
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
We present GradientDICE for estimating the density ratio between the sta...
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Provably Convergent OffPolicy ActorCritic with Function Approximation
We present the first provably convergent offpolicy actorcritic algorit...
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Robust Conditional GAN from UncertaintyAware Pairwise Comparisons
Conditional generative adversarial networks have shown exceptional gener...
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ObjectGuided Instance Segmentation for Biological Images
Instance segmentation of biological images is essential for studying obj...
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Dual Sequential Monte Carlo: Tunneling Filtering and Planning in Continuous POMDPs
We present the DualSMC network that solves continuous POMDPs by learning...
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PerStep Reward: A New Perspective for RiskAverse Reinforcement Learning
We present a new perstep reward perspective for riskaverse control in ...
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Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
Due to a variety of motions across different frames, it is highly challe...
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Stable and Efficient Policy Evaluation
Policy evaluation algorithms are essential to reinforcement learning due...
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A LightWeighted Convolutional Neural Network for Bitemporal SAR Image Change Detection
Recently, many Convolution Neural Networks (CNN) have been successfully ...
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A Convolutional Neural Network with Parallel MultiScale Spatial Pooling to Detect Temporal Changes in SAR Images
In synthetic aperture radar (SAR) image change detection, it is quite ch...
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PACMAN: A PlannerActorCritic Architecture for HumanCentered Planning and Learning
Conventional reinforcement learning (RL) allows an agent to learn polici...
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Dual Temporal Memory Network for Efficient Video Object Segmentation
Video Object Segmentation (VOS) is typically formulated in a semisuperv...
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Deep Object Cosegmentation via SpatialSemantic Network Modulation
Object cosegmentation is to segment the shared objects in multiple rele...
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DCAR: A Discriminative and Compact Audio Representation to Improve Event Detection
This paper presents a novel twophase method for audio representation, D...
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O^2TD: (Near)Optimal OffPolicy TD Learning
Temporal difference learning and Residual Gradient methods are the most ...
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Dual Iterative Hard Thresholding: From Nonconvex Sparse Minimization to Nonsmooth Concave Maximization
Iterative Hard Thresholding (IHT) is a class of projected gradient desce...
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Regressionbased Hypergraph Learning for Image Clustering and Classification
Inspired by the recently remarkable successes of Sparse Representation (...
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Sparse Qlearning with Mirror Descent
This paper explores a new framework for reinforcement learning based on ...
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Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data
MicroRNAs (miRNAs) are small RNA molecules composed of 1922 nt, which p...
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Feature Space Transfer for Data Augmentation
The problem of data augmentation in feature space is considered. A new a...
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PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust DecisionMaking
Reinforcement learning and symbolic planning have both been used to buil...
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Privacy Preservation in LocationBased Services: A Novel Metric and Attack Model
Recent years have seen rising needs for locationbased services in our e...
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Constrainedsize Tensorflow Models for YouTube8M Video Understanding Challenge
This paper presents our 10th place solution to the second YouTube8M vid...
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A Block Coordinate Ascent Algorithm for MeanVariance Optimization
Risk management in dynamic decision problems is a primary concern in man...
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SDRL: Interpretable and Dataefficient Deep Reinforcement LearningLeveraging Symbolic Planning
Deep reinforcement learning (DRL) has gained great success by learning d...
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QUOTA: The Quantile Option Architecture for Reinforcement Learning
In this paper, we propose the Quantile Option Architecture (QUOTA) for e...
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SDRL: Interpretable and Dataefficient Deep Reinforcement Learning Leveraging Symbolic Planning
Deep reinforcement learning (DRL) has gained great success by learning d...
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Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application to Reinforcement Learning
Dantzig Selector (DS) is widely used in compressed sensing and sparse le...
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A Containerbased DoS AttackResilient Control Framework for RealTime UAV Systems
The Unmanned aerial vehicles (UAVs) sector is fastexpanding. Protection...
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Evolving the pulmonary nodules diagnosis from classical approaches to deep learning aided decision support: three decades development course and future prospect
Lung cancer is the commonest cause of cancer deaths worldwide, and its m...
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Viconmavlink: A software tool for indoor positioning using a motion capture system
Motion capture is a widelyused technology in robotics research thanks t...
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Robust Matrix Completion State Estimation in Distribution Systems
Due to the insufficient measurements in the distribution system state es...
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Predicting pregnancy using largescale data from a women's health tracking mobile application
Predicting pregnancy has been a fundamental problem in women's health fo...
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Machine Learning Aided Anonymization of Spatiotemporal Trajectory Datasets
The big data era requires a growing number of companies to publish their...
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Optimal Control of Complex Systems through Variational Inference with a Discrete Event Decision Process
Complex social systems are composed of interconnected individuals whose ...
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Anonymized BERT: An Augmentation Approach to the Gendered Pronoun Resolution Challenge
We present our 7th place solution to the Gendered Pronoun Resolution cha...
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Towards PhotoRealistic Visible Watermark Removal with Conditional Generative Adversarial Networks
Visible watermark plays an important role in image copyright protection ...
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Multiscale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes
Most existing methods handle cell instance segmentation problems directl...
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Nonuniqueness phenomenon of object representation in modelling IT cortex by deep convolutional neural network (DCNN)
Recently DCNN (Deep Convolutional Neural Network) has been advocated as ...
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Transfer LearningBased Label Proportions Method with Data of Uncertainty
Learning with label proportions (LLP), which is a learning task that onl...
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Optimal Function Approximation with Relu Neural Networks
We consider in this paper the optimal approximations of convex univariat...
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Heterogeneous Deep Graph Infomax
Graph representation learning is to learn universal node representations...
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A HumanCentered DataDriven PlannerActorCritic Architecture via Logic Programming
Recent successes of Reinforcement Learning (RL) allow an agent to learn ...
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FeCaffe: FPGAenabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10
Deep learning and Convolutional Neural Network (CNN) have becoming incre...
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Understanding Global Loss Landscape of Onehiddenlayer ReLU Neural Networks
For onehiddenlayer ReLU networks, we show that all local minima are gl...
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ShannonLimit Approached Information Reconciliation for Quantum Key Distribution
Information reconciliation (IR) corrects the errors in sifted keys and e...
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Geometry and Topology of Deep Neural Networks' Decision Boundaries
Geometry and topology of decision regions are closely related with class...
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Adaptive Graph Convolutional Network with Attention Graph Clustering for Cosaliency Detection
Cosaliency detection aims to discover the common and salient foreground...
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Exploit Clues from Views: SelfSupervised and Regularized Learning for Multiview Object Recognition
Multiview recognition has been well studied in the literature and achiev...
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APPLD: Adaptive Planner Parameter Learning from Demonstration
Existing autonomous robot navigation systems allow robots to move from o...
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