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Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
Potential crowd flow prediction for new planned transportation sites is ...
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Guidance Module Network for Video Captioning
Video captioning has been a challenging and significant task that descri...
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Self-Supervised Visual Representation Learning from Hierarchical Grouping
We create a framework for bootstrapping visual representation learning f...
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Semi-supervised Autoencoding Projective Dependency Parsing
We describe two end-to-end autoencoding models for semi-supervised graph...
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Cross-Lingual Document Retrieval with Smooth Learning
Cross-lingual document search is an information retrieval task in which ...
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Measuring Information Transfer in Neural Networks
Estimation of the information content in a neural network model can be p...
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Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient
Deep Q-learning algorithms often suffer from poor gradient estimations w...
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Solving the Bethe-Salpeter 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
Over-parameterized deep neural networks (DNNs) with sufficient capacity ...
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Weighted directed networks with a differentially private bi-degree 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 K-Means
In this paper, we study the statistical properties of the kernel k-means...
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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 Worst-Case Mutual Information Maximization
Training machine learning models to be robust against adversarial inputs...
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Label-guided 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 EEG-Based Brain-Computer Interface Speller Output Anything
An electroencephalogram (EEG) based brain-computer interface (BCI) spell...
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Tensor Graph Convolutional Networks for Text Classification
Compared to sequential learning models, graph-based 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 EEG-Based BCIs
Multiple convolutional neural network (CNN) classifiers have been propos...
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An Anomaly Contribution Explainer for Cyber-Security Applications
In this paper, we introduce Anomaly Contribution Explainer or ACE, a too...
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Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer 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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Low-cost LIDAR based Vehicle Pose Estimation and Tracking
Detecting surrounding vehicles by low-cost LIDAR has been drawing enormo...
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Learning Conceptual-Contexual Embeddings for Medical Text
External knowledge is often useful for natural language understanding ta...
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The iMaterialist Fashion Attribute Dataset
Large-scale 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 sub-task...
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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 feed-forward...
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P2SGrad: Refined Gradients for Optimizing Deep Face Models
Cosine-based softmax losses significantly improve the performance of dee...
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AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
The cosine-based 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 EEG-Based 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: Single-Shot Image Parser
We present a single-shot, bottom-up 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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Cost-Sensitive Robustness against Adversarial Examples
Several recent works have developed methods for training classifiers tha...
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Learning One-hidden-layer ReLU Networks via Gradient Descent
We study the problem of learning one-hidden-layer neural networks with R...
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Economics of UAV-aided 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: Platform-Aware 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 Multi-Phase Procrustes Flow
We revisit the inductive matrix completion problem that aims to recover ...
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Medical Exam Question Answering with Large-scale 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 Spatially-aware Fashion Concept Discovery
This paper proposes an automatic spatially-aware 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 Low-Rank plus Sparse Matrix Recovery
We study the problem of low-rank plus sparse matrix recovery. We propose...
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