Rong Jin

发表

Learning with Multiple Labels

Rong Jin, Zoubin Ghahramani, Zoubin Ghahramani, 2002, NIPS.

NEON+: Accelerated Gradient Methods for Extracting Negative Curvature for Non-Convex Optimization

Tianbao Yang, Yi Xu, Rong Jin, 2017, 1712.01033.

Distance Metric Learning: A Comprehensive Survey

Rong Jin, Liu Yang, Liu Yang, 2006 .

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient

Jinfeng Yi, Rong Jin, Tianbao Yang, 2016, ICML.

Semi-Supervised Boosting for Multi-Class Classification

Rong Jin, Anil K. Jain, Hamed Valizadegan, 2008, ECML/PKDD.

Large-scale text categorization by batch mode active learning

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2006, WWW '06.

SemiBoost: Boosting for Semi-Supervised Learning

Yi Liu, Rong Jin, Anil K. Jain, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Batch mode active learning and its application to medical image classification

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2006, ICML.

Unifying discriminative visual codebook generation with classifier training for object category recognition

Rong Jin, Liu Yang, Frédéric Jurie, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Multi-Task Learning: Multiple Kernels for Multiple Tasks

Rong Jin, Hang Li, Wei Wu, 2010 .

Approximate kernel k-means: solution to large scale kernel clustering

Rong Jin, Anil K. Jain, Timothy C. Havens, 2011, KDD.

Regret bounded by gradual variation for online convex optimization

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2014, Machine Learning.

Learning a distance metric from multi-instance multi-label data

Zhi-Hua Zhou, Rong Jin, Shijun Wang, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization pdf

Rong Jin, Mehrdad Mahdavi, Rong Jin, 2013, ArXiv.

Online Multiple Kernel Similarity Learning for Visual Search.

Rong Jin, P. Zhao, S. Hoi, 2013, IEEE transactions on pattern analysis and machine intelligence.

25th Annual Conference on Learning Theory Online Optimization with Gradual Variations

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2022 .

Double Updating Online Learning

Rong Jin, Steven C. H. Hoi, Peilin Zhao, 2011, J. Mach. Learn. Res..

Stochastic Proximal Gradient Methods for Non-smooth Non-Convex Regularized Problems.

Tianbao Yang, Yi Xu, Rong Jin, 2019 .

Some contributions to dimensionality reduction

Rong Jin, Wei Tong, 2010 .

Towards Understanding Label Smoothing

Yi Xu, Rong Jin, Yuanhong Xu, 2020, ArXiv.

Boosting multi-kernel locality-sensitive hashing for scalable image retrieval

Rong Jin, Steven C. H. Hoi, Hao Xia, 2012, SIGIR '12.

Stochastic Optimization with Multiple Objectives

Rong Jin, M. Mahdavi, 2013 .

On Theoretical Analysis of Distributed Stochastic Dual Coordinate Ascent pdf

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2013, ArXiv.

Decision Making under Stochastic Constraints

Rong Jin, M. Mahdavi, 2012 .

Image Retrieval in Forensics: Tattoo Image Database

Rong Jin, Anil K. Jain, Jung-Eun Lee, 2012 .

Learning Phenotype Specific Gene Network by Knowledge Driven Matrix Factorization

Rong Jin, Zheng Li, Christina Chan, 2007 .

Learning Position and Target Consistency for Memory-based Video Object Segmentation

Rong Jin, Yinghui Xu, Bang Zhang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

KVT: k-NN Attention for Boosting Vision Transformers

Rong Jin, Hao Li, F. Wang, 2021, ECCV.

Improved Bound for the Nystrom's Method and its Application to Kernel Classification pdf

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2011, ArXiv.

On the Equivalence of Nonnegative Matrix Factorization and K-means - Spectral Clustering

C. Ding, Xiaofeng He, H. Simon, 2005 .

Robust Graph Structure Learning over Images via Multiple Statistical Tests

Rong Jin, Senzhang Wang, Ming Lin, 2022, ArXiv.

CUR Algorithm for Partially Observed Matrices pdf

Miao Xu, Rong Jin, Zhi-Hua Zhou, 2014, ICML.

On the Convergence of Deep Networks with Sample Quadratic Overparameterization pdf

Yi Xu, Yonathan Aflalo, Rong Jin, 2021, ArXiv.

A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks

Lihi Zelnik-Manor, Rong Jin, Yonathan Aflalo, 2021, 2101.04243.

Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach

Rong Jin, Karim G. Oweiss, Seif Eldawlatly, 2009, Neural Computation.

A maximum coherence model for dictionary-based cross-language information retrieval

Yi Liu, Rong Jin, Joyce Yue Chai, 2005, SIGIR '05.

Robust Ensemble Clustering by Matrix Completion

Jinfeng Yi, Rong Jin, Tianbao Yang, 2012, 2012 IEEE 12th International Conference on Data Mining.

On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles

Rong Jin, Karim G. Oweiss, Yang Zhou, 2010, Neural Computation.

Learning Bregman Distance Functions for Semi-Supervised Clustering

Nenghai Yu, Lei Wu, Rong Jin, 2012, IEEE Transactions on Knowledge and Data Engineering.

Learning from noisily connected data

Rong Jin, Tianbao Yang, Tianbao Yang, 2012 .

Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data

Rong Jin, Liu Yang, Rahul Sukthankar, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning

Rong Jin, Hamed Valizadegan, Rong Jin, 2006, NIPS.

A Probabilistic Approach for Optimizing Spectral Clustering

Chris H. Q. Ding, Rong Jin, Feng Kang, 2005, NIPS.

A Novel Approach to Model Generation for Heterogeneous Data Classification

Huan Liu, Rong Jin, Rong Jin, 2005, IJCAI.

WeMix: How to Better Utilize Data Augmentation pdf

Yi Xu, Qi Qian, Hao Li, 2020, ArXiv.

On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization

Rong Jin, Tianbao Yang, Sen Yang, 2019, IJCAI.

Learning to Rank Image Tags With Limited Training Examples

Rong Jin, Songhe Feng, Zheyun Feng, 2015, IEEE Transactions on Image Processing.

Mixed Optimization for Smooth Functions

Rong Jin, Lijun Zhang, Mehrdad Mahdavi, 2013, NIPS.

Robust Online Matching with User Arrival Distribution Drift

Rong Jin, Chen Liang, Shenghuo Zhu, 2019, AAAI.

Online Stochastic Optimization with Multiple Objectives pdf

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2012, ArXiv.

Multi-Class Learning by Smoothed Boosting

Rong Jin, Jian Zhang, Rong Jin, 2007, Machine Learning.

Multi-label Multiple Kernel Learning

Jieping Ye, Rong Jin, Liang Sun, 2008, NIPS.

Automated annotation of Drosophila gene expression patterns using a controlled vocabulary

Jieping Ye, Rong Jin, Liang Sun, 2008, Bioinform..

Speedup Matrix Completion with Side Information: Application to Multi-Label Learning

Miao Xu, Rong Jin, Zhi-Hua Zhou, 2013, NIPS.

Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach

Jinfeng Yi, Rong Jin, Anil K. Jain, 2012, HCOMP@AAAI.

On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization pdf

Rong Jin, Hao Yu, Rong Jin, 2019, ICML.

A Bayesian framework for knowledge driven regression model in micro-array data analysis

Luo Si, Rong Jin, Christina Chan, 2008, Int. J. Data Min. Bioinform..

A Knowledge Driven Regression Model for Gene Expression and Microarray Analysis

Luo Si, Zheng Li, Rong Jin, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

Deep Learning at Alibaba

Rong Jin, Rong Jin, 2017, IJCAI.

Publishing Social Network Graph Eigenspectrum With Privacy Guarantees

Rong Jin, Alex X. Liu, Faraz Ahmed, 2020, IEEE Transactions on Network Science and Engineering.

Unsupervised Visual Representation Learning by Online Constrained K-Means

Rong Jin, Hao Li, Yuanhong Xu, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Finding multiple stable clusterings

Jian Pei, Rong Jin, Qi Qian, 2015, 2015 IEEE International Conference on Data Mining.

Detecting communities and their evolutions in dynamic social networks—a Bayesian approach

Yihong Gong, Yun Chi, Rong Jin, 2011, Machine Learning.

Combining link and content for community detection: a discriminative approach

Yun Chi, Rong Jin, Tianbao Yang, 2009, KDD.

Speedup of fuzzy and possibilistic kernel c-means for large-scale clustering

Rong Jin, Anil K. Jain, Timothy C. Havens, 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

Multiple Kernel Learning for Visual Object Recognition: A Review

Rong Jin, Anil K. Jain, Serhat Selcuk Bucak, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

High-dimensional model recovery from random sketched data by exploring intrinsic sparsity

Tianbao Yang, Shenghuo Zhu, Qihang Lin, 2020, Machine Learning.

Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees pdf

Rong Jin, Tianbao Yang, Qihang Lin, 2015, ArXiv.

On Data Preconditioning for Regularized Loss Minimization

Tianbao Yang, Shenghuo Zhu, Rong Jin, 2014, Machine Learning.

Dash: Semi-Supervised Learning with Dynamic Thresholding

Rong Jin, Qi Qian, Baigui Sun, 2021, ICML.

A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound

Rong Jin, Jiawei Han, Tianbao Yang, 2012, ICML.

Unsupervised transfer classification: application to text categorization

Rong Jin, Tianbao Yang, Anil K. Jain, 2010, KDD.

Discriminative Semi-Supervised Feature Selection Via Manifold Regularization

Zenglin Xu, Michael R. Lyu, Irwin King, 2009, IEEE Transactions on Neural Networks.

Adaptive Regularization for Transductive Support Vector Machine

Zenglin Xu, Rong Jin, Michael R. Lyu, 2009, NIPS.

Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2009, IEEE Transactions on Knowledge and Data Engineering.

Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization

Rong Jin, Liu Yang, Rahul Sukthankar, 2008, NIPS.

Efficient Convex Relaxation for Transductive Support Vector Machine

Zenglin Xu, Rong Jin, Michael R. Lyu, 2007, NIPS.

A learning framework using Green's function and kernel regularization with application to recommender system

Chris H. Q. Ding, Rong Jin, Tao Li, 2007, KDD '07.

Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization

Yi Liu, Rong Jin, Liu Yang, 2006, AAAI.

Semi-Supervised Learning by Mixed Label Propagation

Rong Jin, Wei Tong, Rong Jin, 2007, AAAI.

CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

Rong Jin, Pichao Wang, Hao Li, 2021, ICLR.

Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds

Rong Jin, Tianbao Yang, Lijun Zhang, 2017, COLT.

One-Pass AUC Optimization pdf

Zhi-Hua Zhou, Shenghuo Zhu, Wei Gao, 2013, ICML.

Understanding bag-of-words model: a statistical framework

Rong Jin, Zhi-Hua Zhou, Yin Zhang, 2010, Int. J. Mach. Learn. Cybern..

Linear Convergence with Condition Number Independent Access of Full Gradients

Rong Jin, Lijun Zhang, Mehrdad Mahdavi, 2013, NIPS.

Rong Jin, Rahul Sukthankar, Feng Kang, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Multinomial Logit Bandit with Linear Utility Functions

Rong Jin, Shenghuo Zhu, Nan Li, 2018, IJCAI.

Active Learning by Querying Informative and Representative Examples

Rong Jin, Zhi-Hua Zhou, Sheng-Jun Huang, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Active query selection for semi-supervised clustering

Rong Jin, Anil K. Jain, Pavan Kumar Mallapragada, 2008, 2008 19th International Conference on Pattern Recognition.

CobBO: Coordinate Backoff Bayesian Optimization

Rong Jin, Niv Nayman, Mengchang Wang, 2021, ArXiv.

BoostCluster: boosting clustering by pairwise constraints

Yi Liu, Rong Jin, Anil K. Jain, 2007, KDD '07.

Online Feature Selection and Its Applications

Rong Jin, Steven C. H. Hoi, Jialei Wang, 2014, IEEE Transactions on Knowledge and Data Engineering.

Image Retrieval in Forensics: Tattoo Image Database Application

Rong Jin, Anil K. Jain, Wei Tong, 2012, IEEE MultiMedia.

Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition

Rong Jin, Anil K. Jain, Serhat Selcuk Bucak, 2010, NIPS.

Dynamic Regret of Strongly Adaptive Methods

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2017, ICML.

Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization

Rong Jin, Lijun Zhang, Mehrdad Mahdavi, 2015, COLT.

An efficient primal dual prox method for non-smooth optimization

Tianbao Yang, Rong Jin, Shenghuo Zhu, 2012, Machine Learning.

Multi-label learning with incomplete class assignments

Rong Jin, Anil K. Jain, Serhat Selcuk Bucak, 2011, CVPR 2011.

Multiple Kernel Learning from Noisy Labels by Stochastic Programming pdf

Rong Jin, Tianbao Yang, Lijun Zhang, 2012, ICML.

Simple and Efficient Multiple Kernel Learning by Group Lasso

Zenglin Xu, Rong Jin, Michael R. Lyu, 2010, ICML.

