Zobrazeno 1 - 10
of 149
pro vyhledávání: '"Chakrabarti, Deepayan"'
Autor:
Jalan, Akhil, Chakrabarti, Deepayan
In network formation games, agents form edges with each other to maximize their utility. Each agent's utility depends on its private beliefs and its edges in the network. Strategic agents can misrepresent their beliefs to get a better resulting netwo
Externí odkaz:
http://arxiv.org/abs/2402.08779
Financial networks help firms manage risk but also enable financial shocks to spread. Despite their importance, existing models of financial networks have several limitations. Prior works often consider a static network with a simple structure (e.g.,
Externí odkaz:
http://arxiv.org/abs/2212.06808
Autor:
Chakrabarti, Deepayan
We consider the problem of linear classification under general loss functions in the limited-data setting. Overfitting is a common problem here. The standard approaches to prevent overfitting are dimensionality reduction and regularization. But dimen
Externí odkaz:
http://arxiv.org/abs/2110.01648
Akademický článek
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People belong to multiple communities, words belong to multiple topics, and books cover multiple genres; overlapping clusters are commonplace. Many existing overlapping clustering methods model each person (or word, or book) as a non-negative weighte
Externí odkaz:
http://arxiv.org/abs/1806.06945
We consider the problem of estimating community memberships of nodes in a network, where every node is associated with a vector determining its degree of membership in each community. Existing provably consistent algorithms often require strong assum
Externí odkaz:
http://arxiv.org/abs/1709.00407
The problem of finding overlapping communities in networks has gained much attention recently. Optimization-based approaches use non-negative matrix factorization (NMF) or variants, but the global optimum cannot be provably attained in general. Model
Externí odkaz:
http://arxiv.org/abs/1607.00084
Publikováno v:
Operations Research, 2019 Jul 01. 67(4), 965-983.
Externí odkaz:
https://www.jstor.org/stable/27295915
We tackle the problem of inferring node labels in a partially labeled graph where each node in the graph has multiple label types and each label type has a large number of possible labels. Our primary example, and the focus of this paper, is the join
Externí odkaz:
http://arxiv.org/abs/1401.7709