
On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration
Imitation learning from observation (LfO) is more preferable than imitat...
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LoRRaL: Facial Action Unit Detection Based on Local Region Relation Learning
Endtoend convolution representation learning has been proved to be ver...
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Weakshot Finegrained Classification via Similarity Transfer
Recognizing finegrained categories remains a challenging task, due to t...
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Solving the Blind PerspectivenPoint Problem EndToEnd With Robust Differentiable Geometric Optimization
Blind PerspectivenPoint (PnP) is the problem of estimating the positio...
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Robust Structured Statistical Estimation via Conditional Gradient Type Methods
Structured statistical estimation problems are often solved by Condition...
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Robust compressed sensing of generative models
The goal of compressed sensing is to estimate a high dimensional vector ...
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Channel Attention based Iterative Residual Learning for Depth Map SuperResolution
Despite the remarkable progresses made in deeplearning based depth map ...
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Computation on Sparse Neural Networks: an Inspiration for Future Hardware
Neural network models are widely used in solving many challenging proble...
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Learning 2D3D Correspondences To Solve The Blind PerspectivenPoint Problem
Conventional absolute camera pose via a PerspectivenPoint (PnP) solver...
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Hodge and Podge: Hybrid Supervised Sound Event Detection with MultiHot MixMatch and Composition Consistence Training
In this paper, we propose a method called Hodge and Podge for sound even...
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Deep Image Harmonization via Domain Verification
Image composition is an important operation in image processing, but the...
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Error estimate of a bifidelity method for kinetic equations with random parameters and multiple scales
In this paper, we conduct uniform error estimates of the bifidelity met...
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Encoding Selection for Solving Hamiltonian Cycle Problems with ASP
It is common for search and optimization problems to have alternative eq...
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Quantum algorithm for finding the negative curvature direction in nonconvex optimization
We present an efficient quantum algorithm aiming to find the negative cu...
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NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network
Denoising extreme low light images is a challenging task due to the high...
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Image Harmonization Datasets: HCOCO, HAdobe5k, HFlickr, and Hday2night
Image composition is an important operation in image processing, but the...
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HODGEPODGE: Sound event detection based on ensemble of semisupervised learning methods
In this paper, we present a method called HODGEPODGE[1] for largescale ...
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Optimal Feature Transport for CrossView Image GeoLocalization
This paper addresses the problem of crossview image based localization,...
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Lending Orientation to Neural Networks for Crossview Geolocalization
This paper studies imagebased geolocalization (IBL) problem using grou...
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FurcaNeXt: Endtoend monaural speech separation with dynamic gated dilated temporal convolutional networks
Deep dilated temporal convolutional networks (TCN) have been proved to b...
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FurcaNet: An endtoend deep gated convolutional, long shortterm memory, deep neural networks for single channel speech separation
Deep gated convolutional networks have been proved to be very effective ...
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Is CQT more suitable for monaural speech separation than STFT? an empirical study
Shorttime Fourier transform (STFT) is used as the front end of many pop...
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High Dimensional Robust Estimation of Sparse Models via Trimmed Hard Thresholding
We study the problem of sparsity constrained Mestimation with arbitrary...
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Dynamic Sparse Graph for Efficient Deep Learning
We propose to execute deep neural networks (DNNs) with dynamic and spars...
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Stochastic Secondorder Methods for Nonconvex Optimization with Inexact Hessian and Gradient
Trust region and cubic regularization methods have demonstrated good per...
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Stochastically Controlled Stochastic Gradient for the Convex and Nonconvex Composition problem
In this paper, we consider the convex and nonconvex composition problem...
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Deep Stochastic Attraction and Repulsion Embedding for Image Based Localization
This paper tackles the problem of largescale imagebased localization w...
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Stochastic Zerothorder Optimization via Variance Reduction method
Derivativefree optimization has become an important technique used in m...
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High Dimensional Robust Sparse Regression
We provide a novel  and to the best of our knowledge, the first  alg...
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Approximate Newtonbased statistical inference using only stochastic gradients
We present a novel inference framework for convex empirical risk minimiz...
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Discriminative CrossView Binary Representation Learning
Learning compact representation is vital and challenging for large scale...
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L1Norm Batch Normalization for Efficient Training of Deep Neural Networks
Batch Normalization (BN) has been proven to be quite effective at accele...
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PIRT: A Runtime Framework to Enable EnergyEfficient RealTime Robotic Applications on Heterogeneous Architectures
Enabling full robotic workloads with diverse behaviors on mobile systems...
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Asymptotic Analysis for LowResolution Massive MIMO Systems with MMSE Receiver
The uplink achievable rate of massive multiple inputmultipleoutput (M...
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A Double Joint Bayesian Approach for JVector Based Textdependent Speaker Verification
Jvector has been proved to be very effective in textdependent speaker ...
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Variance Reduced methods for Nonconvex Composition Optimization
This paper explores the nonconvex composition optimization in the form ...
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Dualityfree Methods for Stochastic Composition Optimization
We consider the composition optimization with two expectedvalue functio...
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Person Reidentification Using Visual Attention
Despite recent attempts for solving the person reidentification problem...
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Addressing Ambiguity in Multitarget Tracking by Hierarchical Strategy
This paper presents a novel hierarchical approach for the simultaneous t...
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MultiView TaskDriven Recognition in Visual Sensor Networks
Nowadays, distributed smart cameras are deployed for a wide set of tasks...
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Statistical inference using SGD
We present a novel method for frequentist statistical inference in Mest...
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Endtoend Binary Representation Learning via Direct Binary Embedding
Learning binary representation is essential to largescale computer visi...
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Compressing Deep Convolutional Networks using Vector Quantization
Deep convolutional neural networks (CNN) has become the most promising m...
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Liu Liu
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Graduate Research Assistant at University of Tennessee, Knoxville and Sr. Machine Learning Engineer at Samsung Semiconductor, Inc