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Convex Analysisの二,三の進展について
徹 丸山
- Vol. 70, Iss: 1, pp 97-119
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The article was published on 1977-02-01 and is currently open access. It has received 5933 citations till now.read more
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References
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Proceedings ArticleDOI
Truthful mechanism design for multi-dimensional scheduling via cycle monotonicity
Ron Lavi,Chaitanya Swamy +1 more
TL;DR: This work designs randomized mechanisms with non-trivial performance guarantees for a multidimensional scheduling domain, and is the first work that leverages cycle monotonicity in the multiddimensional setting.
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An Augmented ADMM Algorithm With Application to the Generalized Lasso Problem
TL;DR: A fast and stable algorithm for solving a class of optimization problems that arise in many statistical estimation procedures, such as sparse fused lasso over a graph, convex clustering, and trend filtering, among others is presented.
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High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
TL;DR: This work uses the natural hierarchical structure of the problem to extend the multiple kernel learning framework to kernels that can be embedded in a directed acyclic graph, and shows that it is then possible to perform kernel selection through a graph-adapted sparsity-inducing norm, in polynomial time in the number of selected kernels.
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A class of greedy algorithms for the generalized assignment problem
TL;DR: A relationship with the partial solution given by the LP-relaxation of the GAP is found, and the conditions under which the algorithm is asymptotically optimal in a probabilistic sense are derived.
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On Information Design in Games
TL;DR: The extent to which a designer can manipulate agents’ beliefs by disclosing information is characterized and the structure of optimal belief distributions is described, including a concave-envelope representation that subsumes the single-agent result of Kamenica and Gentzkow.