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Jing Rong
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- affiliation: Michigan State University, East Lansing, USA
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2020 – today
- 2020
[j69]Tianbao Yang
, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin:
High-dimensional model recovery from random sketched data by exploring intrinsic sparsity. Mach. Learn. 109(5): 899-938 (2020)- [j68]Rong Jin, Qingxia Li, Hang Liu:
A Subspace Algorithm to Mitigate Energy Unknown RFI for Synthetic Aperture Interferometric Radiometer. IEEE Trans. Geosci. Remote. Sens. 58(1): 227-237 (2020) - [j67]Faraz Ahmed, Alex X. Liu, Rong Jin:
Publishing Social Network Graph Eigenspectrum With Privacy Guarantees. IEEE Trans. Netw. Sci. Eng. 7(2): 892-906 (2020) - [c267]Xiangzeng Zhou, Pan Pan, Yun Zheng, Yinghui Xu, Rong Jin:
Large Scale Long-tailed Product Recognition System at Alibaba. CIKM 2020: 3353-3356 - [c266]Qi Qian, Lei Chen, Hao Li, Rong Jin:
DR Loss: Improving Object Detection by Distributional Ranking. CVPR 2020: 12161-12169 - [c265]Yang Jiao, Liang Han, Rong Jin, Yi-Jung Su, Chiente Ho, Li Yin, Yun Li, Long Chen, Zhen Chen, Lu Liu, Zhuyu He, Yu Yan, Jun He, Jun Mao, Xiaotao Zai, Xuejun Wu, Yongquan Zhou, Mingqiu Gu, Guocai Zhu, Rong Zhong, Wenyuan Lee, Ping Chen, Yiping Chen, Weiliang Li, Deyu Xiao, Qing Yan, Mingyuan Zhuang, Jiejun Chen, Yun Tian, Yingzi Lin, Wei Wu, Hao Li, Zesheng Dou:
7.2 A 12nm Programmable Convolution-Efficient Neural-Processing-Unit Chip Achieving 825TOPS. ISSCC 2020: 136-140 - [c264]Liuyihan Song, Pan Pan, Kang Zhao, Hao Yang, Yiming Chen, Yingya Zhang, Yinghui Xu, Rong Jin:
Large-Scale Training System for 100-Million Classification at Alibaba. KDD 2020: 2909-2930 - [c263]Liang Han, Zhaozheng Yin, Zhurong Xia, Minqian Tang, Rong Jin:
Price Suggestion for Online Second-hand Items with Texts and Images. ACM Multimedia 2020: 2784-2792 - [c262]Rong Jin:
Large-scale Multi-modal Search and QA at Alibaba. SIGIR 2020: 8 - [i68]Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu:
Representation Learning with Fine-grained Patterns. CoRR abs/2005.09681 (2020) - [i67]Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang:
A Practical Online Method for Distributionally Deep Robust Optimization. CoRR abs/2006.10138 (2020) - [i66]Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin:
Towards Understanding Label Smoothing. CoRR abs/2006.11653 (2020) - [i65]Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin:
Neural Architecture Design for GPU-Efficient Networks. CoRR abs/2006.14090 (2020) - [i64]Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin:
WeMix: How to Better Utilize Data Augmentation. CoRR abs/2010.01267 (2020) - [i63]Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin:
Learning Accurate Entropy Model with Global Reference for Image Compression. CoRR abs/2010.08321 (2020)
2010 – 2019
- 2019
- [j66]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. J. Mach. Learn. Res. 20: 97:1-97:22 (2019) - [j65]Wenjie Zhang, Hui Li, Rong Jin, Shanlin Wei, Wei Cheng, Weisi Kong, Penglu Liu:
Distributed Structured Compressive Sensing-Based Time-Frequency Joint Channel Estimation for Massive MIMO-OFDM Systems. Mob. Inf. Syst. 2019: 2634361:1-2634361:16 (2019) - [j64]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou:
A simple homotopy proximal mapping algorithm for compressive sensing. Mach. Learn. 108(6): 1019-1056 (2019) - [c261]Yu-Hang Zhou, Chen Liang, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin:
Robust Online Matching with User Arrival Distribution Drift. AAAI 2019: 459-466 - [c260]Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI 2019: 4312-4319 - [c259]Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li:
