systems) are widely used in all walks of life.
no code implementations • 7 Jul 2022 • Yue Cao, Xiaojiang Zhou, Peihao Huang, Yao Xiao, Dayao Chen, Sheng Chen
In this paper, we focus on the information transfer from ranking to pre-ranking stage.
1 code implementation • 20 May 2022 • Yue Cao, Xiaojiang Zhou, Jiaqi Feng, Peihao Huang, Yao Xiao, Dayao Chen, Sheng Chen
However, the retrieval-based methods are sub-optimal and would cause more or less information losses, and it's difficult to balance the effectiveness and efficiency of the retrieval algorithm.
no code implementations • 19 May 2022 • Xiang Li, Xiaojiang Zhou, Yao Xiao, Peihao Huang, Dayao Chen, Sheng Chen, Yunsen Xian
Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages.
no code implementations • 8 May 2022 • Yang Wang, Zhen Gao, Dezhi Zheng, Sheng Chen, Deniz Gündüz, H. Vincent Poor
It is anticipated that 6G wireless networks will accelerate the convergence of the physical and cyber worlds and enable a paradigm-shift in the way we deploy and exploit communication networks.
no code implementations • 21 Dec 2021 • Di Yao, Chang Gong, Lei Zhang, Sheng Chen, Jingping Bi
Existing methods first train a model to predict the conversion probability of the advertisement journeys with historical data and calculate the attribution of each touchpoint using counterfactual predictions.
no code implementations • 10 Nov 2021 • Zijian Gao, Jingyu Liu, Weiqi Sun, Sheng Chen, Dedan Chang, Lili Zhao
Modern video-text retrieval frameworks basically consist of three parts: video encoder, text encoder and the similarity head.
Ranked #12 on Video Retrieval on MSR-VTT-1kA (using extra training data)
1 code implementation • 4 Nov 2021 • Yuxin Meng, Eric Rigall, Xueen Chen, Feng Gao, Junyu Dong, Sheng Chen
Physical modeling methods can offer the potential for extrapolation beyond observational conditions, while data-driven methods are flexible in adapting to data and are capable of detecting unexpected patterns.
no code implementations • 18 Aug 2021 • Jinhua Guo, Hao Chen, Jingxin Zhang, Sheng Chen
For structure parameters, the kernel dictionary is selected by some sparsification techniques with online selective modeling criteria, and moreover the kernel covariance matrix is intermittently optimized in the light of the covariance matrix adaptation evolution strategy (CMA-ES).
no code implementations • 17 May 2021 • Andrey Ignatov, Grigory Malivenko, Radu Timofte, Sheng Chen, Xin Xia, Zhaoyan Liu, Yuwei Zhang, Feng Zhu, Jiashi Li, Xuefeng Xiao, Yuan Tian, Xinglong Wu, Christos Kyrkou, Yixin Chen, Zexin Zhang, Yunbo Peng, Yue Lin, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Himanshu Kumar, Chao Ge, Pei-Lin Wu, Jin-Hua Du, Andrew Batutin, Juan Pablo Federico, Konrad Lyda, Levon Khojoyan, Abhishek Thanki, Sayak Paul, Shahid Siddiqui
To address this problem, we introduce the first Mobile AI challenge, where the target is to develop quantized deep learning-based camera scene classification solutions that can demonstrate a real-time performance on smartphones and IoT platforms.
1 code implementation • 13 May 2021 • Menghui Zhu, Minghuan Liu, Jian Shen, Zhicheng Zhang, Sheng Chen, Weinan Zhang, Deheng Ye, Yong Yu, Qiang Fu, Wei Yang
In Goal-oriented Reinforcement learning, relabeling the raw goals in past experience to provide agents with hindsight ability is a major solution to the reward sparsity problem.
no code implementations • 28 Apr 2021 • Chen-Chen Fan, Haiqun Xie, Liang Peng, Hongjun Yang, Zhen-Liang Ni, Guan'an Wang, Yan-Jie Zhou, Sheng Chen, Zhijie Fang, Shuyun Huang, Zeng-Guang Hou
On the DMS data set, GF-DANN has obtained an accuracy rate of 89. 47%, and the sensitivity and specificity are 90% and 89%.
no code implementations • 18 Apr 2021 • Xin Sun, Changrui Chen, Xiaorui Wang, Junyu Dong, Huiyu Zhou, Sheng Chen
Furthermore, we also build a Gaussian dynamic pyramid Pooling to show its potential and generality in common semantic segmentation.
1 code implementation • 8 Jan 2021 • Ke Ma, Dongxuan He, Hancun Sun, Zhaocheng Wang, Sheng Chen
To tackle this problem, the second scheme adopts long-short term memory (LSTM) network for tracking the movement of users and calibrating the beam direction according to the received signals of prior beam training, in order to enhance the robustness to noise.
no code implementations • 18 Dec 2020 • Sheng Chen, Menghui Zhu, Deheng Ye, Weinan Zhang, Qiang Fu, Wei Yang
Hero drafting is essential in MOBA game playing as it builds the team of each side and directly affects the match outcome.
