
Fisher AutoEncoders
It has been conjectured that the Fisher divergence is more robust to mod...
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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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Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments
We consider three important challenges in conference peer review: (i) re...
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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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Towards Understanding Fast Adversarial Training
Current neuralnetworkbased classifiers are susceptible to adversarial ...
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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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Indecision Modeling
AI systems are often used to make or contribute to important decisions i...
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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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LotteryFL: Personalized and CommunicationEfficient Federated Learning with Lottery Ticket Hypothesis on NonIID Datasets
Federated learning is a popular distributed machine learning paradigm wi...
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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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DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
Recent research finds CNN models for image classification demonstrate ov...
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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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Improved Design of Quadratic Discriminant Analysis Classifier in Unbalanced Settings
The use of quadratic discriminant analysis (QDA) or its regularized vers...
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Low to High Dimensional Modality Hallucination using Aggregated Fields of View
Realworld robotics systems deal with data from a multitude of modalitie...
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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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Cooperative MultiAgent Reinforcement Learning with Partial Observations
In this paper, we propose a distributed zerothorder policy optimization...
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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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Improving Disentangled Text Representation Learning with InformationTheoretic Guidance
Learning disentangled representations of natural language is essential f...
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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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