Mingming Gong

发表

Domain Adaptation with Conditional Transferable Components

Bernhard Schölkopf, Dacheng Tao, Mingming Gong, 2016, ICML.

Deep Domain Generalization via Conditional Invariant Adversarial Networks

D. Tao, Mingming Gong, Kun Zhang, 2018, ECCV.

Deep Ordinal Regression Network for Monocular Depth Estimation

Dacheng Tao, Mingming Gong, Chaohui Wang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Multi-Source Domain Adaptation: A Causal View

Bernhard Schölkopf, Mingming Gong, Kun Zhang, 2015, AAAI.

Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering

Pengtao Xie, Eric P. Xing, Kun Zhang, 2019, NeurIPS.

Domain Generalization via Conditional Invariant Representation pdf

Dacheng Tao, Ya Li, Mingming Gong, 2018, ArXiv.

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

Barnabás Póczos, Nematollah Batmanghelich, Mingming Gong, 2018, MICCAI.

LTF: A Label Transformation Framework for Correcting Target Shift

D. Tao, Mingming Gong, Tongliang Liu, 2020 .

Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping

D. Tao, Mingming Gong, Kun Zhang, 2018, ArXiv.

Causal Generative Domain Adaptation Networks pdf

Dacheng Tao, Mingming Gong, Clark Glymour, 2018, ArXiv.

Causal and causally-inspired learning

Mingming Gong, 2017 .

Not “ monkey ” Not “ prairie dog ” Not “ meerkat ” ComplementaryLabel True Label Meerkat MonkeyPrairie Dog

D. Tao, Mingming Gong, Tongliang Liu, 2018 .

Material for “ Causal Discovery and Forecasts in Nonstationary Environments with State-Space Models ”

C. Glymour, Mingming Gong, Kun Zhang, 2019 .

On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis

Mingming Gong, J. Manton, U. Aickelin, 2022, ArXiv.

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models

Mingming Gong, Kun Zhang, Tongliang Liu, 2022, 2205.13869.

Instance-dependent Label-noise Learning under a Structural Causal Model

Mingming Gong, Tongliang Liu, Bo Han, 2021, NeurIPS.

CausalAdv: Adversarial Robustness through the Lens of Causality

B. Schölkopf, B. Scholkopf, Mingming Gong, 2021, 2106.06196.

Domain Generalization via Entropy Regularization

Tongliang Liu, Dacheng Tao, Mingming Gong, 2020, NeurIPS.

Few-Shot Font Generation by Learning Fine-Grained Local Styles

Mingming Gong, Errui Ding, Zhibin Hong, 2022, ArXiv.

Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint

Mingming Gong, Huan Fu, Jiaxian Guo, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption

Mingming Gong, Errui Ding, Jingdong Wang, 2022, ArXiv.

Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data

Mingming Gong, Tongliang Liu, Haikun Wei, 2022, Knowledge Discovery and Data Mining.

Rethinking Class-Prior Estimation for Positive-Unlabeled Learning

Masashi Sugiyama, M. Sugiyama, D. Tao, 2020, ICLR.

Identifying Latent Causal Content for Multi-Source Domain Adaptation

Mingming Gong, Biwei Huang, J. Shi, 2022, ArXiv.

On the Sparse DAG Structure Learning Based on Adaptive Lasso

Mingming Gong, Wei Huang, Erdun Gao, 2022, 2209.02946.

Counterfactual Fairness with Partially Known Causal Graph

Mingming Gong, Kun Zhang, Tongliang Liu, 2022, ArXiv.

Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis

Mingming Gong, K. Batmanghelich, K. Yu, 2022, IEEE Journal of Biomedical and Health Informatics.

Truncated Matrix Power Iteration for Differentiable DAG Learning

Mingming Gong, Ehsan Abbasnejad, J. Shi, 2022, 2208.14571.