Effective Model Sparsification by Scheduled Grow-and-Prune Methods pdf

Rong Jin, Xiaolong Ma, Zejiang Hou, 2021, ICLR.

Graph Convolution for Re-Ranking in Person Re-Identification

Rong Jin, Weihua Chen, Yuqi Zhang, 2021, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Large-Scale Distance Metric Learning with Uncertainty

Rong Jin, Qi Qian, Shenghuo Zhu, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

SoftTriple Loss: Deep Metric Learning Without Triplet Sampling

Rong Jin, Qi Qian, Hao Li, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

DUOL: A Double Updating Approach for Online Learning

Rong Jin, Steven C. H. Hoi, Peilin Zhao, 2009, NIPS.

Combining Link and Content for Community Detection

Yun Chi, Rong Jin, Tianbao Yang, 2014, Encyclopedia of Social Network Analysis and Mining.

Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM

Shenghuo Zhu, Hao Li, Rong Jin, 2017, AAAI.

Learning nonparametric kernel matrices from pairwise constraints

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2007, ICML '07.

Trading regret for efficiency: online convex optimization with long term constraints pdf

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2011, J. Mach. Learn. Res..

Online Multiple Kernel Similarity Learning for Visual Search

Rong Jin, Steven C. H. Hoi, Hao Xia, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Combi ni ng Li nk and Content for Communi ty Detecti on: A Discriminative Approach

Yun Chi, Rong Jin, Tianbao Yang, 2009 .

Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis

Luo Si, Rong Jin, Rong Jin, 2005, PAKDD.

A Random Matrix Approach to Differential Privacy and Structure Preserved Social Network Graph Publishing pdf

Rong Jin, Alex X. Liu, Faraz Ahmed, 2013, ArXiv.

A Novel Convergence Analysis for Algorithms of the Adam Family and Beyond

Tianbao Yang, Yi Xu, Rong Jin, 2021, 2104.14840.

On Stochastic Moving-Average Estimators for Non-Convex Optimization

Tianbao Yang, Yi Xu, Rong Jin, 2021, ArXiv.

Seamless Color Mapping for 3D Reconstruction with Consumer-Grade Scanning Devices

Bin Wang, Rong Jin, Xiaogang Jin, 2018, ECCV Workshops.

Identifying neuronal assemblies with local and global connectivity with scale space spectral clustering

Rong Jin, Karim G. Oweiss, Yasir Suhail, 2007, Neurocomputing.

Missing Modalities Imputation via Cascaded Residual Autoencoder

Jiayu Zhou, Rong Jin, Xiaoming Liu, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization

Rong Jin, Hao Yu, Sen Yang, 2019, ICML.

Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD)

Jinfeng Yi, Rong Jin, Qi Qian, 2013, Machine Learning.

Recovering the Optimal Solution by Dual Random Projection

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2012, COLT.

Proceedings of the first SIGMM workshop on Social media

Susanne CJ Boll, Rong Jin, Dong Xu, 2009, WSM@MM.

Self-supervised Video Representation Learning by Context and Motion Decoupling

Rong Jin, Yinghui Xu, Pan Pan, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Analysis of Distributed Stochastic Dual Coordinate Ascent

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2013, 1312.1031.

Self-supervised Motion Learning from Static Images

Rong Jin, Shiwei Zhang, Marcelo Ang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Visual Search at Alibaba

Rong Jin, Yanhao Zhang, Yun Zheng, 2018, KDD.

Semisupervised SVM batch mode active learning with applications to image retrieval

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2009, TOIS.

Tag Completion for Image Retrieval

Lei Wu, Rong Jin, Anil K. Jain, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

User term feedback in interactive text-based image retrieval

Chen Zhang, Rong Jin, Joyce Yue Chai, 2005, SIGIR '05.

Exploitation and exploration in a performance based contextual advertising system

Wei Li, Ying Cui, Rong Jin, 2010, KDD.

DR Loss: Improving Object Detection by Distributional Ranking

Rong Jin, Qi Qian, Hao Li, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Scaled ReLU Matters for Training Vision Transformers pdf

Rong Jin, Jingkai Zhou, Zhipeng Zhou, 2021, AAAI.

A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval

Rong Jin, Mahadev Satyanarayanan, Steven C. H. Hoi, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Social Media Modeling and Computing

Jiebo Luo, Steven C. H. Hoi, Susanne Boll, 2011 .

Rethinking supervised pre-training for better downstream transferring

Rong Jin, Jianwen Jiang, Mingqian Tang, 2021, ICLR.

