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# Image Classification Edit

330 papers with code · Computer Vision

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# Optimal Attacks against Multiple Classifiers

Juan C. Perdomo et al

The main technical challenge we consider is the design of best response oracles that can be implemented in a Multiplicative Weight Updates framework to find equilibrium strategies in the zero-sum game.

01 May 2019

# How Training Data Affect the Accuracy and Robustness of Neural Networks for Image Classification

Suhua Lei et al

In light of a recent study on the mutual influence between robustness and accuracy over 18 different ImageNet models, this paper investigates how training data affect the accuracy and robustness of deep neural networks.

01 May 2019

# Learning Implicitly Recurrent CNNs Through Parameter Sharing

Pedro Savarese et al

Restricting the number of templates yields a flexible hybridization of traditional CNNs and recurrent networks.

01 May 2019

# Convolutional Neural Networks combined with Runge-Kutta Methods

Mai Zhu et al

A convolutional neural network for image classification can be constructed mathematically since it can be regarded as a multi-period dynamical system.

01 May 2019

# signSGD via Zeroth-Order Oracle

Sijia Liu et al

Our study shows that ZO signSGD requires $\sqrt{d}$ times more iterations than signSGD, leading to a convergence rate of $O(\sqrt{d}/\sqrt{T})$ under mild conditions, where $d$ is the number of optimization variables, and $T$ is the number of iterations.

01 May 2019

# Probabilistic Federated Neural Matching

Mikhail Yurochkin et al

In federated learning problems, data is scattered across different servers and exchanging or pooling it is often impractical or prohibited.

01 May 2019

# Pooling Is Neither Necessary nor Sufficient for Appropriate Deformation Stability in CNNs

Avraham Ruderman et al

In this work, we rigorously test these questions, and find that deformation stability in convolutional networks is more nuanced than it first appears: (1) Deformation invariance is not a binary property, but rather that different tasks require different degrees of deformation stability at different layers.

01 May 2019

# FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS

Mohammad K. Ebrahimpour et al

We demonstrate that a simple linear mapping can be learned from sensitivity maps to bounding box coordinates, localizing the recognized object.

01 May 2019

# RedSync : Reducing Synchronization Traffic for Distributed Deep Learning

Jiarui Fang et al

Data parallelism has become a dominant method to scale Deep Neural Network (DNN) training across multiple nodes.

01 May 2019

# HIGHLY EFFICIENT 8-BIT LOW PRECISION INFERENCE OF CONVOLUTIONAL NEURAL NETWORKS

Haihao Shen et al

High throughput and low latency inference of deep neural networks are critical for the deployment of deep learning applications.

01 May 2019