Weight-variant Latent Causal Models

A. V. Hengel, Mingming Gong, Dong Gong, 2022, ArXiv.

Identifying Weight-Variant Latent Causal Models

A. V. Hengel, Mingming Gong, Biwei Huang, 2022, 2208.14153.

C AUSAL A DV : A DVERSARIAL R OBUSTNESS THROUGH THE L ENS OF C AUSALITY

B. Schölkopf, Mingming Gong, Tongliang Liu, 2022 .

A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning

Mingming Gong, Dacheng Tao, Jixian Guo, 2022, ICLR.

Identifying Latent Causal Content for Multi-Source Domain Adaptation

Mingming Gong, Biwei Huang, J. Shi, 2022, ArXiv.

Uncertainty-Aware Clustering for Unsupervised Domain Adaptive Object Re-Identification pdf

Dacheng Tao, Mingming Gong, Kui Jia, 2021, IEEE Transactions on Multimedia.

Style Interleaved Learning for Generalizable Person Re-identification

Mingming Gong, K. Jia, Changxing Ding, 2022, ArXiv.

Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations

Mingming Gong, Tongliang Liu, Dacheng Tao, 2022, ArXiv.

3D-FUTURE: 3D Furniture Shape with TextURE pdf

Lin Gao, Dacheng Tao, Binqiang Zhao, 2020, International Journal of Computer Vision.

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style

Mingming Gong, Tongliang Liu, Bo Han, 2022, International Conference on Learning Representations.

Sample Selection with Uncertainty of Losses for Learning with Noisy Labels

Masashi Sugiyama, M. Sugiyama, Mingming Gong, 2021, International Conference on Learning Representations.

Truncated Matrix Power Iteration for Differentiable DAG Learning

Mingming Gong, Ehsan Abbasnejad, J. Shi, 2022, NeurIPS.

On the Sparse DAG Structure Learning Based on Adaptive Lasso

Mingming Gong, Wei Huang, Erdun Gao, 2022, ArXiv.

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models

Mingming Gong, Kun Zhang, Tongliang Liu, 2022, ArXiv.

FedDAG: Federated DAG Structure Learning

Mingming Gong, Tongliang Liu, H. Bondell, 2021, 2112.03555.

FedDAG: Federated DAG Structure Learning

Mingming Gong, Tongliang Liu, H. Bondell, 2021, Trans. Mach. Learn. Res..

Parts-dependent Label Noise: Towards Instance-dependent Label Noise pdf

Gang Niu, Nannan Wang, Tongliang Liu, 2020, ArXiv.

Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets

Kun Zhang, Clark Glymour, Mingming Gong, 2020, AAAI.

Unpaired data empowers association tests

Peng Liu, Petar Stojanov, Kayhan Batmanghelich, 2019, bioRxiv.

Low-Dimensional Density Ratio Estimation for Covariate Shift Correction

Jaime G. Carbonell, Mingming Gong, Petar Stojanov, 2019, AISTATS.

Towards Mixture Proportion Estimation without Irreducibility pdf

Gang Niu, Yu Yao, Masashi Sugiyama, 2020, ArXiv.

Learning with Biased Complementary Labels

Dacheng Tao, Mingming Gong, Tongliang Liu, 2017, ECCV.

Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?

J. Carbonell, Mingming Gong, P. Stojanov, 2021, NeurIPS.

LTF: A Label Transformation Framework for Correcting Label Shift

Dacheng Tao, Tongliang Liu, Mingming Gong, 2020, ICML.

Domain Adaptation As a Problem of Inference on Graphical Models pdf

Kun Zhang, Petar Stojanov, Clark Glymour, 2020, NeurIPS.

Data-Driven Approach to Multiple-Source Domain Adaptation

Jaime G. Carbonell, Mingming Gong, Petar Stojanov, 2019, AISTATS.

DERF: Distinctive Efficient Robust Features From the Biological Modeling of the P Ganglion Cells

Dacheng Tao, Hui Wei, Dawei Weng, 2015, IEEE Transactions on Image Processing.

Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping

Kun Zhang, Dacheng Tao, Mingming Gong, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A method using long digital straight segments for fingerprint recognition

Xinge You, Mingming Gong, Xiubao Jiang, 2012, Neurocomputing.

Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation

Mingming Gong, Shaoan Xie, K. Batmanghelich, 2022, MICCAI.

Domain Generalization via Conditional Invariant Representations

Dacheng Tao, Ya Li, Mingming Gong, 2018, AAAI.

Twin Auxilary Classifiers GAN

Kun Zhang, Yanwu Xu, Kayhan Batmanghelich, 2019, NeurIPS.

Adaptive Context-Aware Multi-Modal Network for Depth Completion

Dacheng Tao, Mingming Gong, Huan Fu, 2020, IEEE Transactions on Image Processing.

Sample Selection with Uncertainty of Losses for Learning with Noisy Labels pdf

Mingming Gong, Masashi Sugiyama, Tongliang Liu, 2021, ICLR.

Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results

Kun Zhang, Mingming Gong, Clark Glymour, 2018, UAI.

HRSiam: High-Resolution Siamese Network, Towards Space-Borne Satellite Video Tracking

Bo Du, Mingming Gong, Chen Wu, 2021, IEEE Transactions on Image Processing.

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style

Mingming Gong, Tongliang Liu, Bo Han, 2022, ICLR.

Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization pdf

Mingming Gong, Lanfen Lin, Kun Kuang, 2021, ArXiv.

Sub-center ArcFace: Boosting Face Recognition by Large-Scale Noisy Web Faces

Stefanos Zafeiriou, Jia Guo, Tongliang Liu, 2020, ECCV.

An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption

Dacheng Tao, Mingming Gong, Kayhan Batmanghelich, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Video Summarization Based on Video-text Modelling

Li Haopeng, Ke Qiuhong, Zhang Rui, 2022, ArXiv.

Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Dacheng Tao, Mingming Gong, Shanshan Zhao, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis

D. Tao, Mingming Gong, Shanshan Zhao, 2022, ArXiv.

Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning pdf

Dacheng Tao, Shunming Li, Binqiang Zhao, 2020, NeurIPS.

A Coarse-Fine Network for Keypoint Localization

Dacheng Tao, Mingming Gong, Shaoli Huang, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Exploring Set Similarity for Dense Self-supervised Representation Learning

Mingming Gong, Tongliang Liu, Guoxin Zhang, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Class2Simi: A New Perspective on Learning with Label Noise pdf

Gang Niu, Nannan Wang, Tongliang Liu, 2020, ArXiv.

Learning with Group Noise

Hongxia Yang, Chen Gong, Mingming Gong, 2021, AAAI.

Adversarial Robustness through the Lens of Causality pdf

Bernhard Schölkopf, Mingming Gong, Xinmei Tian, 2022, ICLR.

Short-Term and Long-Term Context Aggregation Network for Video Inpainting

Rui Zhang, Dacheng Tao, Ang Li, 2020, ECCV.

Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models

Kun Zhang, Clark Glymour, Biwei Huang, 2019, ICML.

Understanding Robust Overfitting of Adversarial Training and Beyond

Mingming Gong, Tongliang Liu, Bo Han, 2022, ICML.

Counterfactual Fairness with Partially Known Causal Graph

Mingming Gong, Kun Zhang, Tongliang Liu, 2022, NeurIPS.

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models

Mingming Gong, Kun Zhang, Tongliang Liu, 2022, NeurIPS.

Federated Causal Discovery pdf

Mingming Gong, Tongliang Liu, Erdun Gao, 2021, ArXiv.

Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis pdf

Li Sun, Yanwu Xu, Ke Yu, 2020, IEEE Journal of Biomedical and Health Informatics.

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning pdf

Gang Niu, Yu Yao, Tongliang Liu, 2020, NeurIPS.

MetaComp: Learning to Adapt for Online Depth Completion

Mingming Gong, Wei Ji, Y. Chen, 2022, ArXiv.