no code implementations • 25 Nov 2020 • Deheng Ye, Guibin Chen, Peilin Zhao, Fuhao Qiu, Bo Yuan, Wen Zhang, Sheng Chen, Mingfei Sun, Xiaoqian Li, Siqin Li, Jing Liang, Zhenjie Lian, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang
Unlike prior attempts, we integrate the macro-strategy and the micromanagement of MOBA-game-playing into neural networks in a supervised and end-to-end manner.
no code implementations • NeurIPS 2020 • Deheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, Yinyuting Yin, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu
However, existing work falls short in handling the raw game complexity caused by the explosion of agent combinations, i. e., lineups, when expanding the hero pool in case that OpenAI's Dota AI limits the play to a pool of only 17 heroes.
no code implementations • 5 Jun 2020 • Ashwini Badgujar, Sheng Chen, Andrew Wang, Kai Yu, Paul Intrevado, David Guy Brizan
In this research, we continuously collect data from the RSS feeds of traditional news sources.
no code implementations • 17 Mar 2020 • Xuanyu Shu, Jin Zhang, Sen Tian, Sheng Chen, Lingyu Chen
Based on the idea of small world network, a random edge adding algorithm is proposed to improve the performance of convolutional neural network model.
no code implementations • 12 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.
no code implementations • 4 Dec 2018 • Zhiyuan Jiang, Ziyan He, Sheng Chen, Andreas F. Molisch, Sheng Zhou, Zhisheng Niu
Channel state information (CSI) is of vital importance in wireless communication systems.
no code implementations • 4 Dec 2018 • Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu
In this paper, we propose a learning-based low-overhead beam alignment method for vehicle-to-infrastructure communication in vehicular networks.
no code implementations • 3 Dec 2018 • Zhiyuan Jiang, Sheng Chen, Andreas F. Molisch, Rath Vannithamby, Sheng Zhou, Zhisheng Niu
Knowledge of information about the propagation channel in which a wireless system operates enables better, more efficient approaches for signal transmissions.
no code implementations • NeurIPS 2018 • Sheng Chen, Arindam Banerjee
To find the coefficient vector, estimators with a joint approximation of the noise covariance are often preferred than the simple linear regression in view of their superior empirical performance, which can be generally solved by alternating-minimization type procedures.
no code implementations • 1 Aug 2018 • Sheng Chen, Jia Guo, Yang Liu, Xiang Gao, Zhen Han
In this paper, we propose a novel Global Norm-Aware Pooling (GNAP) block, which reweights local features in a convolutional neural network (CNN) adaptively according to their L2 norms and outputs a global feature vector with a global average pooling layer.
17 code implementations • 20 Apr 2018 • Sheng Chen, Yang Liu, Xiang Gao, Zhen Han
Face Analysis Project on MXNet
Ranked #5 on Lightweight Face Recognition on AgeDB-30
no code implementations • 16 Oct 2017 • Sheng Chen, Arindam Banerjee
In machine learning and data mining, linear models have been widely used to model the response as parametric linear functions of the predictors.
no code implementations • ICML 2017 • Sheng Chen, Arindam Banerjee
In this paper, we investigate general single-index models (SIMs) in high dimensions.
no code implementations • WS 2017 • Sheng Chen, Akshay Soni, Aasish Pappu, Yashar Mehdad
Tagging news articles or blog posts with relevant tags from a collection of predefined ones is coined as document tagging in this work.
no code implementations • NeurIPS 2017 • Sheng Chen, Arindam Banerjee
We consider learning high-dimensional multi-response linear models with structured parameters.
no code implementations • NeurIPS 2016 • Sheng Chen, Arindam Banerjee
In recent years, structured matrix recovery problems have gained considerable attention for its real world applications, such as recommender systems and computer vision.
no code implementations • NeurIPS 2015 • Sheng Chen, Arindam Banerjee
For structured estimation problems with atomic norms, recent advances in the literature express sample complexity and estimation error bounds in terms of certain geometric measures, in particular Gaussian width of the unit norm ball, Gaussian width of a spherical cap induced by a tangent cone, and a restricted norm compatibility constant.
no code implementations • 4 Sep 2015 • Xia Hong, Sheng Chen, Yi Guo, Junbin Gao
A l1-norm penalized orthogonal forward regression (l1-POFR) algorithm is proposed based on the concept of leaveone- out mean square error (LOOMSE).
no code implementations • CVPR 2015 • Sheng Chen, Alan Fern, Sinisa Todorovic
This problem is a middle-ground between frame-level person counting, which does not localize counts, and person detection aimed at perfectly localizing people with count-one detections.
no code implementations • NeurIPS 2014 • Arindam Banerjee, Sheng Chen, Farideh Fazayeli, Vidyashankar Sivakumar
Analysis of non-asymptotic estimation error and structured statistical recovery based on norm regularized regression, such as Lasso, needs to consider four aspects: the norm, the loss function, the design matrix, and the noise model.
no code implementations • NeurIPS 2014 • Soumyadeep Chatterjee, Sheng Chen, Arindam Banerjee
For statistical analysis, we provide upper bounds for the Gaussian widths needed in the GDS analysis, yielding the first statistical recovery guarantee for estimation with the $k$-support norm.
no code implementations • CVPR 2014 • Sheng Chen, Alan Fern, Sinisa Todorovic
This paper presents a new approach to tracking people in crowded scenes, where people are subject to long-term (partial) occlusions and may assume varying postures and articulations.