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Feb 11, 2017
Machine Learning
Distributed
Parallel
and Cluster Computing

Training Deep Neural Networks via Optimization Over Graphs

In this work, we propose to train a deep neural network by distributed optimization over a graph. Two nonlinear functions are considered: the rectifi…
Aug 11, 2018
Neural and Evolutionary Computation

Automatically Designing CNN Architectures Using Genetic Algorithm for…

Convolutional Neural Networks (CNNs) have gained a remarkable success on many real-world problems in recent years. However, the performance of CNNs i…
Mar 10, 2019
Computer Vision
Artificial Intelligence
Machine Learning
Neural and Evolutionary Computation

A Hybrid GA-PSO Method for Evolving Architecture and Short Connection…

Image classification is a difficult machine learning task, where Convolutional Neural Networks (CNNs) have been applied for over 20 years in order to…
Apr 18, 2018
Machine Learning
Artificial Intelligence

An Adaptive Clipping Approach for Proximal Policy Optimization

Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learni…
Apr 13, 2019
Cryptography and Security

Automatic Device Selection and Access PolicyGeneration based on User …

The emerging Internet of Things (IoT) has lead to a dramatic increase in type, quantity, and the number of functions that can be offered in a smart e…
May 28, 2017
Computer Vision

Cross-modal Subspace Learning for Fine-grained Sketch-based Image R…

Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap between sketch and photo. Compared with pixel-perfect depictions of…
Mar 03, 2015
Information Theory

Deployment Issues for Massive MIMO Systems

In this paper we examine a number of deployment issues which arise from practical considerations in massive multiple-input-multiple-output (MIMO) sys…
Jul 30, 2018
Machine Learning
Signal Processing

Kernel Density Estimation-Based Markov Models with Hidden State

We consider Markov models of stochastic processes where the next-step conditional distribution is defined by a kernel density estimator (KDE), simila…
Mar 15, 2018
Programming Languages

We have presented a type and effect system which infers sharing possibly introduced by the evaluation of an expression. Sharing is directly represented at the syntactic level as a relation among free variables. This representation allows us to expre…

Tracing sharing in an imperative pure calculus (Extended Version)

We introduce a type and effect system, for an imperative object calculus, which infers "sharing" possibly introduced by the evaluation of an expressi…
Oct 23, 2019
Neural and Evolutionary Computation
Computer Vision

Genetic Programming for Evolving Similarity Functions for Clustering:…

Clustering is a difficult and widely-studied data mining task, with many varieties of clustering algorithms proposed in the literature. Nearly all al…
Dec 29, 2019
Neural and Evolutionary Computation

Divide-and-Conquer Large Scale Capacitated Arc Routing Problems with …

The capacitated arc routing problem is a very important problem with many practical applications. This paper focuses on the large scale capacitated a…
Feb 02, 2018
Neural and Evolutionary Computation
Artificial Intelligence

Generating Redundant Features with Unsupervised Multi-Tree Genetic …

Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of moder…
Feb 24, 2018
Neural and Evolutionary Computation

Improved Regularity Model-based EDA for Many-objective Optimization

The performance of multi-objective evolutionary algorithms deteriorates appreciably in solving many-objective optimization problems which encompass m…
Mar 17, 2018
Neural and Evolutionary Computation
Computer Vision

Evolving Deep Convolutional Neural Networks by Variable-length Partic…

Convolutional neural networks (CNNs) are one of the most effective deep learning methods to solve image classification problems, but the best archite…
Aug 31, 2015
Conferences: ICCV
Computer Vision
Artificial Intelligence
Machine Learning

Domain Generalization for Object Recognition with Multi-task Autoen…

The problem of domain generalization is to take knowledge acquired from a number of related domains where training data is available, and to then suc…
Oct 30, 2017
Neural and Evolutionary Computation
Computer Vision

Evolving Deep Convolutional Neural Networks for Image Classification

Evolutionary computation methods have been successfully applied to neural networks since two decades ago, while those methods cannot scale well to th…
Apr 12, 2019
Machine Learning
Networking and Internet Architecture

Effective Scheduling Function Design in SDN through Deep Reinforcemen…

Recent research on Software-Defined Networking (SDN) strongly promotes the adoption of distributed controller architectures. To achieve high network …
Aug 20, 2018
Neural and Evolutionary Computation
Artificial Intelligence
Computer Vision
Machine Learning

A Hybrid DE Approach to Designing CNN for Image Classification

Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have rece…
Jan 27, 2019
Artificial Intelligence

Composing Distributed Data-intensive Web Services Using a Flexible …

Web Service Composition (WSC) is a particularly promising application of Web services, where multiple individual services with specific functionaliti…
Feb 25, 2019
Machine Learning

Rapidly Adapting Moment Estimation

Adaptive gradient methods such as Adam have been shown to be very effective for training deep neural networks (DNNs) by tracking the second moment of…
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