Online AUC Maximization

Rong Jin, Tianbao Yang, Steven C. H. Hoi, 2011, ICML.

Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice pdf

Rong Jin, Qi Qian, Antoni B. Chan, 2021, ArXiv.

Similarity Beyond Distance Measurement

Rong Jin, Steven C. H. Hoi, Feng Kang, 2007, RIAO.

Active multiple kernel learning for interactive 3D object retrieval systems

Rong Jin, Steven C. H. Hoi, Rong Jin, 2011, ACM Trans. Interact. Intell. Syst..

Robust Optimization over Multiple Domains

Rong Jin, Qi Qian, Shenghuo Zhu, 2018, AAAI.

A New Boosting Algorithm Using Input-Dependent Regularizer

Luo Si, Rong Jin, Jaime G. Carbonell, 2003, ICML 2003.

Stochastic Convex Optimization with Multiple Objectives

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2013, NIPS.

Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning

Jinfeng Yi, Rong Jin, Tianbao Yang, 2012, NIPS.

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Rong Jin, Pichao Wang, Zhenhong Sun, 2021, ArXiv.

An automatic weighting scheme for collaborative filtering

Luo Si, Rong Jin, Joyce Yue Chai, 2004, SIGIR '04.

An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives

Tianbao Yang, Yi Xu, Rong Jin, 2020, NeurIPS.

Online feature selection for mining big data

Rong Jin, Steven C. H. Hoi, Jialei Wang, 2012, BigMine '12.

Exclusive Lasso for Multi-task Feature Selection

Rong Jin, Steven C. H. Hoi, Yang Zhou, 2010, AISTATS.

Stock Constrained Recommendation in Tmall

Qi Zhang, Rong Jin, Leon Wenliang Zhong, 2015, KDD.

Topic Modeling in Semantic Space with Keywords

Rong Jin, Gui-Rong Xue, Gangshan Wu, 2015, CIKM.

Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation

Zenglin Xu, Rong Jin, Bin Shen, 2015, AAAI.

Social Graph Publishing with Privacy Guarantees

Rong Jin, Alex X. Liu, Faraz Ahmed, 2016, 2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS).

Learning to Rank by Optimizing NDCG Measure

Rong Jin, Ruofei Zhang, Jianchang Mao, 2009, NIPS.

A Pairwise Ensemble Approach for Accurate Genre Classification

Rong Jin, Jaime G. Carbonell, Yan Liu, 2003 .

Linguistic theories in efficient multimodal reference resolution: an empirical investigation

Rong Jin, Joyce Yue Chai, Zahar Prasov, 2005, IUI.

Ranking refinement and its application to information retrieval

Hang Li, Rong Jin, Hamed Valizadegan, 2008, WWW.

Learning to trade off between exploration and exploitation in multiclass bandit prediction

Rong Jin, Shijun Wang, Hamed Valizadegan, 2011, KDD.

A study of mixture models for collaborative filtering

Luo Si, Rong Jin, ChengXiang Zhai, 2006, Information Retrieval.

A Bayesian Approach toward Active Learning for Collaborative Filtering

Luo Si, Rong Jin, Rong Jin, 2004, UAI.

A Simple Homotopy Proximal Mapping for Compressive Sensing pdf

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2014, ArXiv.

A simple homotopy proximal mapping algorithm for compressive sensing

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2014, Machine Learning.

First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time

Tianbao Yang, Jing Rong, Yi Xu, 2017, NeurIPS.

An Efficient Algorithm for Local Distance Metric Learning

Yi Liu, Rong Jin, Liu Yang, 2006, AAAI.

An empirical investigation of user term feedback in text-based targeted image search

Chen Zhang, Rong Jin, Joyce Yue Chai, 2007, TOIS.

A graph-based framework for relation propagation and its application to multi-label learning

Rong Jin, Ming Wu, Rong Jin, 2006, SIGIR.

Online visual vocabulary pruning using pairwise constraints

Rong Jin, Anil K. Jain, Pavan Kumar Mallapragada, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Attentional Biased Stochastic Gradient for Imbalanced Classification pdf

Qi Qi, Yi Xu, Tianbao Yang, 2020, ArXiv.

Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization

Rong Jin, Xuerui Yang, Yang Zhou, 2009, Bioinform..

XNAS: Neural Architecture Search with Expert Advice

Lihi Zelnik-Manor, Itamar Friedman, Rong Jin, 2019, NeurIPS.

