
Do Deep Minds Think Alike? Selective Adversarial Attacks for FineGrained Manipulation of Multiple Deep Neural Networks
Recent works have demonstrated the existence of adversarial examples ta...
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a simple and effective framework for pairwise deep metric learning
Deep metric learning (DML) has received much attention in deep learning ...
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Improving Efficiency in LargeScale Decentralized Distributed Training
Decentralized Parallel SGD (DPSGD) and its asynchronous variant Asynchr...
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Robust Image Segmentation Quality Assessment without Ground Truth
Deep learning based image segmentation methods have achieved great succe...
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NADSNet: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks
A new convolutional neural network (CNN) architecture for 2D driver/pass...
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Outlier Detection using Generative Models with Theoretical Performance Guarantees
This paper considers the problem of recovering signals from compressed m...
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Deep Generalization of Structured Low Rank Algorithms (DeepSLR)
Structured lowrank (SLR) algorithms are emerging as powerful image reco...
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How Local is the Local Diversity? Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization
The large volume of video content and high viewing frequency demand auto...
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Stochastic Optimization for DC Functions and Nonsmooth Nonconvex Regularizers with Nonasymptotic Convergence
Difference of convex (DC) functions cover a broad family of nonconvex a...
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FilterNet: A Neighborhood Relationship Enhanced Fully Convolutional Network for Calf Muscle Compartment Segmentation
Automated segmentation of individual calf muscle compartments from 3D ma...
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Improving Sequential Determinantal Point Processes for Supervised Video Summarization
It is now much easier than ever before to produce videos. While the ubiq...
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Fast Single Image Reflection Suppression via Convex Optimization
Removing undesired reflections from images taken through the glass is of...
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3D Surface Segmentation Meets Conditional Random Fields
Automated surface segmentation is important and challenging in many medi...
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CramérRao Lower Bounds Arising from Generalized Csiszár Divergences
We study the geometry of probability distributions with respect to a gen...
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NEON+: Accelerated Gradient Methods for Extracting Negative Curvature for NonConvex Optimization
Accelerated gradient (AG) methods are breakthroughs in convex optimizati...
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Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect
We introduce a novel generative model for interpretable subgroup analysi...
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MultiValue Rule Sets
We present the MultivAlue Rule Set (MARS) model for interpretable class...
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Stochastic Nonconvex Optimization with Strong High Probability Secondorder Convergence
In this paper, we study stochastic nonconvex optimization with nonconv...
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DSCOVR: Randomized PrimalDual Block Coordinate Algorithms for Asynchronous Distributed Optimization
Machine learning with big data often involves large optimization models....
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Deep Spectral Descriptors: Learning the pointwise correspondence metric via Siamese deep neural networks
A robust and informative local shape descriptor plays an important role ...
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A Simple Analysis for Expconcave Empirical Minimization with Arbitrary Convex Regularizer
In this paper, we present a simple analysis of fast rates with high pr...
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SEPNets: Small and Effective Pattern Networks
While going deeper has been witnessed to improve the performance of conv...
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Towards Adversarial Retinal Image Synthesis
Synthesizing images of the eye fundus is a challenging task that has bee...
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The biglasso Package: A Memory and ComputationEfficient Solver for Lasso Model Fitting with Big Data in R
Penalized regression models such as the lasso have been extensively appl...
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Bayesian Decision Process for CostEfficient Dynamic Ranking via Crowdsourcing
Rank aggregation based on pairwise comparisons over a set of items has a...
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Realistic riskmitigating recommendations via inverse classification
Inverse classification, the process of making meaningful perturbations t...
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Generalized Inverse Classification
Inverse classification is the process of perturbing an instance in a mea...
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Early Predictions of Movie Success: the Who, What, and When of Profitability
This paper proposes a decision support system to aid movie investment de...
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A budgetconstrained inverse classification framework for smooth classifiers
Inverse classification is the process of manipulating an instance such t...
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Optimal Multiple Surface Segmentation with Convex Priors in Irregularly Sampled Space
Optimal surface segmentation is widely used in numerous medical image se...
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Improved Dropout for Shallow and Deep Learning
Dropout has been witnessed with great success in training deep neural ne...
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RSG: Beating Subgradient Method without Smoothness and Strong Convexity
In this paper, we study the efficiency of a Restarted Sub Gradient (RS...
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Precise Phase Transition of Total Variation Minimization
Characterizing the phase transitions of convex optimizations in recoveri...
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Doubly Stochastic PrimalDual Coordinate Method for Bilinear SaddlePoint Problem
We propose a doubly stochastic primaldual coordinate optimization algor...
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Analysis of Nuclear Norm Regularization for Fullrank Matrix Completion
In this paper, we provide a theoretical analysis of the nuclearnorm reg...
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Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction
This paper explores robust recovery of a superposition of R distinct com...
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Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling
In crowd labeling, a large amount of unlabeled data instances are outsou...
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Universally Elevating the Phase Transition Performance of Compressed Sensing: NonIsometric Matrices are Not Necessarily Bad Matrices
In compressed sensing problems, ℓ_1 minimization or Basis Pursuit was kn...
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Precisely Verifying the Null Space Conditions in Compressed Sensing: A Sandwiching Algorithm
In this paper, we propose new efficient algorithms to verify the null sp...
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Recovery of Piecewise Smooth Images from Few Fourier Samples
We introduce a Pronylike method to recover a continuous domain 2D piec...
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Objectcentric Sampling for Finegrained Image Classification
This paper proposes to go beyond the stateoftheart deep convolutional...
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Subspace based low rank and joint sparse matrix recovery
We consider the recovery of a low rank and jointly sparse matrix from un...
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Deformation corrected compressed sensing (DCCS): a novel framework for accelerated dynamic MRI
We propose a novel deformation corrected compressed sensing (DCCS) fram...
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Iterative NonLocal Shrinkage Algorithm for MR Image Reconstruction
We introduce a fast iterative nonlocal shrinkage algorithm to recover M...
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A DivideandConquer Bayesian Approach to LargeScale Kriging
Flexible hierarchical Bayesian modeling of massive data is challenging d...
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SyGuS Techniques in the Core of an SMT Solver
We give an overview of recent techniques for implementing syntaxguided ...
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VietorisRips and Cech Complexes of Metric Gluings
We study VietorisRips and Cech complexes of metric wedge sums and metri...
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On Partial Covering For Geometric Set Systems
We study a generalization of the Set Cover problem called the Partial Se...
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NearOptimal Clustering in the kmachine model
The clustering problem, in its many variants, has numerous applications ...
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Information Geometric Approach to Bayesian Lower Error Bounds
Information geometry describes a framework where probability densities c...
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