Mingsheng Long

Orcid: 0000-0001-9421-463X

According to our database¹, Mingsheng Long authored at least 166 papers between 2010 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

One Fits Many: Class Confusion Loss for Versatile Domain Adaptation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., November, 2024

Editorial: Learning With Fewer Labels in Computer Vision.

[BibT_eX]

[DOI]

Li Liu

Timothy M. Hospedales

IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2024

Metadata Matters for Time Series: Informative Forecasting with Transformers.

[BibT_eX]

[DOI]

CoRR, 2024

Long-Sequence Recommendation Models Need Decoupled Embeddings.

[BibT_eX]

[DOI]

CoRR, 2024

Deep Time Series Models: A Comprehensive Survey and Benchmark.

[BibT_eX]

[DOI]

CoRR, 2024

Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting.

[BibT_eX]

[DOI]

CoRR, 2024

Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers.

[BibT_eX]

[DOI]

CoRR, 2024

iVideoGPT: Interactive VideoGPTs are Scalable World Models.

[BibT_eX]

[DOI]

CoRR, 2024

RoPINN: Region Optimized Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Supercompiler Code Optimization with Zero-Shot Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers.

[BibT_eX]

[DOI]

CoRR, 2024

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables.

[BibT_eX]

[DOI]

CoRR, 2024

EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics.

[BibT_eX]

[DOI]

CoRR, 2024

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Timer: Transformers for Time Series Analysis at Scale.

[BibT_eX]

[DOI]

CoRR, 2024

Recommender Transformers with Behavior Pathways.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization.

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Transolver: A Fast Transformer Solver for PDEs on General Geometries.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

HarmonyDream: Task Harmonization Inside World Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Timer: Generative Pre-trained Transformers Are Large Time Series Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On the Embedding Collapse when Scaling up Recommendation Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient ConvBN Blocks for Transfer Learning and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

Interpretable weather forecasting for worldwide stations with a unified deep model.

[BibT_eX]

[DOI]

Nat. Mac. Intell., June, 2023

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

From Big to Small: Adaptive Learning to Partial-Set Domains.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Skilful nowcasting of extreme precipitation with NowcastNet.

[BibT_eX]

[DOI]

Nat., 2023

HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation.

[BibT_eX]

[DOI]

CoRR, 2023

Harmony World Models: Boosting Sample Efficiency for Model-based Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Tune-Mode ConvBN Blocks For Efficient Transfer Learning.

[BibT_eX]

[DOI]

CoRR, 2023

ForkMerge: Overcoming Negative Transfer in Multi-Task Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Bi-tuning: Efficient Transfer from Pre-trained Models.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Solving High-Dimensional PDEs with Latent Spectral Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

CLIPood: Generalizing CLIP to Out-of-Distributions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

VideoDG: Generalizing Temporal Relations in Videos to Novel Domains.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2022

Debiased Pseudo Labeling in Self-Training.

[BibT_eX]

[DOI]

CoRR, 2022

Transferability in Deep Learning: A Survey.

[BibT_eX]

[DOI]

CoRR, 2022

Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Debiased Self-Training for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supported Policy Optimization for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Flowformer: Linearizing Transformers with Conservation Flows.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

X-model: Improving Data Efficiency in Deep Learning with A Minimax Model.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Decoupled Adaptation for Cross-Domain Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Continual Predictive Learning from Videos.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Out-of-Dynamics Imitation Learning from Multimodal Demonstrations.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

2021

Preface.

[BibT_eX]

[DOI]

Min-Ling Zhang

Sheng-Jun Huang

Mingsheng Long

J. Comput. Sci. Technol., 2021

Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs.

[BibT_eX]

[DOI]

CoRR, 2021

Omni-Training for Data-Efficient Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Cycle Self-Training for Domain Adaptation.

[BibT_eX]

[DOI]

Hong Liu

Jianmin Wang

Mingsheng Long

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

LogME: Practical Assessment of Pre-trained Models for Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Self-Tuning for Data-Efficient Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Zoo-Tuning: Adaptive Transfer from A Zoo of Models.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Representation Subspace Distance for Domain Adaptation Regression.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Open Domain Generalization with Domain-Augmented Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Regressive Domain Adaptation for Unsupervised Keypoint Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

MetaSets: Meta-Learning on Point Sets for Generalizable Representations.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Transferable Query Selection for Active Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Bi-tuning of Pre-trained Representations.

[BibT_eX]

[DOI]

CoRR, 2020

On Localized Discrepancy for Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, 2020

Co-Tuning for Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Transferable Calibration with Lower Bias and Variance in Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Adapt to Evolving Domains.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Normalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Resource Efficient Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Unsupervised Transfer Learning for Spatiotemporal Predictive Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Multi-Task Learning of Generalizable Representations for Video Action Recognition.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

A Multi-Player Minimax Game for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

Negative Margin Matters: Understanding Margin in Few-Shot Classification.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Minimum Class Confusion for Versatile Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning to Detect Open Classes for Universal Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Progressive Adversarial Networks for Fine-Grained Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Probabilistic Video Prediction From Noisy Data With a Posterior Confidence.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Transferring Pretrained Networks to Small Data via Category Decorrelation.

