Convex Optimization
Adaptive Bound Optimization for Online Convex Optimization
... In this work, we analyzed a new algorithm for online convex optimization, which takes ideas both from online subgradient descent as well as follow-the-regularized-leader. In our analysis of this algorithm, ...
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Clustering Partially Observed Graphs via Convex Optimization
... using convex optimization, including LP relaxation (Charikar et ...different convex relaxation, and we focus on understanding when our con- vex program yields an optimal clustering without further ...
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IIR Digital Filter Design Using Convex Optimization
... The Steiglitz-McBride (SM) scheme [49] is adopted in many sequential design methods [7]-[13] under various design criteria. At each iteration, the denominator of an approximation error is replaced by its counterpart ...
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A Non–Convex Optimization Approach to Correlation Clustering
... We develop a non-convex optimization approach to correla- tion clustering using the Frank-Wolfe (FW) framework. We show that the basic approach leads to a simple and natural lo- cal search algorithm with ...
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SnapVX: A Network-Based Convex Optimization Solver
... SnapVX is a high-performance solver for convex optimization problems defined on networks. For problems of this form, SnapVX provides a fast and scalable solution with guaranteed global convergence. It ...
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An Online Convex Optimization Approach to Blackwell's Approachability
... Online Convex Optimization (OCO) framework, where Nature’s discrete action is replaced by the choice of a convex function at each stage, and the agent’s decision is a point in a convex ...
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Global passivity enforcement via convex optimization
... a convex optimization problem and efficiently solved based on recently developed interior-point ...The convex optimization is a special class of mathematical optimization problems in ...
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Misaligned Image Integration Based on Convex Optimization
... A new method can be introduced to solve this problem. The proposed system combining two images and produce an image with clear and natural color. The two images are flash image and long-exposure image [1]. The ...
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Online Convex Optimization Using Predictions
... Contributions of this paper. First, we introduce a general colored noise model for studying prediction errors in online convex optimization problems. The model captures three important features of real ...
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Quantum algorithms and lower bounds for convex optimization
... since optimization problems naturally have continuous inputs and outputs, whereas most previous work on quantum lower bounds focuses on discrete ...unconstrained convex optimization ...
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Distributed and parallel methods for structural convex optimization
... separable convex optimization (see Chapters 4 and ...separable convex problems when each inner subproblem is solved ...separable convex optimization based on Nesterov’s smoothing ...
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On Lower and Upper Bounds in Smooth and Strongly Convex Optimization
... strongly convex optimization algo- ...examine optimization algorithms as a recursive application of linear ...of optimization algorithms and the analytic theory of polynomials whereby new ...
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CVXPY: A Python-Embedded Modeling Language for Convex Optimization
... disciplined convex programming analysis and ...combine convex optimization with high-level features of Python such as parallelism and object- oriented ...
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Analysis of Langevin Monte Carlo via Convex Optimization
... order optimization algorithm for an ob- jective functional defined on the Wasserstein space of order ...from convex optimization, we give a non-asymptotic analysis of this method to sample from ...
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A Regularized Newton Method with Correction for Unconstrained Convex Optimization
... In this paper, we propose a regularized Newton method with correction for unconstrained convex optimization. At every iteration, not only a RNM step is computed but also two correction steps are computed ...
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CONVEX optimization forms the backbone of many
... of convex optimization, lesser attention has been paid to the fundamental hardness of these ...of convex optimization in machine learning and statis- tics, gaining an understanding of these ...
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Convex optimization using quantum oracles
... the convex set is given only in a black-box man- ner, through an ...in convex optimization identified by Grötschel, Lovász, and Schrijver [GLS88] are: membership, separation, optimization, ...
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Solving multiobjective mixed integer convex optimization problems
... multiobjective optimization problem is to convert the problem into a parameter-dependent single-objective one, known as ...integer convex optimization ...
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Filter Design Problems with Convex Optimization
... of convex optimization has been studied for about one ...of convex optimization have been discovered in various fields of applied science and engineering, such as automatic control system, ...
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Optimal Tensor Methods in Smooth Convex and Uniformly Convex Optimization
... non-convex optimization, which we do not consider in our ...formly convex functions and propose an algorithm, which is faster in this case, see our Algorithm ...
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