
Robust subsamplingbased sparse Bayesian inference to tackle four challenges (large noise, outliers, data integration, and extrapolation) in the discovery of physical laws from
The derivation of physical laws is a dominant topic in scientific resear...
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Unrestricted Adversarial Attacks for Semantic Segmentation
Semantic segmentation is one of the most impactful applications of machi...
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PENet: Object Detection using Points Estimation in Aerial Images
Aerial imagery has been increasingly adopted in missioncritical tasks, ...
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Horseshoe Regularization for Machine Learning in Complex and Deep Models
Since the advent of the horseshoe priors for regularization, globalloca...
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Zooming SlowMo: Fast and Accurate OneStage SpaceTime Video SuperResolution
In this paper, we explore the spacetime video superresolution task, wh...
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TREND: Transferability based Robust ENsemble Design
Deep Learning models hold stateoftheart performance in many fields, b...
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Multilevel hypothesis testing for populations of heterogeneous networks
In this work, we consider hypothesis testing and anomaly detection on da...
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Fast Deep Learning for Automatic Modulation Classification
In this work, we investigate the feasibility and effectiveness of employ...
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City2City: Translating Place Representations across Cities
Large mobility datasets collected from various sources have allowed us t...
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A TwoStage Approach to FewShot Learning for Image Recognition
This paper proposes a multilayer neural network structure for fewshot ...
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Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications
In this work, we propose a Bayesian type sparse deep learning algorithm....
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A Comparative Evaluation of SGM Variants (including a New Variant, tMGM) for Dense Stereo Matching
Our goal here is threefold: [1] To present a new densestereo matching a...
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LowPower Computer Vision: Status, Challenges, Opportunities
Computer vision has achieved impressive progress in recent years. Meanwh...
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AdaWISH: Faster Discrete Integration via Adaptive Quantiles
Discrete integration in a high dimensional space of n variables poses fu...
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Safetyguaranteed Reinforcement Learning based on Multiclass Support Vector Machine
Several works have addressed the problem of incorporating constraints in...
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A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks
In this era of machine learning models, their functionality is being thr...
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PeriNetPro: The neural processes with quantified uncertainty for crack patterns
This paper uses the peridynamic theory, which is wellsuited to crack st...
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Deepfakes Detection with Automatic Face Weighting
Altered and manipulated multimedia is increasingly present and widely di...
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TiMDNN: Ternary inMemory accelerator for Deep Neural Networks
The use of lower precision has emerged as a popular technique to optimiz...
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Classspecific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images
Detecting objects in a twodimensional setting is often insufficient in ...
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Structured Compression and Sharing of Representational Space for Continual Learning
Humans are skilled at learning adaptively and efficiently throughout the...
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Multilevel Training and Bayesian Optimization for Economical Hyperparameter Optimization
Hyperparameters play a critical role in the performances of many machine...
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Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge
The recent advent of `Internet of Things' (IOT) has increased the demand...
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Deep Learning Guided Building Reconstruction from Satellite Imageryderived Point Clouds
3D urban reconstruction of buildings from remotely sensed imagery has dr...
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Deep Transfer Learning For Plant Center Localization
Plant phenotyping focuses on the measurement of plant characteristics th...
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Megapixel PhotonCounting Color Imaging using Quanta Image Sensor
Quanta Image Sensor (QIS) is a singlephoton detector designed for extre...
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Robust datadriven discovery of governing physical laws using a new subsamplingbased sparse Bayesian method to tackle four challenges (large noise, outliers, data integration,
The derivation of physical laws is a dominant topic in scientific resear...
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Relevantfeatures based Auxiliary Cells for Energy Efficient Detection of Natural Errors
Deep neural networks have demonstrated stateoftheart performance on m...
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Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Spiking Neural Networks (SNNs) operate with asynchronous discrete events...
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Ensemble Wrapper Subsampling for Deep Modulation Classification
Subsampling of received wireless signals is important for relaxing hardw...
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Interactive Learning for Identifying Relevant Tweets to Support Realtime Situational Awareness
Various domain users are increasingly leveraging realtime social media ...
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Geometric AllWay Boolean Tensor Decomposition
Boolean tensor has been broadly utilized in representing high dimensiona...
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Automatic Foreground Extraction using MultiAgent Consensus Equilibrium
While foreground extraction is fundamental to virtual reality systems an...
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MEBF: a fast and efficient Boolean matrix factorization method
Boolean matrix has been used to represent digital information in many fi...
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A Sparse Deep Factorization Machine for Efficient CTR prediction
Clickthrough rate (CTR) prediction is a crucial task in online display ...
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Object classification from randomized EEG trials
New results suggest strong limits to the feasibility of classifying huma...
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Lowrank Tensor Bandits
In recent years, multidimensional online decision making has been playi...
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A New Stereo Benchmarking Dataset for Satellite Images
In order to facilitate further research in stereo reconstruction with mu...
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Flexible Mixture Modeling on Constrained Spaces
This paper addresses challenges in flexibly modeling multimodal data tha...
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Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals
Insects and hummingbirds exhibit extraordinary flight capabilities and c...
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Efficient Gaussian Process Bandits by Believing only Informative Actions
Bayesian optimization is a framework for global search via maximum a pos...
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A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs
Tensor computations present significant performance challenges that impa...
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Towards Understanding the Effect of Leak in Spiking Neural Networks
Spiking Neural Networks (SNNs) are being explored to emulate the astound...
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3D Object Classification via Spherical Projections
In this paper, we introduce a new method for classifying 3D objects. Our...
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Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing
Deep convolutional neural network (DCNN) based supervised learning is a ...
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On Deterministic Sampling Patterns for Robust LowRank Matrix Completion
In this letter, we study the deterministic sampling patterns for the com...
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Deep Neural Network Architectures for Modulation Classification
In this work, we investigate the value of employing deep learning for th...
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Accelerating Convolutional Neural Networks for Continuous Mobile Vision via Cache Reuse
Convolutional Neural Network (CNN) is the stateoftheart algorithm of ...
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From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets
We propose a Las Vegas transformation of Markov Chain Monte Carlo (MCMC)...
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TraNNsformer: Neural Network Transformation for Memristive Crossbar based Neuromorphic System Design
Implementation of Neuromorphic Systems using post Complementary MetalOx...
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