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04/08/2021
Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT
Many real-world IoT systems comprising various internet-connected sensor...
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03/24/2021
Improved Estimation of Concentration Under ℓ_p-Norm Distance Metrics Using Half Spaces
Concentration of measure has been argued to be the fundamental cause of ...
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03/19/2021
Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond
Deep neural networks have been well-known for their superb performance i...
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01/24/2021
Multi-Task Time Series Forecasting With Shared Attention
Time series forecasting is a key component in many industrial and busine...
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01/18/2021
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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12/20/2020
Guidance Module Network for Video Captioning
Video captioning has been a challenging and significant task that descri...
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12/05/2020
Self-Supervised Visual Representation Learning from Hierarchical Grouping
We create a framework for bootstrapping visual representation learning f...
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11/02/2020
Semi-supervised Autoencoding Projective Dependency Parsing
We describe two end-to-end autoencoding models for semi-supervised graph...
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11/02/2020
Cross-Lingual Document Retrieval with Smooth Learning
Cross-lingual document search is an information retrieval task in which ...
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09/16/2020
Measuring Information Transfer in Neural Networks
Estimation of the information content in a neural network model can be p...
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07/25/2020
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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06/15/2020
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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04/29/2020
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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03/21/2020
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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03/15/2020
CoinMagic: A Differential Privacy Framework for Ring Signature Schemes
By allowing users to obscure their transactions via including "mixins" (...
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03/09/2020
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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03/01/2020
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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02/26/2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Training machine learning models to be robust against adversarial inputs...
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02/25/2020
Label-guided Learning for Text Classification
Text classification is one of the most important and fundamental tasks i...
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01/30/2020
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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01/12/2020
Tensor Graph Convolutional Networks for Text Classification
Compared to sequential learning models, graph-based neural networks exhi...
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01/04/2020
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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12/25/2019
Learn to Segment Retinal Lesions and Beyond
Towards automated retinal screening, this paper makes an endeavor to sim...
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12/03/2019
Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs
Multiple convolutional neural network (CNN) classifiers have been propos...
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12/01/2019
An Anomaly Contribution Explainer for Cyber-Security Applications
In this paper, we introduce Anomaly Contribution Explainer or ACE, a too...
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11/07/2019
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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10/23/2019
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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10/15/2019
SegSort: Segmentation by Discriminative Sorting of Segments
Almost all existing deep learning approaches for semantic segmentation t...
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10/03/2019
Low-cost LIDAR based Vehicle Pose Estimation and Tracking
Detecting surrounding vehicles by low-cost LIDAR has been drawing enormo...
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08/16/2019
Learning Conceptual-Contexual Embeddings for Medical Text
External knowledge is often useful for natural language understanding ta...
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06/13/2019
The iMaterialist Fashion Attribute Dataset
Large-scale image databases such as ImageNet have significantly advanced...
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06/03/2019
Sentiment Tagging with Partial Labels using Modular Architectures
Many NLP learning tasks can be decomposed into several distinct sub-task...
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05/29/2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Many recent works have shown that adversarial examples that fool classif...
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05/16/2019
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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05/07/2019
P2SGrad: Refined Gradients for Optimizing Deep Face Models
Cosine-based softmax losses significantly improve the performance of dee...
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05/01/2019
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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04/07/2019
Normalized Diversification
Generating diverse yet specific data is the goal of the generative adver...
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03/31/2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs
Deep learning has been successfully used in numerous applications becaus...
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03/27/2019
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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02/13/2019
DeeperLab: Single-Shot Image Parser
We present a single-shot, bottom-up approach for whole image parsing. Wh...
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12/11/2018
Delta Embedding Learning
Learning from corpus and learning from supervised NLP tasks both give us...
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10/22/2018
Cost-Sensitive Robustness against Adversarial Examples
Several recent works have developed methods for training classifiers tha...
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06/20/2018
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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05/22/2018
Economics of UAV-aided Mobile Services Deployment
An Unmanned Aerial Vehicle (UAV) network has emerged as a promising tech...
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04/30/2018
OMG - Emotion Challenge Solution
This short paper describes our solution to the 2018 IEEE World Congress ...
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04/09/2018
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications
This work proposes an automated algorithm, called NetAdapt, that adapts ...
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03/24/2018
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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03/03/2018
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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02/28/2018
Medical Exam Question Answering with Large-scale Reading Comprehension
Reading and understanding text is one important component in computer ai...
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10/16/2017