Learning distance metrics for interactive search-assisted diagnosis of mammograms

Rong Jin, Mei Chen, Mahadev Satyanarayanan, 2007, SPIE Medical Imaging.

Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion

Jinfeng Yi, Rong Jin, Qi Qian, 2013, ICML.

Online Stochastic Linear Optimization under One-bit Feedback

Zhi-Hua Zhou, Tianbao Yang, Yichi Xiao, 2015, ICML.

Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning pdf

Rong Jin, Yinghui Xu, Bin Wang, 2021, AAAI.

Communication Efficient SGD via Gradient Sampling with Bayes Prior

Rong Jin, Yinghui Xu, Yingya Zhang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems

Tianbao Yang, Yi Xu, Rong Jin, 2019, NeurIPS.

Why Does Stagewise Training Accelerate Convergence of Testing Error Over SGD? pdf

Rong Jin, Tianbao Yang, Yan Yan, 2018, ArXiv.

Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence

Rong Jin, Tianbao Yang, Qihang Lin, 2018, ICML.

Large-Scale Training System for 100-Million Classification at Alibaba

Rong Jin, Kang Zhao, Yingya Zhang, 2020, KDD.

Efficient Kernel Clustering Using Random Fourier Features

Rong Jin, Anil K. Jain, Radha Chitta, 2012, 2012 IEEE 12th International Conference on Data Mining.

Rank-based distance metric learning: An application to image retrieval

Rong Jin, Anil K. Jain, Jung-Eun Lee, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

A Novel Convergence Analysis for Algorithms of the Adam Family pdf

Rong Jin, Tianbao Yang, Wotao Yin, 2021, ArXiv.

Neural Architecture Design for GPU-Efficient Networks

Rong Jin, Qi Qian, Hao Li, 2020, ArXiv.

Efficient multi-label ranking for multi-class learning: Application to object recognition

Rong Jin, Anil K. Jain, Serhat Selcuk Bucak, 2009, 2009 IEEE 12th International Conference on Computer Vision.

Regularized Distance Metric Learning: Theory and Algorithm

Rong Jin, Shijun Wang, Yang Zhou, 2009, NIPS.

Online Multiple Kernel Learning: Algorithms and Mistake Bounds

Rong Jin, Tianbao Yang, Steven C. H. Hoi, 2010, ALT.

Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions

Mingrui Liu, Tianbao Yang, Xiaoxuan Zhang, 2018, NeurIPS.

Strongly Adaptive Regret Implies Optimally Dynamic Regret pdf

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2017, ArXiv.

Online kernel learning with nearly constant support vectors

Rong Jin, Changshui Zhang, Ming Lin, 2016, Neurocomputing.

Online Kernel Learning with a Near Optimal Sparsity Bound

Jinfeng Yi, Rong Jin, Xiaofei He, 2013, ICML.

O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions pdf

Rong Jin, Tianbao Yang, Xiaofei He, 2013, ICML.

Stochastic Gradient Descent with Only One Projection

Jinfeng Yi, Rong Jin, Tianbao Yang, 2012, NIPS.

Efficient Online Learning for Large-scale Sparse Kernel Logistic Regression

Chun Chen, Jiajun Bu, Rong Jin, 2022 .

Online Kernel Selection: Algorithms and Evaluations

Jinfeng Yi, Rong Jin, Tianbao Yang, 2012, AAAI.

Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning pdf

Steven C. H. Hoi, Peilin Zhao, Pengcheng Wu, 2012, ICML.

Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering

Nenghai Yu, Lei Wu, Rong Jin, 2009, NIPS.

Of Information Systems School of Information Systems 8-2012 Online Feature Selection for Mining Big Data

Rong Jin, Steven C. H. Hoi, Peilin Zhao, 2015 .

A Practical Online Method for Distributionally Deep Robust Optimization pdf

Qi Qi, Yi Xu, Tianbao Yang, 2020, ArXiv.

An Online Method for Distributionally Deep Robust Optimization

Qi Qi, Yi Xu, Tianbao Yang, 2020 .

A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis

Rong Jin, Tianbao Yang, Lijun Zhang, 2017, AAAI.

Stochastic Optimization for Kernel PCA

Jinfeng Yi, Rong Jin, Zhi-Hua Zhou, 2016, AAAI.

Stochastic Proximal Gradient Descent for Nuclear Norm Regularization pdf

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2015, ArXiv.

Random Projections for Classification: A Recovery Approach

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2014, IEEE Transactions on Information Theory.

