We give a simple reduction from Bayesian incentive compatible mechanism design to algorithm design in settings where the agents' private types are multidimensional. The reduction preserves performance up to an add...
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ISBN:
(纸本)9780898719932
We give a simple reduction from Bayesian incentive compatible mechanism design to algorithm design in settings where the agents' private types are multidimensional. The reduction preserves performance up to an additive loss that can be made arbitrarily small in polynomial time in the number of agents and the size of the agents' type spaces.
The diverse world of machine learning applications has given rise to a plethora of algorithms and optimization methods, finely tuned to the specific regression or classification task at hand. We reduce the complexity ...
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ISBN:
(纸本)9781510838819
The diverse world of machine learning applications has given rise to a plethora of algorithms and optimization methods, finely tuned to the specific regression or classification task at hand. We reduce the complexity of algorithm design for machine learning by reductions: we develop reductions that take a method developed for one setting and apply it to the entire spectrum of smoothness and strong-convexity in applications. Furthermore, unlike existing results, our new reductions are optimal and more practical. We show how these new reductions give rise to new and faster running times on training linear classifiers for various families of loss functions, and conclude with experiments showing their successes also in practice.
In this paper, we investigate resource allocation for a multiuser communication system employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. The considered sys...
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In this paper, we investigate resource allocation for a multiuser communication system employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. The considered system enables secure simultaneous downlink and uplink communication via artificial noise (AN) generation causing interference to potential eavesdroppers. The system design objective is to maximize the system secrecy throughput by jointly optimizing the downlink beamformer, the AN covariance matrix, and the uplink transmit power. The algorithm design leads to a non-convex optimization problem and obtaining the globally optimal solution entails a prohibitively high computational complexity. Therefore, an efficient suboptimal iterative algorithm based on successive convex approximation is proposed. Our simulation results confirm that the proposed suboptimal algorithm achieves a substantial system secrecy throughput gain compared to two baseline schemes.
In this paper, a Supervised Adaptive Learning-based Fuzzy Controller (ALFC) with Neural Network Identification and Convex Parameterization is designed to identify and control the unmanned vehicle in an autonomous park...
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ISBN:
(纸本)9781467386838
In this paper, a Supervised Adaptive Learning-based Fuzzy Controller (ALFC) with Neural Network Identification and Convex Parameterization is designed to identify and control the unmanned vehicle in an autonomous parking system. The objective is to achieve robust learning and control while maintaining a low implementation cost. The proposed algorithm design incorporates the following learning and control theorems - non-linear system identification using neural network, fuzzy logic, supervised adaptive learning as well as multiple model based convex parameterization. To demonstrate the algorithm in a more straight forward manner, we are using a real nonlinear unmanned autonomous driving system as an example to apply the algorithm and showing the superior performance of controller. In the autonomous driving system, the proposed method can be used for both estimating and further controlling a desired vehicle speed and steering wheel turning. With a supervised adaptive learning-based method, robustness can be also assured under various operating environments regardless of unpredictable disturbances. The convex parameterization further improves the speed of convergence of the adaptive learning process for the Fuzzy controller by using the multiple models concept. Last but not least, comparative experiments have also demonstrated that systems equipped with the new algorithm are able to achieve faster and smoother convergence.
The role of graph width metrics, such as treewidth, pathwidth, and cliquewidth, is now seen as central in both algorithm design and the delineation of what is algorithmically possible. In this article we introduce a n...
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ISBN:
(纸本)1920682236
The role of graph width metrics, such as treewidth, pathwidth, and cliquewidth, is now seen as central in both algorithm design and the delineation of what is algorithmically possible. In this article we introduce a new, related, parameter for graphs, persistence.A path decomposition of width k, in which every vertex of the underlying graph belongs to at most l nodes of the path, has pathwidth k and persistence l, and a graph that admits such a decomposition has bounded persistence pathwidth.We believe that this natural notion truly captures the intuition behind the notion of pathwidth. We present some basic results regarding the general recognition of graphs having bounded persistence path decompositions.
Digital Signal Processing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent res...
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ISBN:
(纸本)9781479903573
Digital Signal Processing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent research shows that floating-point arithmetic can be made competitive by using a reduced-precision format instead of, e.g., IEEE standard single precision, thereby avoiding the algorithm design and implementation difficulties associated with fixed-point arithmetic. This paper investigates the effects of simplified floating-point arithmetic applied to an FMA-based floating-point unit and the associated software division and square root operations. Software operations are proposed which attain near-exact precision with twice the performance of exact algorithms and resolve overflow-related errors with inexpensive exponent-manipulation special instructions.
We present a novel algorithm for digital halftoning. The algorithm combines a technique based on error diffusion with the use of a cost function to determine termination. Its chief advantages include the use of random...
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ISBN:
(纸本)0909925828
We present a novel algorithm for digital halftoning. The algorithm combines a technique based on error diffusion with the use of a cost function to determine termination. Its chief advantages include the use of randomness to avoid visual artifacts in the binary image and its amenability to parallel execution. The algorithm is a member of the class of "dynamic communication algorithms" which make novel use of dynamically-routed messages to structure the execution of a program.
We propose an algorithm for designing nonuniform oversampled filterbanks with arbitray delay. The filterbank has uniform sections obtained by generalized DFT modulation;between the uniform sections, there are transiti...
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We propose an algorithm for designing nonuniform oversampled filterbanks with arbitray delay. The filterbank has uniform sections obtained by generalized DFT modulation;between the uniform sections, there are transition filters. There is no a priori constraint on the widths of transition filters channels, as in previous publications. The designalgorithm is composed of three steps, in which a bank (analysis or synthesis) is optimized by solving convex optimization problems for finding the prototypes of uniform sections and the transition filters. In the first step, an orthogonal filterbank is designed, while in the other steps a bank is given and the other is optimized. We present an example of design suitable to subband processing of wideband speech signals.
A multistage graph is center problem of computer science,many coordination and consistency problems can be convert into multistage graph *** obtained the fitness function by coding the vertex of multistage graph,and d...
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ISBN:
(纸本)9781467397155
A multistage graph is center problem of computer science,many coordination and consistency problems can be convert into multistage graph *** obtained the fitness function by coding the vertex of multistage graph,and designed the genetic algorithm for solving multistage graph *** results show that this algorithm is very effective and feasible.
Background,Motivation and Objective For large amounts of data are transported to the ground in the process of logging and limitations of cable bandwidth,so ultrasonic log data need to be compressed in the downhole whe...
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Background,Motivation and Objective For large amounts of data are transported to the ground in the process of logging and limitations of cable bandwidth,so ultrasonic log data need to be compressed in the downhole when *** acoustic data compression algorithm is
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