Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, 2017 University of Alabama - Tuscaloosa
Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong
We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, 2017 Chinese Academy of Sciences
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song
Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, 2017 The Chinese University of Hong Kong
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang
The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, 2017 Southeast University
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu
The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...
Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu
No abstract provided.
Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, 2017 Zhejiang University
Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
Consider a multiple-input multiple-output (MIMO) downlink multi-user channel. A well-studied problem in such a system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called minimum mean square error (MMSE)-second-order cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851-856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using Second-Order Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492-496] and ...
Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, 2017 The Chinese University of Hong Kong
Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang
Aiming at solving large-scale optimization problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating the optimization problem as a consensus problem, the ADMM can be used to solve the consensus problem in a fully parallel fashion over a computer network with a star topology. However, traditional synchronized computation does not scale well with the problem size, as the speed of the algorithm is limited by the slowest workers. This is particularly true in a heterogeneous network where the computing nodes experience different computation and communication delays. In this paper, we propose ...
On Leveraging Multi-Path Transport In Mobile Networks, 2017 University of Massachusetts - Amherst
On Leveraging Multi-Path Transport In Mobile Networks, Yeon-Sup Lim
Doctoral Dissertations May 2014 - current
Multi-Path TCP (MPTCP) is a new transport protocol that enables mobile devices to simultaneously use several physical paths through multiple network interfaces. MPTCP is particularly useful for mobile devices, which usually have multiple wireless interfaces such as IEEE 802.11 (WiFi), cellular (3G/LTE), and Bluetooth. However, applying MPTCP to mobile devices introduces new concerns since they operate in harsh environments with resource constraints due to intermittent path availability and limited power supply. The goal of this thesis is to resolve these problems so as to be able to practically deploy MPTCP in mobile devices.
The first part of the ...
Hydrobase: An Iot Gardening Application, 2016 San Jose State University
Hydrobase: An Iot Gardening Application, Nandini Kant Goyal
As the world is moving towards urban agriculture, there are many IoT Hydroponic Control Systems being introduced these days. There are many different platforms emerging, but they all suffer from the same flaw, the software and hardware are so tightly integrated that most of the times the individuals have no freedom of how to use the product, or they need to completely hack the system. This brings us to the need of a system that is designed to allow the user more flexibility in platform configuration, as well as assist in platform construction. We propose a model called Hydrobase to ...
Android Drone: Remote Quadcopter Control With A Phone, 2016 California Polytechnic State University, San Luis Obispo
Android Drone: Remote Quadcopter Control With A Phone, Aubrey John Russell
The purpose of the “Android Drone” project was to create a quadcopter that can be controlled by user input sent over the phone’s Wi-Fi connection or 4G internet connection. Furthermore, the purpose was also to be able to receive live video feedback over the internet connection, thus making the drone an inexpensive option compared to other, equivalent drones that might cost thousands of dollars. Not only that, but the Android phone also has a host of other useful features that could be utilized by the drone: this includes GPS, pathing, picture taking, data storage, networking and TCP/IP, a ...
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, 2016 Singapore Management University
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Yu, Jianfei, Jing Jiang
Research Collection School Of Information Systems
Relation classification is the task of classifying the semantic relations between entity pairs intext. Observing that existing work has not fully explored using different representations forrelation instances, especially in order to better handle the asymmetry of relation types, in thispaper, we propose a neural network based method for relation classification that combines theraw sequence and the shortest dependency path representations of relation instances and usesmirror instances to perform pairwise relation classification. We evaluate our proposed modelson two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results showthat our combined model together with mirror instances achieves the state-of-the-art results ...
Agora: A Knowledge Marketplace For Machine Learning, 2016 The University of Western Ontario
Agora: A Knowledge Marketplace For Machine Learning, Mauro Ribeiro
Electronic Thesis and Dissertation Repository
More and more data are becoming part of people's lives. With the popularization of technologies like sensors, and the Internet of Things, data gathering is becoming possible and accessible for users. With these data in hand, users should be able to extract insights from them, and they want results as soon as possible. Average users have little or no experience in data analytics and machine learning and are not great observers who can collect enough data to build their own machine learning models. With large quantities of similar data being generated around the world and many machine learning models ...