[BibT_eX]

[DOI]

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Transferable Representation Learning with Deep Adaptation Networks.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Adversarial Pyramid Network for Video Domain Generalization.

[BibT_eX]

[DOI]

CoRR, 2019

Less Confusion More Transferable: Minimum Class Confusion for Versatile Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, 2019

Towards Understanding the Transferability of Deep Representations.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications.

[BibT_eX]

[DOI]

CoRR, 2019

Process Extraction from Texts via Multi-Task Architecture.

[BibT_eX]

[DOI]

CoRR, 2019

WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection.

[BibT_eX]

[DOI]

CoRR, 2019

Transferable Normalization: Towards Improving Transferability of Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Bridging Theory and Algorithm for Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Z-Order Recurrent Neural Networks for Video Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

Eidetic 3D LSTM: A Model for Video Prediction and Beyond.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Maximum-Margin Hamming Hashing.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Universal Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Separate to Adapt: Open Set Domain Adaptation via Progressive Separation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learning to Transfer Examples for Partial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Transferable Attention for Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Transferable Curriculum for Weakly-Supervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Reversing Two-Stream Networks with Decoding Discrepancy Penalty for Robust Action Recognition.

[BibT_eX]

[DOI]

CoRR, 2018

Conditional Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalized Zero-Shot Learning with Deep Calibration Network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Triplet Quantization.

[BibT_eX]

[DOI]

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Deep Priority Hashing.

[BibT_eX]

[DOI]

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

PredCNN: Predictive Learning with Cascade Convolutions.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Partial Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Cross-Modal Hamming Hashing.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Deep Cauchy Hashing for Hamming Space Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Partial Transfer Learning With Selective Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Multi-Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Unsupervised Domain Adaptation With Distribution Matching Machines.

[BibT_eX]

[DOI]

Yue Cao

Mingsheng Long

Jianmin Wang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Transfer Adversarial Hashing for Hamming Space Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Domain Adaptation with Randomized Multilinear Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2017

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Multiple Tasks with Multilinear Relationship Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep Transfer Learning with Joint Adaptation Networks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

HashNet: Deep Learning to Hash by Continuation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Spatiotemporal Pyramid Network for Video Action Recognition.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Deep Visual-Semantic Quantization for Efficient Image Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Correlation Hashing Network for Efficient Cross-Modal Retrieval.

[BibT_eX]

[DOI]

Yue Cao

Mingsheng Long

Jianmin Wang

Proceedings of the British Machine Vision Conference 2017, 2017

Collective Deep Quantization for Efficient Cross-Modal Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Transitive Hashing Network for Heterogeneous Multimedia Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Deep Learning of Transferable Representation for Scalable Domain Adaptation.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2016

Deep Transfer Learning with Joint Adaptation Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

Michael I. Jordan

CoRR, 2016

Unsupervised Domain Adaptation with Residual Transfer Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

Michael I. Jordan

CoRR, 2016

Transitive Hashing Network for Heterogeneous Multimedia Retrieval.

[BibT_eX]

[DOI]

Zhangjie Cao

Mingsheng Long

Qiang Yang

CoRR, 2016

Composite Correlation Quantization for Efficient Multimodal Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Unsupervised Domain Adaptation with Residual Transfer Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Correlation Autoencoder Hashing for Supervised Cross-Modal Search.

[BibT_eX]

[DOI]

Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, 2016

Deep Visual-Semantic Hashing for Cross-Modal Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Deep Hashing Network for Efficient Similarity Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Deep Quantization Network for Efficient Image Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Domain Invariant Transfer Kernel Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2015

Compositional Correlation Quantization for Large-Scale Multimodal Search.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

Philip S. Yu

CoRR, 2015

Learning Multiple Tasks with Deep Relationship Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

CoRR, 2015

Learning Transferable Features with Deep Adaptation Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

CoRR, 2015

Learning Transferable Features with Deep Adaptation Networks.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Adaptation Regularization: A General Framework for Transfer Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2014

Transfer Learning with Graph Co-Regularization.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2014

Local Hybrid Coding for Image Classification.

[BibT_eX]

[DOI]

Wu Xiang

Jianmin Wang

Mingsheng Long

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Transfer Joint Matching for Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Inherent Replica Inconsistency in Cassandra.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Congress on Big Data, Anchorage, AK, USA, June 27, 2014

2013

Twin Bridge Transfer Learning for Sparse Collaborative Filtering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Transfer Feature Learning with Joint Distribution Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2013

Transfer Sparse Coding for Robust Image Representation.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

Dual Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Topic Correlation Analysis for Cross-Domain Text Classification.

[BibT_eX]

[DOI]

Lianghao Li

Xiaoming Jin

Mingsheng Long

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2010

Transfer Learning via Cluster Correspondence Inference.

[BibT_eX]

[DOI]

Proceedings of the ICDM 2010, 2010

Mingsheng Long

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