
Denoising Relation Extraction from Documentlevel Distant Supervision
Distant supervision (DS) has been widely used to generate autolabeled d...
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Knowledge Transfer via Pretraining for Recommendation: A Review and Prospect
Recommender systems aim to provide item recommendations for users, and a...
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Robust Autoencoder GAN for CryoEM Image Denoising
The cryoelectron microscopy (CryoEM) becomes popular for macromolecula...
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Multisource Heterogeneous Domain Adaptation with Conditional Weighting Adversarial Network
Heterogeneous domain adaptation (HDA) tackles the learning of crossdoma...
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Leveraging both Lesion Features and Procedural Bias in Neuroimaging: An DualTask Split dynamics of inverse scale space
The prediction and selection of lesion features are two important tasks ...
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How to trust unlabeled data? Instance Credibility Inference for FewShot Learning
Deep learning based models have excelled in many computer vision task an...
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DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths
Overparameterization is ubiquitous nowadays in training neural networks...
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Crossmodal Language Grounding in an Embodied Neurocognitive Model
Human infants are able to acquire natural language seemingly easily at a...
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Video Playback Rate Perception for SelfsupervisedSpatioTemporal Representation Learning
In selfsupervised spatiotemporal representation learning, the temporal...
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Exploring Private Federated Learning with Laplacian Smoothing
Federated learning aims to protect data privacy by collaboratively learn...
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Boosting Semantic Human Matting with Coarse Annotations
Semantic human matting aims to estimate the perpixel opacity of the for...
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Learning the mapping x∑_i=1^d x_i^2: the cost of finding the needle in a haystack
The task of using machine learning to approximate the mapping x∑_i=1^d x...
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Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction
Reconstruction of a 3D shape from a single 2D image is a classical compu...
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SMAUG: EndtoEnd FullStack Simulation Infrastructure for Deep Learning Workloads
In recent years, there has been tremendous advances in hardware accelera...
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Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size
Learning representation from relative similarity comparisons, often call...
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Adversarial Language Games for Advanced Natural Language Intelligence
While adversarial games have been well studied in various board games an...
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iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
Due to the inherent uncertainty of data, the problem of predicting parti...
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Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
Bayesian deep learning is recently regarded as an intrinsic way to chara...
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OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
OpenNRE is an opensource and extensible toolkit that provides a unified...
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An Acceleration Framework for High Resolution Image Synthesis
Synthesis of high resolution images using Generative Adversarial Network...
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Heterogeneous Domain Adaptation via Soft Transfer Network
Heterogeneous domain adaptation (HDA) aims to facilitate the learning ta...
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DocRED: A LargeScale DocumentLevel Relation Extraction Dataset
Multiple entities in a document generally exhibit complex intersentence...
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Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence
Overparameterization is ubiquitous nowadays in training neural networks...
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Efficient Estimation For The Cox Proportional Hazards Cure Model
While analysing timetoevent data, it is possible that a certain fracti...
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S^2LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning
This paper proposes a novel Stochastic Split Linearized Bregman Iteratio...
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Deep Robust Subjective Visual Property Prediction in Crowdsourcing
The problem of estimating subjective visual properties (SVP) of images (...
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Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
Robust scatter estimation is a fundamental task in statistics. The recen...
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BOLTSSI: A Statistical Approach to Screening Interaction Effects for UltraHigh Dimensional Data
Detecting interaction effects is a crucial step in various applications....
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A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning
Efficient training of deep neural networks (DNNs) is a challenge due to ...
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Attentionaware Multistroke Style Transfer
Neural style transfer has drawn considerable attention from both academi...
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Multiview Crosssupervision for Semantic Segmentation
This paper presents a semisupervised learning framework for a customize...
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FewRel: A LargeScale Supervised FewShot Relation Classification Dataset with StateoftheArt Evaluation
We present a FewShot Relation Classification Dataset (FewRel), consisti...
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DataDriven Tight Frame for CryoEM Image Denoising and Conformational Classification
The cryoelectron microscope (cryoEM) is increasingly popular these yea...
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A Unified Dynamic Approach to Sparse Model Selection
Sparse model selection is ubiquitous from linear regression to graphical...
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On Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics
Margin enlargement over training data has been an important strategy sin...
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Robust Estimation and Generative Adversarial Nets
Robust estimation under Huber's ϵcontamination model has become an impo...
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A Marginbased MLE for Crowdsourced Partial Ranking
A preference order or ranking aggregated from pairwise comparison data i...
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FDRHS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
Recent studies found that in voxelbased neuroimage analysis, detecting ...
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MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Fewshot and Zeroshot Learning
It is one typical and general topic of learning a good embedding model t...
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MONET: Multiview Semisupervised Keypoint via Epipolar Divergence
This paper presents MONETan endtoend semisupervised learning frame...
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A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
Training deep neural networks (DNNs) efficiently is a challenge due to t...
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From Social to Individuals: a Parsimonious Path of Multilevel Models for Crowdsourced Preference Aggregation
In crowdsourced preference aggregation, it is often assumed that all the...
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Block Coordinate Descent for Deep Learning: Unified Convergence Guarantees
Training deep neural networks (DNNs) efficiently is a challenge due to t...
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Zeroshot Learning via SharedReconstructionGraph Pursuit
Zeroshot learning (ZSL) aims to recognize objects from novel unseen cla...
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Stochastic Nonconvex Ordinal Embedding with Stabilized BarzilaiBorwein Step Size
Learning representation from relative similarity comparisons, often call...
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HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation
Recently, crowdsourcing has emerged as an effective paradigm for humanp...
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Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics
Nonconvex optimization problems arise in different research fields and a...
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Exploring Outliers in Crowdsourced Ranking for QoE
Outlier detection is a crucial part of robust evaluation for crowdsource...
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Visual Attribute Transfer through Deep Image Analogy
We propose a new technique for visual attribute transfer across images t...
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Boosting with Structural Sparsity: A Differential Inclusion Approach
Boosting as gradient descent algorithms is one popular method in machine...
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Yuan Yao
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Associate Professor at The Hong Kong University of Science and Technology