Robust Optimization over Multiple Domains. AAAI 2019: 4739-4746 - [c258]Mingdong Ou, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin:
Semi-Parametric Sampling for Stochastic Bandits with Many Arms. AAAI 2019: 7933-7940 - [c257]Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu, Rong Jin:
Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance. CIKM 2019: 2489-2497 - [c256]Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin:
Large-Scale Visual Search with Binary Distributed Graph at Alibaba. CIKM 2019: 2567-2575 - [c255]Qi Qian, Lei Shang, Baigui Sun, Juhua Hu, Tacoma Tacoma, Hao Li, Rong Jin:
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling. ICCV 2019: 6449-6457 - [c254]Hesen Chen, Ming Lin, Xiuyu Sun, Qian Qi, Hao Li, Rong Jin:
MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning. ICCV Workshops 2019: 2943-2952 - [c253]Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang:
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence. ICML 2019: 6942-6951 - [c252]Hao Yu, Rong Jin:
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization. ICML 2019: 7174-7183 - [c251]Hao Yu, Rong Jin, Sen Yang:
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization. ICML 2019: 7184-7193 - [c250]Yi Peng, Miao Xie, Jiahao Liu, Xuying Meng, Nan Li, Cheng Yang, Tao Yao, Rong Jin:
A Practical Semi-Parametric Contextual Bandit. IJCAI 2019: 3246-3252 - [c249]Yi Xu, Zhuoning Yuan, Sen Yang, Rong Jin, Tianbao Yang:
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization. IJCAI 2019: 4003-4009 - [c248]Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin:
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. KDD 2019: 2838-2847 - [c247]Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin:
Vision-based Price Suggestion for Online Second-hand Items. ACM Multimedia 2019: 1988-1996 - [c246]Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor:
XNAS: Neural Architecture Search with Expert Advice. NeurIPS 2019: 1975-1985 - [c245]Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang:
Stagewise Training Accelerates Convergence of Testing Error Over SGD. NeurIPS 2019: 2604-2614 - [c244]Yi Xu, Rong Jin, Tianbao Yang:
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems. NeurIPS 2019: 2626-2636 - [c243]Midori Kitagawa, Paul Fishwick, Michael Kesden, Mary Urquhart, Rosanna Guadagno, Rong Jin, Ngoc Tran, Erik Omogbehin, Aditya Prakash, Priyanka Awaraddi, Baily Hale, Ken Suura, Aniket Raj, James Stanfield, Henry Vo:
Scaffolded Training Environment for Physics Programming (STEPP): Modeling High School Physics using Concept Maps and State Machines. SIGSIM-PADS 2019: 127-136 - [c242]Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang:
Learning with Non-Convex Truncated Losses by SGD. UAI 2019: 244 - [i62]Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR abs/1901.11149 (2019) - [i61]Rong Jin, David Simchi-Levi, Li Wang, Xinshang Wang, Sen Yang:
Conservative Exploration for Semi-Bandits with Linear Generalization: A Product Selection Problem for Urban Warehouses. CoRR abs/1903.07844 (2019) - [i60]Hao Yu, Rong Jin, Sen Yang:
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization. CoRR abs/1905.03817 (2019) - [i59]Hao Yu, Rong Jin:
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization. CoRR abs/1905.04346 (2019) - [i58]Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin:
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. CoRR abs/1906.01095 (2019) - [i57]Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor:
XNAS: Neural Architecture Search with Expert Advice. CoRR abs/1906.08031 (2019) - [i56]Qi Qian, Lei Chen, Hao Li, Rong Jin:
DR Loss: Improving Object Detection by Distributional Ranking. CoRR abs/1907.10156 (2019) - [i55]Qi Qian, Lei Shang, Baigui Sun, Juhua Hu, Hao Li, Rong Jin:
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling. CoRR abs/1909.05235 (2019) - 2018
- [j63]Rong Jin, Jiaojiao Li, Xin Tuo, Weiming Wang, Xiaolin Li:
A congestion control method of SDN data center based on reinforcement learning. Int. J. Commun. Syst. 31(17) (2018) - [j62]Yanli Wang, Guofu Yin, Rong Jin:
一种新的传感器网络能量收集优化技术 (New Optimized Energy Harvesting Technology for Sensor Networks). 计算机科学 45(11): 82-86 (2018) - [j61]Rong Jin, Kai Zeng:
Secure Inductive-Coupled Near Field Communication at Physical Layer. IEEE Trans. Inf. Forensics Secur. 13(12): 3078-3093 (2018) - [j60]Rong Jin, Kai Zeng:
Physical layer multi-user key generation in wireless networks. Wirel. Networks 24(4): 1043-1054 (2018) - [c241]Cong Leng, Zesheng Dou, Hao Li, Shenghuo Zhu, Rong Jin:
Extremely Low Bit Neural Network: Squeeze the Last Bit Out With ADMM. AAAI 2018: 3466-3473 - [c240]Qi Qian, Jiasheng Tang, Hao Li, Shenghuo Zhu, Rong Jin:
Large-Scale Distance Metric Learning With Uncertainty. CVPR 2018: 8542-8550 - [c239]Bin Wang, Pan Pan, Qinjie Xiao, Likang Luo, Xiaofeng Ren, Rong Jin, Xiaogang Jin:
Seamless Color Mapping for 3D Reconstruction with Consumer-Grade Scanning Devices. ECCV Workshops (1) 2018: 633-648 - [c238]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Dynamic Regret of Strongly Adaptive Methods. ICML 2018: 5877-5886 - [c237]Mingdong Ou, Nan Li, Shenghuo Zhu, Rong Jin:
Multinomial Logit Bandit with Linear Utility Functions. IJCAI 2018: 2602-2608 - [c236]Lakshmi Sharma, Rong Jin, Balakrishnan Prabhakaran, Murry Gans:
LearnDNA: an interactive VR application for learning DNA structure. IWISC 2018: 80-87 - [c235]Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin:
Visual Search at Alibaba. KDD 2018: 993-1001 - [c234]Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Jing Rong, Tianbao Yang:
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. NeurIPS 2018: 4683-4694 - [c233]Yi Xu, Jing Rong, Tianbao Yang:
First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time. NeurIPS 2018: 5535-5545 - [c232]Jinjing Zhao, Ling Pang, Xiaohui Kuang, Rong Jin:
Balancing the QOS and Security in Dijkstra Algorithm by SDN Technology. NPC 2018: 126-131 - [r2]Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu:
Combining Link and Content for Community Detection. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i54]Mingdong Ou, Nan Li, Shenghuo Zhu, Rong Jin:
Multinomial Logit Bandit with Linear Utility Functions. CoRR abs/1805.02971 (2018) - [i53]Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang:
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. CoRR abs/1805.04577 (2018) - [i52]Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li:
Robust Optimization over Multiple Domains. CoRR abs/1805.07588 (2018) - [i51]Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang:
Learning with Non-Convex Truncated Losses by SGD. CoRR abs/1805.07880 (2018) - [i50]Qi Qian, Jiasheng Tang, Hao Li, Shenghuo Zhu, Rong Jin:
Large-scale Distance Metric Learning with Uncertainty. CoRR abs/1805.10384 (2018) - [i49]Tianbao Yang, Yan Yan, Zhuoning Yuan, Rong Jin:
Why Does Stagewise Training Accelerate Convergence of Testing Error Over SGD? CoRR abs/1812.03934 (2018) - 2017
- [j59]Juhua Hu, Qi Qian, Jian Pei, Rong Jin, Shenghuo Zhu:
Finding multiple stable clusterings. Knowl. Inf. Syst. 51(3): 991-1021 (2017) - [j58]Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, Deng Cai, Xuelong Li, Ronghua Liang, Xiaofei He:
Sparse Learning with Stochastic Composite Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 39(6): 1223-1236 (2017) - [j57]Rong Jin, Xianru Du, Kai Zeng, Liqun Huang, Laiyuan Xiao, Jing Xu:
Delay Analysis of Physical-Layer Key Generation in Dynamic Roadside-to-Vehicle Networks. IEEE Trans. Veh. Technol. 66(3): 2526-2535 (2017) - [c231]Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin:
A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis. AAAI 2017: 2224-2230 - [c230]Kevin Desai, Uriel Haile Hernández Belmonte, Rong Jin, Balakrishnan Prabhakaran, Paul Diehl, Víctor Ayala-Ramírez, Vinu Johnson, Murry Gans:
Experiences with Multi-modal Collaborative Virtual Laboratory (MMCVL). BigMM 2017: 376-383 - [c229]Lijun Zhang, Tianbao Yang, Rong Jin:
Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. COLT 2017: 1954-1979 - [c228]Luan Tran, Xiaoming Liu, Jiayu Zhou, Rong Jin:
Missing Modalities Imputation via Cascaded Residual Autoencoder. CVPR 2017: 4971-4980 - [c227]Rong Jin:
Deep Learning at Alibaba. IJCAI 2017: 11-16 - [c226]Gang Liu, Qi Qian, Zhibin Wang, Qingen Zhao, Tianzhou Wang, Hao Li, Jian Xue, Shenghuo Zhu, Rong Jin, Tuo Zhao:
The Opensesame NIST 2016 Speaker Recognition Evaluation System. INTERSPEECH 2017: 2854-2858 - [c225]Kevin Desai, Suraj Raghuraman, Rong Jin, Balakrishnan Prabhakaran:
QoE Studies on Interactive 3D Tele-Immersion. ISM 2017: 130-137 - [c224]Liang Chen, Rong Jin, Christopher Raphael:
Human-Guided Recognition of Music Score Images. DLfM 2017: 9-12 - [c223]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Jing Rong, Zhi-Hua Zhou:
Improved Dynamic Regret for Non-degenerate Functions. NIPS 2017: 732-741 - [i48]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Strongly Adaptive Regret Implies Optimally Dynamic Regret. CoRR abs/1701.07570 (2017) - [i47]Lijun Zhang, Tianbao Yang, Rong Jin:
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n2)-type of Risk Bounds. CoRR abs/1702.02030 (2017) - [i46]Cong Leng, Hao Li, Shenghuo Zhu, Rong Jin:
Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM. CoRR abs/1707.09870 (2017) - 2016
- [j56]Wei Gao, Lu Wang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou:
One-pass AUC optimization. Artif. Intell. 236: 1-29 (2016) - [j55]Qiaozi Gao, Elisabeth Ostendorf, Jeffrey A. Cruz, Rong Jin, David M. Kramer, Jin Chen:
Inter-functional analysis of high-throughput phenotype data by non-parametric clustering and its application to photosynthesis. Bioinform. 32(1): 67-76 (2016) - [j54]Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang:
Online kernel learning with nearly constant support vectors. Neurocomputing 179: 26-36 (2016) - [j53]Hailiang Lu, Qingxia Li, Rong Jin, Ke Chen, Yan Li, Li Feng, Hao Li, Yinan Li:
A Hybrid Calibration Method for Aperture Synthesis Radiometers. IEEE Geosci. Remote. Sens. Lett. 13(5): 651-655 (2016) - [j52]Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin:
On Data Preconditioning for Regularized Loss Minimization. Mach. Learn. 103(1): 57-79 (2016) - [j51]Rong Jin, Liu Shi, Kai Zeng, Amit Pande, Prasant Mohapatra:
MagPairing: Pairing Smartphones in Close Proximity Using Magnetometers. IEEE Trans. Inf. Forensics Secur. 11(6): 1306-1320 (2016) - [j50]Rong Jin, Xianru Du, Zi Deng, Kai Zeng, Jing Xu:
Practical Secret Key Agreement for Full-Duplex Near Field Communications. IEEE Trans. Mob. Comput. 15(4): 938-951 (2016) - [c222]Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin:
Fast and Accurate Refined Nyström-Based Kernel SVM. AAAI 2016: 1830-1836 - [c221]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Stochastic Optimization for Kernel PCA. AAAI 2016: 2315-2322 - [c220]Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He:
Accelerated Sparse Linear Regression via Random Projection. AAAI 2016: 2337-2343 - [c219]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. ALT 2016: 83-97 - [c218]Rong Jin:
Large-scale Robust Online Matching and Its Application in E-commerce. CIKM 2016: 1351 - [c217]Faraz Ahmed, Alex X. Liu, Rong Jin:
Social Graph Publishing with Privacy Guarantees. ICDCS 2016: 447-456 - [c216]Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-Hua Zhou:
Online Stochastic Linear Optimization under One-bit Feedback. ICML 2016: 392-401 - [c215]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. ICML 2016: 449-457 - [c214]Yufang Li, Qingxia Li, Rong Jin, Feng Li, Haofeng Dou, Hang Liu:
Array configuration optimization for Rotating mirrored aperture synthesis (RMAS). IGARSS 2016: 853-856 - [c213]Yan Li, Qingxia Li, Liang Lang, Rong Jin, Zhiwei Chen:
Correction of SMOS data in coastal area of South China Sea based on land contamination analysis. IGARSS 2016: 7667-7670 - [i45]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. CoRR abs/1605.04638 (2016) - [i44]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved dynamic regret for non-degeneracy functions. CoRR abs/1608.03933 (2016) - 2015
- [j49]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu:
An efficient primal dual prox method for non-smooth optimization. Mach. Learn. 98(3): 369-406 (2015) - [j48]Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu:
Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). Mach. Learn. 99(3): 353-372 (2015) - [j47]Songhe Feng, Zheyun Feng, Rong Jin:
Learning to Rank Image Tags With Limited Training Examples. IEEE Trans. Image Process. 24(4): 1223-1234 (2015) - [c212]Zenglin Xu, Rong Jin, Bin Shen, Shenghuo Zhu:
Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation. AAAI 2015: 3115-3121 - [c211]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Online Bandit Learning for a Special Class of Non-Convex Losses. AAAI 2015: 3158-3164 - [c210]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
A Simple Homotopy Algorithm for Compressive Sensing. AISTATS 2015 - [c209]Zhongyun Tang, Rong Jin, Ligang Dong:
An atomic capability chain composition method. CCECE 2015: 1335-1338 - [c208]Chengming Huang, Rong Jin, Chuanhuang Li, Kelei Jin:
A reconfigurable system of routing and switching node based on ATC. CCECE 2015: 1339-1344 - [c207]Radha Chitta, Anil K. Jain, Rong Jin:
Sparse Kernel Clustering of Massive High-Dimensional Data sets with Large Number of Clusters. PIKM@CIKM 2015: 11-18 - [c206]Xiaojia Pu, Rong Jin, Gangshan Wu, Dingyi Han, Gui-Rong Xue:
Topic Modeling in Semantic Space with Keywords. CIKM 2015: 1141-1150 - [c205]Rong Jin, Kai Zeng:
SecNFC: Securing inductively-coupled Near Field Communication at physical layer. CNS 2015: 149-157 - [c204]Rong Jin, Kai Zeng:
Physical layer key agreement under signal injection attacks. CNS 2015: 254-262 - [c203]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT 2015: 1305-1320 - [c202]Qi Qian, Rong Jin, Shenghuo Zhu, Yuanqing Lin:
Fine-grained visual categorization via multi-stage metric learning. CVPR 2015: 3716-3724 - [c201]Juhua Hu, Qi Qian, Jian Pei, Rong Jin, Shenghuo Zhu:
Finding Multiple Stable Clusterings. ICDM 2015: 171-180 - [c200]Radha Chitta, Rong Jin, Anil K. Jain:
Stream Clustering: Efficient Kernel-Based Approximation Using Importance Sampling. ICDM Workshops 2015: 607-614 - [c199]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection. ICML 2015: 135-143 - [c198]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
Theory of Dual-sparse Regularized Randomized Reduction. ICML 2015: 305-314 - [c197]Miao Xu, Rong Jin, Zhi-Hua Zhou:
CUR Algorithm for Partially Observed Matrices. ICML 2015: 1412-1421 - [c196]Rong Jin, Christopher Raphael:
Graph-Based Rhythm Interpretation. ISMIR 2015: 343-349 - [c195]Wenliang Zhong, Rong Jin, Cheng Yang, Xiaowei Yan, Qi Zhang, Qiang Li:
Stock Constrained Recommendation in Tmall. KDD 2015: 2287-2296 - [c194]Tianbao Yang, Qihang Lin, Rong Jin:
Big Data Analytics: Optimization and Randomization. KDD 2015: 2327 - [c193]