On the Sparse DAG Structure Learning Based on Adaptive Lasso

Mingming Gong, Wei Huang, Erdun Gao, 2022, ArXiv.

Strength-Adaptive Adversarial Training

Mingming Gong, Tongliang Liu, Bo Han, 2022, arXiv.org.

Local Metric Learning for Exemplar-Based Object Detection

Xinge You, Qiang Li, Dacheng Tao, 2014, IEEE Transactions on Circuits and Systems for Video Technology.

Fair Classification with Instance-dependent Label Noise

Mingming Gong, Tongliang Liu, Bo Han, 2022, CLeaR.

Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption

Mingming Gong, Errui Ding, Jingdong Wang, 2022, ArXiv.

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

Mingming Gong, Tongliang Liu, Bo Han, 2020, ICML.

Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation

Masashi Sugiyama, M. Sugiyama, Mingming Gong, 2023, ICML.

Correcting the Triplet Selection Bias for Triplet Loss

Dacheng Tao, Mingming Gong, Tongliang Liu, 2018, ECCV.

Label-Noise Robust Domain Adaptation

Dacheng Tao, Kun Zhang, Kayhan Batmanghelich, 2020, ICML.

Deep Learning is Singular, and That's Good pdf

Daniel Murfet, Susan Wei, Mingming Gong, 2020, IEEE transactions on neural networks and learning systems.

MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning

Philip H. S. Torr, Mingming Gong, Yuchen Guo, 2022, SIGIR.

Receptive Field Size Versus Model Depth for Single Image Super-Resolution

Dacheng Tao, Ruxin Wang, Mingming Gong, 2020, IEEE Transactions on Image Processing.

Generative-Discriminative Complementary Learning

Kun Zhang, Mingming Gong, Tongliang Liu, 2019, AAAI.

Unaligned Image-to-Image Translation by Learning to Reweight pdf

Mingming Gong, Kun Zhang, Yanwu Xu, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Unpaired Image-to-Image Translation with Shortest Path Regularization

Mingming Gong, Shaoan Xie, Yanwu Xu, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

M ULTI - DOMAIN IMAGE GENERATION AND TRANSLA - TION WITH IDENTIFIABILITY GUARANTEES

Mingming Gong, Shaoan Xie, Lingjing Kong, 2023 .

Dual-Regularization Complementary Learning for Image Classification

Bo Du, Mingming Gong, Yutian Lin, 2021, 2021 IEEE International Conference on Multimedia and Expo (ICME).

Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation

Mingming Gong, Shaoan Xie, K. Batmanghelich, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Learning World Models with Identifiable Factorization

Mingming Gong, Biwei Huang, Yang Yu, 2023, NeurIPS.

MoE-SPNet: A Mixture-of-Experts Scene Parsing Network

Dacheng Tao, Mingming Gong, Chaohui Wang, 2018, Pattern Recognit..

Large-Cone Nonnegative Matrix Factorization

Dacheng Tao, Mingming Gong, Tongliang Liu, 2017, IEEE Transactions on Neural Networks and Learning Systems.

Efficient Group Learning with Hypergraph Partition in Multi-task Learning

Yu Liu, Xinge You, Mingming Gong, 2012, CCPR.

Few-Shot Font Generation by Learning Fine-Grained Local Styles

Mingming Gong, Errui Ding, Zhibin Hong, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Causal Discovery in the Presence of Measurement Error: Identifiability Conditions pdf

Mingming Gong, Clark Glymour, Kun Zhang, 2017, ArXiv.

Transfer Learning with Label Noise

Kun Zhang, Dacheng Tao, Mingming Gong, 2017, 1707.09724.

Improving clinical disease subtyping and future events prediction through a chest CT‐based deep learning approach

Mingming Gong, K. Batmanghelich, F. Sciurba, 2020, Medical Physics (Lancaster).

SERVE: Soft and Equalized Residual VEctors for image retrieval

Changyin Sun, Jun Li, Mingming Gong, 2016, Neurocomputing.

