b'Mingming Gong'

Learning with Group Noise

Machine learning in the context of noise is a challenging but practical ...
03/17/2021 ∙ by Qizhou Wang, et al. ∙ 0 ∙ share

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

Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D ...
10/23/2020 ∙ by Huan Fu, et al. ∙ 0 ∙ share

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Deep Learning is Singular, and That's Good

In singular models, the optimal set of parameters forms an analytic set ...
10/22/2020 ∙ by Daniel Murfet, et al. ∙ 0 ∙ share

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3D-FUTURE: 3D Furniture shape with TextURE

The 3D CAD shapes in current 3D benchmarks are mostly collected from onl...
09/21/2020 ∙ by Huan Fu, et al. ∙ 16 ∙ share

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Adaptive Context-Aware Multi-Modal Network for Depth Completion

Depth completion aims to recover a dense depth map from the sparse depth...
08/25/2020 ∙ by Shanshan Zhao, et al. ∙ 0 ∙ share

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

Learning with the instance-dependent label noise is challenging, because...
06/14/2020 ∙ by Xiaobo Xia, et al. ∙ 0 ∙ share

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Class2Simi: A New Perspective on Learning with Label Noise

Label noise is ubiquitous in the era of big data. Deep learning algorith...
06/14/2020 ∙ by Songhua Wu, et al. ∙ 0 ∙ share

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

The transition matrix, denoting the transition relationship from clean l...
06/14/2020 ∙ by Yu Yao, et al. ∙ 0 ∙ share

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Multi-Class Classification from Noisy-Similarity-Labeled Data

A similarity label indicates whether two instances belong to the same cl...
02/16/2020 ∙ by Songhua Wu, et al. ∙ 9 ∙ share

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Towards Mixture Proportion Estimation without Irreducibility

Mixture proportion estimation (MPE) is a fundamental problem of practica...
02/10/2020 ∙ by Yu Yao, et al. ∙ 1 ∙ share

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Domain Adaptation As a Problem of Inference on Graphical Models

This paper is concerned with data-driven unsupervised domain adaptation,...
02/09/2020 ∙ by Kun Zhang, et al. ∙ 20 ∙ share

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Likelihood-Free Overcomplete ICA and Applications in Causal Discovery

Causal discovery witnessed significant progress over the past decades. I...
09/04/2019 ∙ by Chenwei Ding, et al. ∙ 0 ∙ share

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Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach

Majority of state-of-the-art monocular depth estimation methods are supe...
07/16/2019 ∙ by Yipeng Mou, et al. ∙ 1 ∙ share

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Twin Auxiliary Classifiers GAN

Conditional generative models enjoy remarkable progress over the past fe...
07/05/2019 ∙ by Mingming Gong, et al. ∙ 2 ∙ share

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

In many scientific fields, such as economics and neuroscience, we are of...
05/26/2019 ∙ by Biwei Huang, et al. ∙ 0 ∙ share

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Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Supervised depth estimation has achieved high accuracy due to the advanc...
04/03/2019 ∙ by Shanshan Zhao, et al. ∙ 0 ∙ share

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Generative-Discriminative Complementary Learning

Majority of state-of-the-art deep learning methods for vision applicatio...
04/02/2019 ∙ by Yanwu Xu, et al. ∙ 0 ∙ share

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Robust Angular Local Descriptor Learning

In recent years, the learned local descriptors have outperformed handcra...
01/21/2019 ∙ by Yanwu Xu, et al. ∙ 0 ∙ share

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Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...
11/05/2018 ∙ by Spyridon Bakas, et al. ∙ 0 ∙ share

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

Unsupervised domain mapping aims at learning a function to translate dom...
09/16/2018 ∙ by Huan Fu, et al. ∙ 2 ∙ share

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Domain Generalization via Conditional Invariant Representation

Domain generalization aims to apply knowledge gained from multiple label...
07/23/2018 ∙ by Ya Li, et al. ∙ 0 ∙ share

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

We propose an attention-based method that aggregates local image feature...
06/28/2018 ∙ by Sumedha Singla, et al. ∙ 0 ∙ share

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

Scene parsing is an indispensable component in understanding the semanti...
06/19/2018 ∙ by Huan Fu, et al. ∙ 2 ∙ share

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Deep Ordinal Regression Network for Monocular Depth Estimation

Monocular depth estimation, which plays a crucial role in understanding ...
06/06/2018 ∙ by Huan Fu, et al. ∙ 0 ∙ share

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Causal Generative Domain Adaptation Networks

We propose a new generative model for domain adaptation, in which traini...
04/12/2018 ∙ by Mingming Gong, et al. ∙ 0 ∙ share

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Learning with Biased Complementary Labels

In this paper we study the classification problem in which we have acces...
11/27/2017 ∙ by Xiyu Yu, et al. ∙ 0 ∙ share

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A Compromise Principle in Deep Monocular Depth Estimation

Monocular depth estimation, which plays a key role in understanding 3D s...
08/28/2017 ∙ by Huan Fu, et al. ∙ 0 ∙ share

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Transfer Learning with Label Noise

Transfer learning aims to improve learning in the target domain with lim...
07/31/2017 ∙ by Xiyu Yu, et al. ∙ 0 ∙ share

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Causal Discovery in the Presence of Measurement Error: Identifiability Conditions

Measurement error in the observed values of the variables can greatly ch...
06/10/2017 ∙ by Kun Zhang, et al. ∙ 0 ∙ share

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Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components

A widely applied approach to causal inference from a non-experimental ti...
11/14/2014 ∙ by Philipp Geiger, et al. ∙ 0 ∙ share

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Mingming Gong

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