
Focus Longer to See Better:Recursively Refined Attention for FineGrained Image Classification
Deep Neural Network has shown great strides in the coarsegrained image ...
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PyODDS: An EndtoEnd Outlier Detection System
PyODDS is an endto end Python system for outlier detection with databas...
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XGNN: Towards ModelLevel Explanations of Graph Neural Networks
Graphs neural networks (GNNs) learn node features by aggregating and com...
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NonLocal Graph Neural Networks
Modern graph neural networks (GNNs) learn node embeddings through multil...
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ScoreCAM:Improved Visual Explanations Via ScoreWeighted Class Activation Mapping
Recently, more and more attention has been drawn into the internal mecha...
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Accelerating PDEconstrained Inverse Solutions with Deep Learning and Reduced Order Models
Inverse problems are pervasive mathematical methods in inferring knowled...
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Networkprincipled deep generative models for designing drug combinations as graph sets
Combination therapy has shown to improve therapeutic efficacy while redu...
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AutoGAN: Neural Architecture Search for Generative Adversarial Networks
Neural architecture search (NAS) has witnessed prevailing success in ima...
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On the Search for Feedback in Reinforcement Learning
This paper addresses the problem of learning the optimal feedback policy...
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Learning an Interpretable Traffic Signal Control Policy
Signalized intersections are managed by controllers that assign right of...
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Deep Structured CrossModal Anomaly Detection
Anomaly detection is a fundamental problem in data mining field with man...
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I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
The learning of hierarchical representations for image classification ha...
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DeblurGANv2: Deblurring (OrdersofMagnitude) Faster and Better
We present a new endtoend generative adversarial network (GAN) for sin...
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Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds
In recent years, unfolding iterative algorithms as neural networks has b...
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Acceleration of Radiation Transport Solves Using Artificial Neural Networks
Discontinuous Finite Element Methods (DFEM) have been widely used for so...
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A Hybrid Deep Learning Model for Predictive Flood Warning and Situation Awareness using Channel Network Sensors Data
The objective of this study is to create and test a hybrid deep learning...
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DAVID: DualAttentional Video Deblurring
Blind video deblurring restores sharp frames from a blurry sequence with...
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Network Shrinkage Estimation
Networks are a natural representation of complex systems across the scie...
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RLCard: A Toolkit for Reinforcement Learning in Card Games
RLCard is an opensource toolkit for reinforcement learning research in ...
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Predicting Depression Severity by MultiModal Feature Engineering and Fusion
We present our preliminary work to determine if patient's vocal acoustic...
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EndtoEnd United Video Dehazing and Detection
The recent development of CNNbased image dehazing has revealed the effe...
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Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach
Emotion recognition from facial expressions is tremendously useful, espe...
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Towards PrivacyPreserving Visual Recognition via Adversarial Training: A Pilot Study
This paper aims to improve privacypreserving visual recognition, an inc...
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PrivacyPreserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset
This paper aims to boost privacypreserving visual recognition, an incre...
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AutoSpeech: Neural Architecture Search for Speaker Recognition
Speaker recognition systems based on Convolutional Neural Networks (CNNs...
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Incentivizing Sharing in Realtime D2D Streaming Networks: A Mean Field Game Perspective
We consider the problem of streaming live content to a cluster of coloc...
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Tensor Completion Algorithms in Big Data Analytics
Tensor completion is a problem of filling the missing or unobserved entr...
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Throughput Optimal Decentralized Scheduling of MultiHop Networks with EndtoEnd Deadline Constraints: II Wireless Networks with Interference
Consider a multihop wireless network serving multiple flows in which wir...
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Spatial Variational AutoEncoding via MatrixVariate Normal Distributions
The key idea of variational autoencoders (VAEs) resembles that of tradi...
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Approximating Continuous Functions by ReLU Nets of Minimal Width
This article concerns the expressive power of depth in deep feedforward...
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αVariational Inference with Statistical Guarantees
We propose a variational approximation to Bayesian posterior distributio...
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Visual Servoing of Unmanned Surface Vehicle from Small Tethered Unmanned Aerial Vehicle
This paper presents an algorithm and the implementation of a motor schem...
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Evolutionary Approaches to Optimization Problems in Chimera Topologies
Chimera graphs define the topology of one of the first commercially avai...
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Frequentist coverage and supnorm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique d...
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Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
This article concerns the expressive power of depth in neural nets with ...
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Attributed Network Embedding for Learning in a Dynamic Environment
Network embedding leverages the node proximity manifested to learn a low...
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Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs
This paper is concerned with the problem of stochastic control of gene r...
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Surrogate Aided Unsupervised Recovery of Sparse Signals in Single Index Models for Binary Outcomes
We consider the recovery of regression coefficients, denoted by β_0, for...
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Detection of Cooperative Interactions in Logistic Regression Models
An important problem in the field of bioinformatics is to identify inter...
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Data Integration with High Dimensionality
We consider a problem of data integration. Consider determining which ge...
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Functorial Hierarchical Clustering with Overlaps
This work draws its inspiration from three important sources of research...
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Consistency constraints for overlapping data clustering
We examine overlapping clustering schemes with functorial constraints, i...
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Enhance Visual Recognition under Adverse Conditions via Deep Networks
Visual recognition under adverse conditions is a very important and chal...
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On Statistical Optimality of Variational Bayes
The article addresses a longstanding open problem on the justification ...
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Oracle Inequalities for Highdimensional Prediction
The abundance of highdimensional data in the modern sciences has genera...
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Qlearning for Optimal Control of Continuoustime Systems
In this paper, two Qlearning (QL) methods are proposed and their conver...
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Convex optimization on Banach Spaces
Greedy algorithms which use only function evaluations are applied to con...
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Offpolicy reinforcement learning for H_∞ control design
The H_∞ control design problem is considered for nonlinear systems with ...
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Moments and RootMeanSquare Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model
The most important aspect of any classifier is its error rate, because t...
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Online Adaptive Decision Fusion Framework Based on Entropic Projections onto Convex Sets with Application to Wildfire Detection in Video
In this paper, an Entropy functional based online Adaptive Decision Fusi...
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Texas A&M University
Texas A&M University is a coeducational public research university in College Station, Texas, United States.