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Estimating and Improving Dynamic Treatment Regimes With a Time-Varying Instrumental Variable
Estimating dynamic treatment regimes (DTRs) from retrospective observati...
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Meaningful Adversarial Stickers for Face Recognition in Physical World
Face recognition (FR) systems have been widely applied in safety-critica...
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Image Composition Assessment with Saliency-augmented Multi-pattern Pooling
Image composition assessment is crucial in aesthetic assessment, which a...
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MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes
Deepfakes raised serious concerns on the authenticity of visual contents...
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Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
In this paper, we proposed a novel Style-based Point Generator with Adve...
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A Minimax Probability Machine for Non-Decomposable Performance Measures
Imbalanced classification tasks are widespread in many real-world applic...
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Learning with Smooth Hinge Losses
Due to the non-smoothness of the Hinge loss in SVM, it is difficult to o...
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Do We Really Need Explicit Position Encodings for Vision Transformers?
Almost all visual transformers such as ViT or DeiT rely on predefined po...
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Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network
Recently, real-world recommendation systems need to deal with millions o...
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Convergence of the uniaxial PML method for time-domain electromagnetic scattering problems
In this paper, we propose and study the uniaxial perfectly matched layer...
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Time domain analysis for electromagnetic scattering by an elastic obstacle in a two-layered medium
In this paper, we consider the scattering of a time-dependent electromag...
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Efficient Compressed Sensing Based Image Coding by Using Gray Transformation
In recent years, compressed sensing (CS) based image coding has become a...
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Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
Self-training is a competitive approach in domain adaptive segmentation,...
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Factor Modelling for Clustering High-dimensional Time Series
We propose a new unsupervised learning method for clustering a large num...
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Statistical matching and subclassification with a continuous dose: characterization, algorithms, and inference
Subclassification and matching are often used to adjust for observed cov...
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Full-Resolution Correspondence Learning for Image Translation
We present the full-resolution correspondence learning for cross-domain ...
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Social Distancing and COVID-19: Randomization Inference for a Structured Dose-Response Relationship
Social distancing is widely acknowledged as an effective public health p...
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Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
The learning and evaluation of energy-based latent variable models (EBLV...
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Bi-level Score Matching for Learning Energy-based Latent Variable Models
Score matching (SM) provides a compelling approach to learn energy-based...
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Old Photo Restoration via Deep Latent Space Translation
We propose to restore old photos that suffer from severe degradation thr...
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AutoKWS: Keyword Spotting with Differentiable Architecture Search
Smart audio devices are gated by an always-on lightweight keyword spotti...
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A Simple and General Graph Neural Network with Stochastic Message Passing
Graph neural networks (GNNs) are emerging machine learning models on gra...
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DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Despite the fast development of differentiable architecture search (DART...
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Deep Sketch-guided Cartoon Video Synthesis
We propose a novel framework to produce cartoon videos by fetching the c...
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Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters
Convolutional neural networks (CNNs) have been successfully used in a ra...
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Bridging preference-based instrumental variable studies and cluster-randomized encouragement experiments: study design, noncompliance, and average cluster effect ratio
Instrumental variable methods are widely used in medical and social scie...
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Noisy Differentiable Architecture Search
Simplicity is the ultimate sophistication. Differentiable Architecture S...
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Bringing Old Photos Back to Life
We propose to restore old photos that suffer from severe degradation thr...
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Cross-domain Correspondence Learning for Exemplar-based Image Translation
We present a general framework for exemplar-based image translation, whi...
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Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation
In deep learning tasks, the learning rate determines the update step siz...
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Perceptual Image Super-Resolution with Progressive Adversarial Network
Single Image Super-Resolution (SISR) aims to improve resolution of small...
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Performance Analysis and Optimization in Privacy-Preserving Federated Learning
As a means of decentralized machine learning, federated learning (FL) ha...
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Selecting and ranking individualized treatment rules with unmeasured confounding
It is common to compare individualized treatment rules based on the valu...
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Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction
Session-based target behavior prediction aims to predict the next item t...
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A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Score matching provides an effective approach to learning flexible unnor...
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Estimating Optimal Treatment Rules with an Instrumental Variable: A Partial Identification Learning Approach
Individualized treatment rules (ITRs) are considered a promising recipe ...
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Estimating Optimal Treatment Rules with an Instrumental Variable: A Semi-Supervised Learning Approach
Individualized treatment rules (ITRs) are regarded as a promising recipe...
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Imaging of buried obstacles in a two-layered medium with phaseless far-field data
The inverse problem we consider is to reconstruct the location and shape...
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Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack
Machine learning algorithms, when applied to sensitive data, pose a pote...
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MixPath: A Unified Approach for One-shot Neural Architecture Search
The expressiveness of search space is a key concern in neural architectu...
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Neural Architecture Search on Acoustic Scene Classification
Convolutional neural networks are widely adopted in Acoustic Scene Class...
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Latent Variables on Spheres for Sampling and Spherical Inference
Variational inference is a fundamental problem in Variational Auto-Encod...
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Triple Generative Adversarial Networks
Generative adversarial networks (GANs) have shown promise in image gener...
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Realization of spatial sparseness by deep ReLU nets with massive data
The great success of deep learning poses urgent challenges for understan...
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Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning
The quality control of fetal sonographic (FS) images is essential for th...
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Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search
Differential Architecture Search (DARTS) is now a widely disseminated we...
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DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures
Bayesian neural networks (BNNs) introduce uncertainty estimation to deep...
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Instrumental Variables: to Strengthen or not to Strengthen?
Instrumental variables (IV) are extensively used to estimate treatment e...
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In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics
Tens of millions of women suffer from infertility worldwide each year. I...
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Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction
Improving the performance of click-through rate (CTR) prediction remains...
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