Results 21 to 30 of about 1,909,109 (209)
Scientific Reports, 2022 Selecting diverse molecules from unexplored areas of chemical space is one of the most important tasks for discovering novel molecules and reactions. This paper proposes a new approach for selecting a subset of diverse molecules from a given molecular ...
Tomohiro Nakamura +5 more
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Submodular Optimization Over Sliding Windows [PDF]
Proceedings of the 26th International Conference on World Wide Web, 2017 Maximizing submodular functions under cardinality constraints lies at the core of numerous data mining and machine learning applications, including data diversification, data summarization, and coverage problems. In this work, we study this question in the context of data streams, where elements arrive one at a time, and we want to design low-memory ...
Alessandro Epasto +3 more
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Hardness of submodular cost allocation : lattice matching and a simplex coloring conjecture [PDF]
, 2014 We consider the Minimum Submodular Cost Allocation (MSCA) problem. In this problem, we are given k submodular cost functions f1, ... , fk: 2V -> R+ and the goal is to partition V into k sets A1, ..., Ak so as to minimize the total cost sumi = 1,k fi(Ai).
Vondrák, Jan, Ene, Alina
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Monotone Submodular Maximization over a Matroid via Non-Oblivious Local Search [PDF]
, 2013 We present an optimal, combinatorial 1−1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pál and Vondrák, 2008), our algorithm is extremely simple ...
Filmus, Yuval +3 more
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Robust and Adaptive Sequential Submodular Optimization [PDF]
IEEE Transactions on Automatic Control, 2022 IEEE TAC ...
Vasileios Tzoumas +2 more
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Convex Analysis for Minimizing and Learning Submodular Set Functions [PDF]
, 2013 The connections between convexity and submodularity are explored, for purposes of minimizing and learning submodular set functions. First, we develop a novel method for minimizing a particular class of submodular functions, which can be expressed as a
Peter Stobbe, Stobbe, Peter
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A Submodular Optimization Framework for Imbalanced Text Classification With Data Augmentation
IEEE Access, 2023 In the domain of text classification, imbalanced datasets are a common occurrence. The skewed distribution of the labels of these datasets poses a great challenge to the performance of text classifiers.
Eyor Alemayehu, Yi Fang
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Submodular stochastic probing on matroids [PDF]
, 2014 In a stochastic probing problem we are given a universe E, where each element e in E is active independently with probability p in [0,1], and only a probe of e can tell us whether it is active or not. On this universe we execute a process that one by one
Sviridenko, Maxim +5 more
core +1 more source
Submodular Optimization in the MapReduce Model
CoRR, 2018 Submodular optimization has received significant attention in both practice and theory, as a wide array of problems in machine learning, auction theory, and combinatorial optimization have submodular structure. In practice, these problems often involve large amounts of data, and must be solved in a distributed way.
Liu, Paul, Vondrak, Jan
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Optimal Region Search with Submodular Maximization [PDF]
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020 Region search is an important problem in location-based services due to its wide applications. In this paper, we study the problem of optimal region search with submodular maximization (ORS-SM). This problem considers a region as a connected subgraph.
Xuefeng Chen 0001 +4 more
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