Distance metric learning using dropout: a structured regularization approach

Jian Pei, Rong Jin, Qi Qian, 2014, KDD.

Sparse Learning with Stochastic Composite Optimization

Xuelong Li, Rong Jin, Zhongming Jin, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Efficient Algorithms for Robust One-bit Compressive Sensing

Jinfeng Yi, Rong Jin, Lijun Zhang, 2014, ICML.

Passive Learning with Target Risk pdf

Rong Jin, Mehrdad Mahdavi, Rong Jin, 2013, COLT.

Regret Bound by Variation for Online Convex Optimization pdf

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2011, ArXiv.

High Probability Bounds for Bandit Stochastic and Adversarial Strongly Convex Optimization

Rong Jin, M. Mahdavi, 2013 .

Online Multiple Kernel Classification

Rong Jin, Tianbao Yang, Steven C. H. Hoi, 2013, Machine Learning.

An Extended Level Method for Efficient Multiple Kernel Learning

Zenglin Xu, Rong Jin, Michael R. Lyu, 2008, NIPS.

Theory of Dual-sparse Regularized Randomized Reduction

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2015, ICML.

A Simple Homotopy Algorithm for Compressive Sensing

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2015, AISTATS.

A Novel Method Incorporating Gene Ontology Information for Unsupervised Clustering and Feature Selection

Rong Jin, Christina Chan, Linxia Zhang, 2008, PloS one.

Image Tag Completion by Noisy Matrix Recovery

Rong Jin, Anil K. Jain, Songhe Feng, 2014, ECCV.

Non-monotonic feature selection

Zenglin Xu, Jieping Ye, Rong Jin, 2009, ICML '09.

Ordering patterns by combining opinions from multiple sources

Rong Jin, Pang-Ning Tan, P. Tan, 2004, KDD.

Scalable Kernel Clustering: Approximate Kernel k-means pdf

Rong Jin, Anil K. Jain, Timothy C. Havens, 2014, ArXiv.

Compressed Hashing

Xuelong Li, Rong Jin, Shuicheng Yan, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Non-parametric Mixture Models for Clustering

Rong Jin, Anil K. Jain, Pavan Kumar Mallapragada, 2010, SSPR/SPR.

Learning Accurate Entropy Model with Global Reference for Image Compression pdf

Rong Jin, Hao Li, Yichen Qian, 2020, ICLR.

Machine learning for information retrieval

Luo Si, Rong Jin, Rong Jin, 2011, SIGIR.

Large-scale near-duplicate image retrieval by kernel density estimation

Anil K. Jain, Rong Jin, Wei Tong, 2012, International Journal of Multimedia Information Retrieval.

A kernel density based approach for large scale image retrieval

Rong Jin, Tianbao Yang, Anil K. Jain, 2011, ICMR.

Inter-functional analysis of high-throughput phenotype data by non-parametric clustering and its application to photosynthesis

Rong Jin, Jin Chen, Qiaozi Gao, 2015, Bioinform..

A Practical Semi-Parametric Contextual Bandit

Rong Jin, Xuying Meng, Jiahao Liu, 2019, IJCAI.

A Kernel Approach to Multi-Task Learning with Task-Specific Kernels

Wei Wu, Rong Jin, Hang Li, 2012, Journal of Computer Science and Technology.

A statistical framework for query translation disambiguation

Yi Liu, Rong Jin, Joyce Yue Chai, 2006, TALIP.

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data

Jun Wang, Jinfeng Yi, Rong Jin, 2014, ICML.

Learning with Non-Convex Truncated Losses by SGD

Rong Jin, Tianbao Yang, Shenghuo Zhu, 2018, UAI.

MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning

Hao Li, Qian Qi, Rong Jin, 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2015, ALT.

Collaborative image retrieval via regularized metric learning

Luo Si, Rong Jin, Michael R. Lyu, 2006, Multimedia Systems.

Learn to weight terms in information retrieval using category information

Luo Si, Rong Jin, Joyce Yue Chai, 2005, ICML.

Query Translation Disambiguation as Graph Partitioning

Yi Liu, Rong Jin, Rong Jin, 2005, AAAI.

Distance metric learning from uncertain side information with application to automated photo tagging

Nenghai Yu, Lei Wu, Rong Jin, 2009, ACM Multimedia.

Fine-grained visual categorization via multi-stage metric learning

Rong Jin, Qi Qian, Shenghuo Zhu, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Efficient Algorithm for Localized Support

Rong Jin, Pang-Ning Tan, Haibin Cheng, 2010 .

