← Authors

Rong Jin

116 papers · 2002–2025 · 17 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (34) 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (23) 🌍 Conference Polyglot (17) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (10) 🏠 Conference Loyalist (35) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (15) 🀝 Dynamic Duo (26) πŸ† Grand Slam πŸ‘‘ Triple Crown 🌱 Topic Pioneer ❓ The Questioner ⚑ Prolific Year (21) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (159) πŸš€ Conference Pioneer πŸ’Ž Century Club (116) πŸ”₯ Unstoppable (20)

Conferences

NIPS (35) ICML (20) CVPR (18) ICLR (8) AAAI (7) COLT (5) IJCAI (4) ICCV (4) AISTATS (3) JMLR (3) ECCV (2) ACL (2) EMNLP (1) COLING (1) INTERSPEECH (1) NAACL (1) UAI (1)

Top co-authors

Tianbao Yang (26) Lijun Zhang (18) Hao Li (16) Shenghuo Zhu (15) Qi Qian (13) Yi Xu (11) xue wang (11) Zhi-Hua Zhou (10) Mehrdad Mahdavi (10) Ming Lin (9)

Research topics

Core AI (1)

Keywords

stochastic gradient descent (11) convex optimization (10) online learning (10) non-convex optimization (9) regret bound (8) distance metric learning (7) stochastic optimization (7) kernel methods (7) matrix completion (6) semi-supervised learning (6) image classification (6) unsupervised learning (5) convergence rate (5) self-supervised learning (5) empirical risk minimization (5) representation learning (4) support vector machine (4) time series forecasting (4) metric learning (4) contrastive learning (4)