Style Interleaved Learning for Generalizable Person Re-Identification

Mingming Gong, K. Jia, Changxing Ding, 2022, IEEE Transactions on Multimedia.

Identifying Weight-Variant Latent Causal Models

Mingming Gong, Biwei Huang, Kun Zhang, 2022, 2208.14153.

Instance Correction for Learning with Open-set Noisy Labels pdf

Mingming Gong, Masashi Sugiyama, Tongliang Liu, 2021, ArXiv.

Causal Discovery from Temporally Aggregated Time Series

Bernhard Schölkopf, Dacheng Tao, Mingming Gong, 2017, UAI.

Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation

Mingming Gong, Bo Du, Ziye Chen, 2020, IJCAI.

Twin Auxiliary Classifiers GAN

Mingming Gong, Yanwu Xu, Kayhan Batmanghelich, 2019, Advances in neural information processing systems.

Multi-Class Classification from Noisy-Similarity-Labeled Data pdf

Gang Niu, Tongliang Liu, Bo Han, 2020, ArXiv.

Label-Noise Robust Domain Adaptation Supplementary Material

D. Tao, Mingming Gong, Kun Zhang, 2020 .

Clustering Based Image Denoising Using SURE-LET

Xinge You, Mingming Gong, Xiubao Jiang, 2011, 2011 Seventh International Conference on Computational Intelligence and Security.

3D-BoxSup: Positive-Unlabeled Learning of Brain Tumor Segmentation Networks From 3D Bounding Boxes

Yanwu Xu, Kayhan Batmanghelich, Junxiang Chen, 2020, Frontiers in Neuroscience.

Do We Need to Penalize Variance of Losses for Learning with Label Noise?

Mingming Gong, Tongliang Liu, Bo Han, 2022, ArXiv.

Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?

Mingming Gong, Tongliang Liu, Bo Han, 2023, ICML.

SELF-SUPERVISED VISUAL PRE-TRAINING

Mingming Gong, Tongliang Liu, Yandong Guo, 2023 .

Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision pdf

Mingming Gong, Kayhan Batmanghelich, Yanwu Xu, 2021, ArXiv.

Domain Adaptation As a Problem of Inference on Graphical Models

C. Glymour, Mingming Gong, Kun Zhang, 2020, NeurIPS.

Discovering Temporal Causal Relations from Subsampled Data

Bernhard Schölkopf, Dacheng Tao, Mingming Gong, 2015, ICML.

A Compromise Principle in Deep Monocular Depth Estimation pdf

Dacheng Tao, Mingming Gong, Chaohui Wang, 2017, ArXiv.

Modeling Dynamic Missingness of Implicit Feedback for Recommendation

Kun Zhang, Mingming Gong, Menghan Wang, 2018, NeurIPS.

Multi-domain image generation and translation with identifiability guarantees

Mingming Gong, Shaoan Xie, Lingjing Kong, 2023, ICLR.

Supplementary Materials For: "Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?"

J. Carbonell, Mingming Gong, P. Stojanov, 2021 .

Mosaic Representation Learning for Self-supervised Visual Pre-training

Mingming Gong, Tongliang Liu, Yandong Guo, 2023, ICLR.

Long digital straight segments for fingerprint matching

Xinge You, Mingming Gong, Xiubao Jiang, 2010, 2010 International Conference on Machine Learning and Cybernetics.

Bridging Causality and Learning: How Do They Benefit from Each Other?

Mingming Gong, 2020, IJCAI.

Likelihood-Free Overcomplete ICA and Applications in Causal Discovery pdf

Dacheng Tao, Mingming Gong, Kun Zhang, 2019, NeurIPS.

Discovery of the Hidden World with Large Language Models

Mingming Gong, Yongqiang Chen, Bo Han, 2024, ArXiv.

Identifying Weight-Variant Latent Causal Models

Mingming Gong, Biwei Huang, Kun Zhang, 2022, 2208.14153.