
VarNet: Variational Neural Networks for the Solution of Partial Differential Equations
In this paper we propose a new modelbased unsupervised learning method,...
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A Meanfield Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth
Training deep neural networks with stochastic gradient descent (SGD) can...
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Toward Automatic Threat Recognition for Airport Xray Baggage Screening with Deep Convolutional Object Detection
For the safety of the traveling public, the Transportation Security Admi...
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ParkingSticker: A RealWorld Object Detection Dataset
We present a new and challenging object detection dataset, ParkingSticke...
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Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach
A deep neural network (DNN) that can reliably model muscle responses fro...
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Generative Adversarial Network Training is a Continual Learning Problem
Generative Adversarial Networks (GANs) have proven to be a powerful fram...
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DeepObfuscator: Adversarial Training Framework for PrivacyPreserving Image Classification
Deep learning has been widely utilized in many computer vision applicati...
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Enhancing Crosstask BlackBox Transferability of Adversarial Examples with Dispersion Reduction
Neural networks are known to be vulnerable to carefully crafted adversar...
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Stochastic Gradient Descent Escapes Saddle Points Efficiently
This paper considers the perturbed stochastic gradient descent algorithm...
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How You Act Tells a Lot: PrivacyLeakage Attack on Deep Reinforcement Learning
Machine learning has been widely applied to various applications, some o...
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A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm
In this note, we derive concentration inequalities for random vectors wi...
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In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction
In recent years, academics and investigative journalists have criticized...
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LaneNet: RealTime Lane Detection Networks for Autonomous Driving
Lane detection is to detect lanes on the road and provide the accurate l...
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Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization
We improve the robustness of deep neural nets to adversarial attacks by ...
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Nonparametric Deconvolution Models
We describe nonparametric deconvolution models (NDMs), a family of Bayes...
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ModelBased Learning of Turbulent Flows using Mobile Robots
In this paper we consider the problem of modelbased learning of turbule...
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The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure
There is a stark disparity between the step size schedules used in pract...
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A DeepLearning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images
We consider thyroidmalignancy prediction from ultrahighresolution who...
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Learning Diverse Fashion Collocation by Neural Graph Filtering
Fashion recommendation systems are highly desired by customers to find v...
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Survival Function Matching for Calibrated TimetoEvent Predictions
Models for predicting the time of a future event are crucial for risk as...
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Influence Function based Data Poisoning Attacks to TopN Recommender Systems
Recommender system is an essential component of web services to engage u...
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Learning Lowrank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Modern deep neural networks (DNNs) often require high memory consumption...
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SpiderBoost: A Class of Faster Variancereduced Algorithms for Nonconvex Optimization
There has been extensive research on developing stochastic variance redu...
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Learning Diverse Stochastic HumanAction Generators by Learning Smooth Latent Transitions
Humanmotion generation is a longstanding challenging task due to the r...
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Geometric Matrix Completion with Deep Conditional Random Fields
The problem of completing highdimensional matrices from a limited set o...
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Knowledgedriven Encode, Retrieve, Paraphrase for Medical Image Report Generation
Generating long and semanticcoherent reports to describe medical images...
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TRP: Trained Rank Pruning for Efficient Deep Neural Networks
To enable DNNs on edge devices like mobile phones, lowrank approximatio...
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NTIRE 2020 Challenge on Image and Video Deblurring
Motion blur is one of the most common degradation artifacts in dynamic s...
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This looks like that: deep learning for interpretable image recognition
When we are faced with challenging image classification tasks, we often ...
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Expression of Fractals Through Neural Network Functions
To help understand the underlying mechanisms of neural networks (NNs), s...
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Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
Deep neural networks (DNNs) are notorious for their vulnerability to adv...
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Discretized Bottleneck in VAE: PosteriorCollapseFree SequencetoSequence Learning
Variational autoencoders (VAEs) are important tools in endtoend repres...
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StraightThrough Estimator as Projected Wasserstein Gradient Flow
The StraightThrough (ST) estimator is a widely used technique for back...
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POINTER: Constrained Text Generation via Insertionbased Generative Pretraining
Largescale pretrained language models, such as BERT and GPT2, have ac...
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Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images
We consider preoperative prediction of thyroid cancer based on ultrahig...
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Explaining Landscape Connectivity of Lowcost Solutions for Multilayer Nets
Mode connectivity is a surprising phenomenon in the loss landscape of de...
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TIPRDC: TaskIndependent PrivacyRespecting Data Crowdsourcing Framework with Anonymized Intermediate Representations
The success of deep learning partially benefits from the availability of...
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MVStylizer: An Efficient EdgeAssisted Video Photorealistic Style Transfer System for Mobile Phones
Recent research has made great progress in realizing neural style transf...
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AdvDetPatch: Attacking Object Detectors with Adversarial Patches
Object detectors have witnessed great progress in recent years and have ...
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Solving Jigsaw Puzzles By The Graph Connection Laplacian
We propose a novel mathematical framework to address the problem of auto...
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Scalable Thompson Sampling via Optimal Transport
Thompson sampling (TS) is a class of algorithms for sequential decision...
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Interpretable Image Recognition with Hierarchical Prototypes
Vision models are interpretable when they classify objects on the basis ...
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Range Adaptation for 3D Object Detection in LiDAR
LiDARbased 3D object detection plays a crucial role in modern autonomou...
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LMVP: Video Predictor with Leaked Motion Information
We propose a Leaked Motion Video Predictor (LMVP) to predict future fram...
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Fisher information regularization schemes for Wasserstein gradient flows
We propose a variational scheme for computing Wasserstein gradient flows...
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MimickNet, Matching Clinical PostProcessing Under Realistic BlackBox Constraints
Image postprocessing is used in clinicalgrade ultrasound scanners to i...
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Towards Learning a Generic Agent for VisionandLanguage Navigation via Pretraining
Learning to navigate in a visual environment following naturallanguage ...
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Statistically Model Checking PCTL Specifications on Markov Decision Processes via Reinforcement Learning
Probabilistic Computation Tree Logic (PCTL) is frequently used to formal...
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Dominating Manipulations in Voting with Partial Information
We consider manipulation problems when the manipulator only has partial ...
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Incentive Compatible Budget Elicitation in Multiunit Auctions
In this paper, we consider the problem of designing incentive compatible...
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