Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Narayanam, Ramasuri"'
This paper considers the problem of annotating datapoints using an expert with only a few annotation rounds in a label-scarce setting. We propose soliciting reliable feedback on difficulty in annotating a datapoint from the expert in addition to grou
Externí odkaz:
http://arxiv.org/abs/2410.20041
Unsupervised Representation Learning on graphs is gaining traction due to the increasing abundance of unlabelled network data and the compactness, richness, and usefulness of the representations generated. In this context, the need to consider fairne
Externí odkaz:
http://arxiv.org/abs/2304.04391
The paradigm of Federated learning (FL) deals with multiple clients participating in collaborative training of a machine learning model under the orchestration of a central server. In this setup, each client's data is private to itself and is not tra
Externí odkaz:
http://arxiv.org/abs/2110.12257
Network representation learning has traditionally been used to find lower dimensional vector representations of the nodes in a network. However, there are very important edge driven mining tasks of interest to the classical network analysis community
Externí odkaz:
http://arxiv.org/abs/1912.05140
Autor:
Lolakapuri, Phani Raj, Bhaskar, Umang, Narayanam, Ramasuri, Parija, Gyana R, Dayama, Pankaj S
We study the complexity of equilibrium computation in discrete preference games. These games were introduced by Chierichetti, Kleinberg, and Oren (EC '13, JCSS '18) to model decision-making by agents in a social network that choose a strategy from a
Externí odkaz:
http://arxiv.org/abs/1905.11680
Autor:
Pimplikar, Rakesh R, Mukherjee, Kushal, Parija, Gyana, Vishwakarma, Harit, Narayanam, Ramasuri, Ahuja, Sarthak, Vallam, Rohith D, Chaudhuri, Ritwik, Mondal, Joydeep
Research in Artificial Intelligence is breaking technology barriers every day. New algorithms and high performance computing are making things possible which we could only have imagined earlier. Though the enhancements in AI are making life easier fo
Externí odkaz:
http://arxiv.org/abs/1712.03724
Centrality is an important notion in complex networks; it could be used to characterize how influential a node or an edge is in the network. It plays an important role in several other network analysis tools including community detection. Even though
Externí odkaz:
http://arxiv.org/abs/1703.07580
Autor:
Narayanam, Ramasuri
With increasing demand for social network based activities, it is very important to understand not only the structural properties of social networks but also how social networks form, to better exploit their promise and potential. We believe the exis
Externí odkaz:
http://etd.iisc.ernet.in/handle/2005/2350
http://etd.ncsi.iisc.ernet.in/abstracts/3023/G24703-Abs.pdf
http://etd.ncsi.iisc.ernet.in/abstracts/3023/G24703-Abs.pdf
Research accomplishment is usually measured by considering all citations with equal importance, thus ignoring the wide variety of purposes an article is being cited for. Here, we posit that measuring the intensity of a reference is crucial not only t
Externí odkaz:
http://arxiv.org/abs/1609.00081
In this work, we consider the problem of influence maximization on a hypergraph. We first extend the Independent Cascade (IC) model to hypergraphs, and prove that the traditional influence maximization problem remains submodular. We then present a va
Externí odkaz:
http://arxiv.org/abs/1606.05065