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, 2016 University of Maine
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour
Electronic Theses and Dissertations
Understanding the impact of global climate change is a critical concern for society at large. One important piece of the climate puzzle is how large-scale ice sheets, such as those covering Greenland and Antarctica, respond to a warming climate. Given such ice sheets are under constant change, developing models that can accurately capture their dynamics represents a significant challenge to researchers. The problem, however, is properly capturing the dynamics of an ice sheet model requires a high model resolution and simulating these models is intractable even for state-of-the-art supercomputers.
This thesis presents a revolutionary approach to accurately capture ice sheet ...
Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, 2016 University of Tennessee, Knoxville
Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan
With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.
First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience ...
A Feasible No-Root Approach On Android, 2016 Singapore Management University
A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Deng, Robert H.
Research Collection School Of Information Systems
Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.
Optimizing Main Memory Usage In Modern Computing Systems To Improve Overall System Performance, 2016 Florida International University
Optimizing Main Memory Usage In Modern Computing Systems To Improve Overall System Performance, Daniel Jose Campello
FIU Electronic Theses and Dissertations
Operating Systems use fast, CPU-addressable main memory to maintain an application’s temporary data as anonymous data and to cache copies of persistent data stored in slower block-based storage devices. However, the use of this faster memory comes at a high cost. Therefore, several techniques have been implemented to use main memory more efficiently in the literature. In this dissertation we introduce three distinct approaches to improve overall system performance by optimizing main memory usage.
First, DRAM and host-side caching of file system data are used for speeding up virtual machine performance in today’s virtualized data centers. The clustering ...
Prosense, 2016 California Polytechnic State University, San Luis Obispo
Prosense, Johnny Favazza Ii, Casey Glasgow, Matt Epperson
This project aims to gather advanced data sets from MEMS sensors and GPS and deliver it to the user, who can capitalize on the data. The once negligible half-degree difference of your board barreling down a wave can be recorded from a gyro and exploited for the perfect turn. The exact speed dreaded by longboarders where speed wobbles turn into a road rash can be analysed and consequently avoided. Ascertaining the summit of your flight using combined GPS sensors from the ski ramp allows for the correct timing of tricks. When it comes to pursuing excellence in professional sports, amateur ...
Packet Filter Approach To Detect Denial Of Service Attacks, 2016 California State University, San Bernardino
Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish
Electronic Theses, Projects, and Dissertations
Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories ...
Learning Natural Language Inference With Lstm, 2016 Singapore Management University
Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang
Research Collection School Of Information Systems
Natural language inference (NLI) is a fundamentallyimportant task in natural languageprocessing that has many applications. Therecently released Stanford Natural LanguageInference (SNLI) corpus has made it possibleto develop and evaluate learning-centeredmethods such as deep neural networks for naturallanguage inference (NLI). In this paper,we propose a special long short-term memory(LSTM) architecture for NLI. Our modelbuilds on top of a recently proposed neural attentionmodel for NLI but is based on a significantlydifferent idea. Instead of derivingsentence embeddings for the premise and thehypothesis to be used for classification, our solutionuses a match-LSTM to perform word-by-wordmatching of the hypothesis with thepremise. This LSTM ...
The Contributions Of Anatol Rapoport To Game Theory, 2016 Western University
The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson
Political Science Publications
Game theory is used to rationally and dispassionately examine the strategic behaviour of nations, especially superpower behaviour. This article explains how basic game theory - at its simplest level - was used by Anatol Rapoport to generate ideas about how to enhance world peace. Rapoport was at the forefront of the game theoreticians who sought to conceptualize strategies that could promote international cooperation. Accordingly, the basic logic of game theory is explained using the game models of ‘Chicken’ and ‘Prisoner’s Dilemma’. These models were used by Rapoport in his books and lectures in simple and complex ways. Then Rapoport’s revolutionary ...