7.2 A 12nm Programmable Convolution-Efficient Neural-Processing-Unit Chip Achieving 825TOPS

Rong Jin, Long Chen, Jun He, 2020, 2020 IEEE International Solid- State Circuits Conference - (ISSCC).

Semi-Supervised Ensemble Ranking

Rong Jin, Steven C. H. Hoi, Rong Jin, 2008, AAAI.

Top Rank Optimization in Linear Time

Rong Jin, Zhi-Hua Zhou, Nan Li, 2014, NIPS.

Online Bandit Learning for a Special Class of Non-Convex Losses

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2015, AAAI.

Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses

Rong Jin, David Simchi-Levi, Sen Yang, 2019, Manag. Sci..

Sparse Learning for Stochastic Composite Optimization

Rong Jin, Xuelong Li, Xiaofei He, 2014, AAAI Conference on Artificial Intelligence.

Large Scale Long-tailed Product Recognition System at Alibaba

Rong Jin, Yun Zheng, Xiangzeng Zhou, 2020, CIKM.

Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning

Rong Jin, Anil K. Jain, Zheyun Feng, 2013, 2013 IEEE International Conference on Computer Vision.

Inferring functional cortical networks from spike train ensembles using Dynamic Bayesian Networks

Rong Jin, Yang Zhou, Karim G. Oweiss, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

Reconstructing functional neuronal circuits using dynamic Bayesian networks

Karim Oweiss, Yang Zhou, Seif Eldawlatly, 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach

Jinfeng Yi, Rong Jin, Anil K. Jain, 2013, HCOMP.

Excess Risk Bounds for Exponentially Concave Losses pdf

Rong Jin, Mehrdad Mahdavi, Rong Jin, 2014, ArXiv.

Efficient Constrained Regret Minimization pdf

Rong Jin, Tianbao Yang, Mehrdad Mahdavi, 2012, ArXiv.

A Potential-based Framework for Online Multi-class Learning with Partial Feedback

Rong Jin, Shijun Wang, Hamed Valizadegan, 2010, AISTATS.

Improved Bounds for the Nyström Method With Application to Kernel Classification

Rong Jin, Zhi-Hua Zhou, Tianbao Yang, 2011, IEEE Transactions on Information Theory.

Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property

Rong Jin, Changshui Zhang, Ming Lin, 2014, UAI.

Effective automatic image annotation via a coherent language model and active learning

Luo Si, Rong Jin, Joyce Yue Chai, 2004, MULTIMEDIA '04.

Robust Graph Structure Learning over Images via Multiple Statistical Tests

Rong Jin, Senzhang Wang, Ming Lin, 2022, ArXiv.

Large-Scale Visual Search with Binary Distributed Graph at Alibaba

Yinghui Xu, Yun Zheng, Yanhao Zhang, 2019, CIKM.

Bayesian Active Distance Metric Learning pdf

Rong Jin, Liu Yang, Rahul Sukthankar, 2007, UAI.

On Stochastic Moving-Average Estimators for Non-Convex Optimization

Tianbao Yang, Yi Xu, Rong Jin, 2021, ArXiv.

Semi-supervised SVM batch mode active learning for image retrieval

Rong Jin, Michael R. Lyu, Steven C. H. Hoi, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Tattoo-ID: Automatic Tattoo Image Retrieval for Suspect and Victim Identification

Rong Jin, Anil K. Jain, Jung-Eun Lee, 2007, PCM.

A Bayesian Framework for Community Detection Integrating Content and Link

Yun Chi, Rong Jin, Tianbao Yang, 2009, UAI.

SemiBoost: Boosting for Semi-Supervised Learning

Anil K. Jain, Pavan Kumar Mallapragada, Rong Jin, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

IQNAS: Interpretable Integer Quadratic Programming Neural Architecture Search pdf

Lihi Zelnik-Manor, Rong Jin, Yonathan Aflalo, 2021, ArXiv.

CobBO: Coordinate Backoff Bayesian Optimization pdf

Jian Tan, Rong Jin, Mengchang Wang, 2021, ArXiv.

Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion

Zhi-Hua Zhou, Rong Jin, Tianbao Yang, 2015, J. Mach. Learn. Res..

Random Projection with Filtering for Nearly Duplicate Search

Rong Jin, Deng Cai, Xiaofei He, 2012, AAAI.

Effective Model Sparsification by Scheduled Grow-and-Prune Methods

Yi Xu, Rong Jin, Yanzhi Wang, 2021, ICLR.