
Solving the BetheSalpeter equation on massively parallel architectures
The last ten years have witnessed fast spreading of massively parallel c...
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Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs
Overparameterized deep neural networks (DNNs) with sufficient capacity ...
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Weighted directed networks with a differentially private bidegree sequence
The p_0 model is an exponential random graph model for directed networks...
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CoinMagic: A Differential Privacy Framework for Ring Signature Schemes
By allowing users to obscure their transactions via including "mixins" (...
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Nearly Optimal Risk Bounds for Kernel KMeans
In this paper, we study the statistical properties of the kernel kmeans...
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Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models
Starting with Gilmer et al. (2018), several works have demonstrated the ...
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Learning Adversarially Robust Representations via WorstCase Mutual Information Maximization
Training machine learning models to be robust against adversarial inputs...
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Labelguided Learning for Text Classification
Text classification is one of the most important and fundamental tasks i...
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Tiny Noise Can Make an EEGBased BrainComputer Interface Speller Output Anything
An electroencephalogram (EEG) based braincomputer interface (BCI) spell...
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Tensor Graph Convolutional Networks for Text Classification
Compared to sequential learning models, graphbased neural networks exhi...
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Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
A deep neural network (DNN) with piecewise linear activations can partit...
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Learn to Segment Retinal Lesions and Beyond
Towards automated retinal screening, this paper makes an endeavor to sim...
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Universal Adversarial Perturbations for CNN Classifiers in EEGBased BCIs
Multiple convolutional neural network (CNN) classifiers have been propos...
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An Anomaly Contribution Explainer for CyberSecurity Applications
In this paper, we introduce Anomaly Contribution Explainer or ACE, a too...
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Active Learning for BlackBox Adversarial Attacks in EEGBased BrainComputer Interfaces
Deep learning has made significant breakthroughs in many fields, includi...
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An Adaptive Empirical Bayesian Method for Sparse Deep Learning
We propose a novel adaptive empirical Bayesian (AEB) method for sparse d...
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SegSort: Segmentation by Discriminative Sorting of Segments
Almost all existing deep learning approaches for semantic segmentation t...
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Lowcost LIDAR based Vehicle Pose Estimation and Tracking
Detecting surrounding vehicles by lowcost LIDAR has been drawing enormo...
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Learning ConceptualContexual Embeddings for Medical Text
External knowledge is often useful for natural language understanding ta...
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The iMaterialist Fashion Attribute Dataset
Largescale image databases such as ImageNet have significantly advanced...
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Sentiment Tagging with Partial Labels using Modular Architectures
Many NLP learning tasks can be decomposed into several distinct subtask...
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Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Many recent works have shown that adversarial examples that fool classif...
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Joint Learning of Neural Networks via Iterative Reweighted Least Squares
In this paper, we introduce the problem of jointly learning feedforward...
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P2SGrad: Refined Gradients for Optimizing Deep Face Models
Cosinebased softmax losses significantly improve the performance of dee...
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AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
The cosinebased softmax losses and their variants achieve great success...
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Normalized Diversification
Generating diverse yet specific data is the goal of the generative adver...
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On the Vulnerability of CNN Classifiers in EEGBased BCIs
Deep learning has been successfully used in numerous applications becaus...
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Optimal deployment of sustainable UAV networks for providing wireless coverage
Each UAV is constrained in its energy storage and wireless coverage, and...
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DeeperLab: SingleShot Image Parser
We present a singleshot, bottomup approach for whole image parsing. Wh...
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Delta Embedding Learning
Learning from corpus and learning from supervised NLP tasks both give us...
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CostSensitive Robustness against Adversarial Examples
Several recent works have developed methods for training classifiers tha...
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Learning Onehiddenlayer ReLU Networks via Gradient Descent
We study the problem of learning onehiddenlayer neural networks with R...
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Economics of UAVaided Mobile Services Deployment
An Unmanned Aerial Vehicle (UAV) network has emerged as a promising tech...
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OMG  Emotion Challenge Solution
This short paper describes our solution to the 2018 IEEE World Congress ...
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NetAdapt: PlatformAware Neural Network Adaptation for Mobile Applications
This work proposes an automated algorithm, called NetAdapt, that adapts ...
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Learning architectures based on quantum entanglement: a simple matrix product state algorithm for image recognition
It is a fundamental, but still elusive question whether methods based on...
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Fast and Sample Efficient Inductive Matrix Completion via MultiPhase Procrustes Flow
We revisit the inductive matrix completion problem that aims to recover ...
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Medical Exam Question Answering with Largescale Reading Comprehension
Reading and understanding text is one important component in computer ai...
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Optimal Deployment of UAV Networks for Delivering Emergency Wireless Coverage
Unmanned Aerial Vehicle (UAV) networks have emerged as a promising techn...
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Automatic Spatiallyaware Fashion Concept Discovery
This paper proposes an automatic spatiallyaware concept discovery appro...
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Learning Unified Embedding for Apparel Recognition
In apparel recognition, specialized models (e.g. models trained for a pa...
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Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption
We consider the phase retrieval problem of recovering the unknown signal...
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A Nonconvex Free Lunch for LowRank plus Sparse Matrix Recovery
We study the problem of lowrank plus sparse matrix recovery. We propose...
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A Universal Variance ReductionBased Catalyst for Nonconvex LowRank Matrix Recovery
We propose a generic framework based on a new stochastic variancereduce...
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Stochastic Variancereduced Gradient Descent for Lowrank Matrix Recovery from Linear Measurements
We study the problem of estimating lowrank matrices from linear measure...
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Range Loss for Deep Face Recognition with Longtail
Convolutional neural networks have achieved great improvement on face re...
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Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition
A deep learning approach has been widely applied in sequence modeling pr...
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Composing Music with Grammar Argumented Neural Networks and NoteLevel Encoding
Creating aesthetically pleasing pieces of art, including music, has been...
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A Unified Computational and Statistical Framework for Nonconvex LowRank Matrix Estimation
We propose a unified framework for estimating lowrank matrices through ...
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Xiao Zhang
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