Submodular Minimization with General Barrier Functions
Online Submodular Minimization
... To motivate the online decision-making problem with submodular cost functions, here is an example from the survey by McCormick (2006). Consider a factory capable of producing any subset from a given set of ...
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Geometric Rescaling Algorithms for Submodular Function Minimization
... of submodular functions that arise in these applications, such as decomposability [13, 12, 26, ...for general functions, simple iterative algorithms appear to outperform the provably ...
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Active-set Methods for Submodular Minimization Problems
... the submodular function minimization (SFM) and the quadratic minimization prob- lems regularized by the Lov´asz extension of the submodular ...is submodular and its Lov´asz extension is ...
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Discrete Newton’s Algorithm for Parametric Submodular Function Minimization
... more general case of submodular functions f ...considering submodular functions (as opposed to modular functions) makes the problem considerably harder since the number of input ...
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Maximization of Non-Monotone Submodular Functions
... In general, there are practical applications with larger limits k and even limits based on more complex ...non-monotone submodular function of the selected office ...
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Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization
... variables. Functions θ f : L f → R, associated with factors f ∈ F , are called potentials and define local costs on values of variables and their ...energy minimization problem consists in finding a ...
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Scheduling to Minimize Power Consumption using Submodular Functions
... a general optimization problem, called submodular maximization with budget ...this general problem, for example, Set Cover and Max Cover [7, 11] and the submodular maxi- mization problems ...
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Convex Analysis for Minimizing and Learning Submodular Set Functions
... and submodular minimization established in Chapter 3, a natural idea, then, is to use techniques of distributed convex optimization for distributed submodular ...
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A Min-Max Theorem for Transversal Submodular Functions and Its Implications
... t-submodular functions are far more general than k- submodular functions and submodular functions on product ...t-submodular functions with symmetric binary ...
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Submodular Secretary Problem with Shortlists under General Constraints
... the Submodular Secetary Problem ...the submodular secretary problem with shortlists in the most gen- eral case of monotone submodular ...for submodular secretary problem is due to [34], who ...
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Minimizing Submodular Functions on Diamonds via Generalized Fractional Matroid Matchings
... 4 general submodular function on diamonds from ...standard submodular minimization is the minimization of bisubmodular functions by Qi [24], Fujishige and Iwata [5], and ...
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Streaming Algorithms for Maximizing Monotone Submodular Functions under a Knapsack Constraint
... Our Technique We begin by a straightforward generalization of the algorithm of [2] for the special case of cardinality constraint (Section 2). This algorithm proceeds by adding a new item into the current set only if its ...
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General Quadratic Risk Minimization: a Variational Approach
... risk minimization subject to var- ious constraints (see ( ...dual functions in order to attain this goal, by appropriately choosing a vector space of perturbations and a perturbation function (see Step ...
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Beyond the Regret Minimization Barrier: Optimal Algorithms for Stochastic Strongly-Convex Optimization
... cost functions that are also smooth, a O( T 1 ) rate is attainable by vanilla stochastic gradient descent (SGD), and further that SGD with special averaging of the last iterates recovers this optimal rate even in ...
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A Class of Submodular Functions for Document Summarization
... to submodular function opti- mization, a property not explicitly mentioned in these ...of submodular functions for summariza- tion: if summarization algorithms are repeatedly de- veloped that, by ...
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Maximizing Bisubmodular and k-submodular Functions
... Submodular functions play a key role in combinatorial opti- mization and in the study of valued constraint satisfaction ...bisubmodular functions, which assign values to disjoint pairs of sets. Like ...
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Barrier Smoothing for Nonsmooth Convex Minimization
... convex minimization using self-concordant ...the barrier smoothing approach main- tains the sublinear-convergence rate, it affords a new analytic step size, which significantly enhances the practical ...
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Disjunctive analogues of submodular and supermodular pseudo-Boolean functions
... Pseudo-Boolean functions include Boolean functions (that may be identi3ed with those pseudo-Boolean functions whose range is contained in {0; 1}), as well as various combinatorial set ...
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Multi document Summarization via Budgeted Maximization of Submodular Functions
... from submodular optimization, the objective function measuring the summary quality must be ...In general, there are two ways to apply submodular optimization to any application ...many ...
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New performance guarantees for the greedy maximization of submodular set functions
... arXiv:1506.00423v1 [math.OC] 1 Jun 2015 MAXIMIZATION OF SUBMODULAR SET FUNCTIONS JUSSI LAITILA AND ATTE MOILANEN Abstract. We present new tight performance guarantees for the greedy maximization of ...
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