Papers

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment ICML 2025
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? ICLR 2025
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting ICLR 2024
UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks EMNLP 2024
SumCSE: Summary as a transformation for Contrastive Learning NAACL 2024
Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization CVPR 2024
FeDXL: Provable Federated Learning for Deep X-Risk Optimization ICML 2023
One Fits All: Power General Time Series Analysis by Pretrained LM NIPS 2023
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling NIPS 2023
Making Vision Transformers Efficient From a Token Sparsification View CVPR 2023
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation ICML 2023
Progressive Backdoor Erasing via Connecting Backdoor and Adversarial Attacks CVPR 2023
Free Lunch for Domain Adversarial Training: Environment Label Smoothing ICLR 2023
Beyond Appearance: A Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks CVPR 2023
Hybrid Relation Guided Set Matching for Few-Shot Action Recognition CVPR 2022
Learning From Untrimmed Videos: Self-Supervised Video Representation Learning With Hierarchical Consistency CVPR 2022
Unsupervised Visual Representation Learning by Online Constrained K-Means CVPR 2022
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation ICLR 2022
Entroformer: A Transformer-based Entropy Model for Learned Image Compression ICLR 2022
Effective Model Sparsification by Scheduled Grow-and-Prune Methods ICLR 2022
Rethinking Supervised Pre-Training for Better Downstream Transferring ICLR 2022
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation ECCV 2022
KVT: k-NN Attention for Boosting Vision Transformers ECCV 2022
Grow and Merge: A Unified Framework for Continuous Categories Discovery NIPS 2022
Robust Graph Structure Learning via Multiple Statistical Tests NIPS 2022
Improved Fine-Tuning by Better Leveraging Pre-Training Data NIPS 2022
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks NIPS 2022
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting ICML 2022
MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection ICML 2022
Scaled ReLU Matters for Training Vision Transformers AAAI 2022
A Trend-Driven Fashion Design System for Rapid Response Marketing in E-commerce AAAI 2022
Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation ACL 2022
Decoupling and Recoupling Spatiotemporal Representation for RGB-D-Based Motion Recognition CVPR 2022
CHEX: CHannel EXploration for CNN Model Compression CVPR 2022
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting NIPS 2022
Communication Efficient SGD via Gradient Sampling With Bayes Prior CVPR 2021
Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition ICCV 2021
Learning Accurate Entropy Model with Global Reference for Image Compression ICLR 2021
Weakly Supervised Representation Learning With Coarse Labels ICCV 2021
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives NIPS 2021
Learning Position and Target Consistency for Memory-Based Video Object Segmentation CVPR 2021
Self-Supervised Motion Learning From Static Images CVPR 2021
Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning AAAI 2021
Self-Supervised Video Representation Learning by Context and Motion Decoupling CVPR 2021
Dash: Semi-Supervised Learning with Dynamic Thresholding ICML 2021
DR Loss: Improving Object Detection by Distributional Ranking CVPR 2020
Learning with Non-Convex Truncated Losses by SGD UAI 2019
XNAS: Neural Architecture Search with Expert Advice NIPS 2019
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems NIPS 2019
Stagewise Training Accelerates Convergence of Testing Error Over SGD NIPS 2019
Robust Online Matching with User Arrival Distribution Drift AAAI 2019
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee AAAI 2019
Robust Optimization over Multiple Domains AAAI 2019
Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling ICCV 2019
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence ICML 2019
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization ICML 2019
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization ICML 2019
A Practical Semi-Parametric Contextual Bandit IJCAI 2019
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization IJCAI 2019
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019
Multinomial Logit Bandit with Linear Utility Functions IJCAI 2018
Large-Scale Distance Metric Learning With Uncertainty CVPR 2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NIPS 2018
First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time NIPS 2018
Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds COLT 2017
Improved Dynamic Regret for Non-degenerate Functions NIPS 2017
The Opensesame NIST 2016 Speaker Recognition Evaluation System INTERSPEECH 2017
Deep Learning at Alibaba IJCAI 2017
Missing Modalities Imputation via Cascaded Residual Autoencoder CVPR 2017
Online Stochastic Linear Optimization under One-bit Feedback ICML 2016
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection ICML 2015
Theory of Dual-sparse Regularized Randomized Reduction ICML 2015
CUR Algorithm for Partially Observed Matrices ICML 2015
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization COLT 2015
A Simple Homotopy Algorithm for Compressive Sensing AISTATS 2015
Fine-Grained Visual Categorization via Multi-Stage Metric Learning CVPR 2015
Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities NIPS 2014
Efficient Algorithms for Robust One-bit Compressive Sensing ICML 2014
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data ICML 2014
Top Rank Optimization in Linear Time NIPS 2014
Passive Learning with Target Risk COLT 2013
Mixed Optimization for Smooth Functions NIPS 2013
Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning ICCV 2013
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning NIPS 2013
Linear Convergence with Condition Number Independent Access of Full Gradients NIPS 2013
Stochastic Convex Optimization with Multiple Objectives NIPS 2013
Online Kernel Learning with a Near Optimal Sparsity Bound ICML 2013
One-Pass AUC Optimization ICML 2013
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions ICML 2013
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion ICML 2013
Compressed Hashing CVPR 2013
Recovering the Optimal Solution by Dual Random Projection COLT 2013
Online Optimization with Gradual Variations COLT 2012
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning NIPS 2012
Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints JMLR 2012
NystrΓΆm Method vs Random Fourier Features: A Theoretical and Empirical Comparison NIPS 2012
Stochastic Gradient Descent with Only One Projection NIPS 2012
Double Updating Online Learning JMLR 2011
Active Learning by Querying Informative and Representative Examples NIPS 2010
Exclusive Lasso for Multi-task Feature Selection AISTATS 2010
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NIPS 2010
A Potential-based Framework for Online Multi-class Learning with Partial Feedback AISTATS 2010
Learning to Rank by Optimizing NDCG Measure NIPS 2009
Adaptive Regularization for Transductive Support Vector Machine NIPS 2009
Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering NIPS 2009
DUOL: A Double Updating Approach for Online Learning NIPS 2009
Regularized Distance Metric Learning:Theory and Algorithm NIPS 2009
An Extended Level Method for Efficient Multiple Kernel Learning NIPS 2008
Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization NIPS 2008
Multi-label Multiple Kernel Learning NIPS 2008
Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems ACL 2007
Efficient Convex Relaxation for Transductive Support Vector Machine NIPS 2007
Generalized Maximum Margin Clustering and Unsupervised Kernel Learning NIPS 2006
A New Probabilistic Model for Title Generation COLING 2002