Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 53 for “"submodular"”.
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Matchings, matroids and submodular functions
… matching, matroid intersection, and submodular function minimization. We develop simple, efficient, randomized algorithms for the first two problems, and prove new lower bounds for the last two problems. For the matching problem, we give an algorithm for constructing perfect or …
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Approximation algorithms for submodular optimization and graph problems
… combinatorial optimization problems involving submodular functions and graphs. The problems we study are NP-hard and therefore, assuming that P =/= NP, there do not exist polynomial-time algorithms that always output an optimal solution. In order to cope with the intractability of these …
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Scheduling to minimize power consumption using submodular functions
… for logarithmic approximation to maximizing any submodular function subject to budget constraints. We also introduce the online version of this scheduling problem, and show its relation to the classical secretary problem. In order to obtain constant competitive algorithms for this online version, …
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Performance bounds for greedy strategies in submodular optimization problems
To view the abstract, please see the full text of the document.
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Submodular Optimization in Multi-Robot Teams: Robustness, Resilience, and Decentralization
… optimization domain with the help of submodular and matroid optimization techniques. As a motivating example, we use a multi-robot environmental monitoring problem to extract the general formulation of a multi-robot decision-making problem. Consider the problem of deploying multi-agent …
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A Submodular Approach to Find Interpretable Directions in Text-to-Image Models
… edits using those keywords, and then applying a submodular ranking method to find which edits actually work. The experiments in this paper demonstrate the robustness of this approach and its ability to produce high-quality edits across various domains, such as dresses and living rooms.
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Flow Optimization in Dynamic and Continuous Networks (Polymatroids, Submodular, Max-Flow Min-Cut)
… continuous network models whose capacities are submodular set functions. Various applications are considered, including the finite polymatroid networks of Lawler.
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Distributionally Ambiguous Stackelberg Combinatorial Games for Submodular Optimization and Camera View-Frame Placement
… when the defender's objective is maximizing k-submodular func- tion, under both DRO and DRR frameworks. To solve problem, we derive valid inequalities from the diminishing property of k-submodular function, and strengthen them further by imposing an ordering over elements in the defender's …
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Parsimonious, Risk-Aware, and Resilient Multi-Robot Coordination
… in the coordination achieved by means of submodular function optimization. Submodularity encodes the diminishing returns property that arises in multi-robot coordination. For example, the marginal gain of assigning an additional robot to track the same target diminishes as the number of …
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Combinatorial structures in online and convex optimization
… simple algorithm, Inc-Fix, in the case of submodular base polyhedra. For cardinality-based submodular polytopes, we show that Inc-Fix can be speeded up to be the state-of-the-art method for minimizing uniform divergences. We show that the running time of Inc-Fix is independent of the …
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M♮-convexity, S-convexity, and their applications in operations
… in parametric optimization models maximizing submodular objective functions, and it is desirable to derive structural properties including monotone comparative statics of the optimal solutions or preservation of submodularity under the optimization operations. Yet, this task is challenging …
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Efficient and robust resource allocation for network function virtualization
… studied problem is not only NP-hard but also non-submodular. To address these challenges, we introduce a novel relaxation method such that the objective function of the relaxed placement subproblem becomes submodular. Leveraging this useful submodular property, we propose two algorithms that …
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Theoretical guarantees and complexity reduction in information planning
… selections, provide nearly optimal solutions for submodular monotone rewards. In this thesis, we examine several challenges that arise when performing real-world information planning. Our contributions are three-fold: (i) we provide theoretical guarantees for the greedy algorithm used in the …
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Competitive algorithms for online matching and vertex cover problems
… algorithms for the edge-weighted and submodular versions of online bipartite vertex cover, which all match the best performance of ski rental. As an application, we show that by analyzing our algorithm in the primal-dual framework, our result on submodular vertex cover implies an …
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Optimization of Markov Random Fields in Computer Vision
… efficient max-flow algorithm for multi-label submodular MRFs. In fact, such MRFs have been shown to be optimally solvable using max-flow based on an encoding of the labels proposed by Ishikawa, in which each variable $X_i$ is represented by $\ell$ nodes (where $\ell$ is the number of labels) …
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Optimization of Markov Random Fields in Computer Vision
… efficient max-flow algorithm for multi-label submodular MRFs. In fact, such MRFs have been shown to be optimally solvable using max-flow based on an encoding of the labels proposed by Ishikawa, in which each variable $X_i$ is represented by $\ell$ nodes (where $\ell$ is the number of labels) …
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Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity
… Since two of these objective functions are submodular, the search problem can be reformulated as maximizing the cumulative probability of detection (PD) with motion cost. The proof shows that greedy algorithms give near-optimal subgoals with high probability. In the last part, the approach …
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The Sum-Product Theorem and its Applications
… Third, I combine decomposability with submodularity to define submodular field grammars (SFGs), a novel class of probabilistic models that extends both sum-product networks and submodular Markov random fields. SFGs define a novel stochastic image grammar in which each object in the …
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Information overload in structured data
… news aggregation website, Reddit, and design a submodular recommender system that tailors a <em>personalized </em>frontpage for individual users. Second, we propose a novel submodular framework to summarize videos, where both transcript and comments are available. Third, we demonstrate how to …
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