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Institution

International Institute of Information Technology, Hyderabad

EducationHyderabad, India
About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Authentication & Internet security. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).


Papers
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Journal ArticleDOI
01 Dec 2015
TL;DR: Experimental results show that the proposed pattern growth approaches for extracting CPs from transactional databases improve the performance over the level-wise pruning approach and show that CPs could be used in meeting the demands of multiple advertisers.
Abstract: We propose a model of coverage patterns (CPs) and approaches for extracting CPs from transactional databases. The model is motivated by the problem of banner advertisement placement in e-commerce web sites. Normally, an advertiser expects that the banner advertisement should be displayed to a certain percentage of web site visitors. On the other hand, to generate more revenue for a given web site, the publisher makes efforts to meet the coverage demands of multiple advertisers. Informally, a CP is a set of non-overlapping items covered by certain percentage of transactions in a transactional database. The CPs do not satisfy the downward closure property. Efforts are being made in the literature to extract CPs using level-wise pruning approach. In this paper, we propose CP extraction approaches based on pattern growth techniques. Experimental results show that the proposed pattern growth approaches improve the performance over the level-wise pruning approach. The results also show that CPs could be used in meeting the demands of multiple advertisers.

17 citations

Journal ArticleDOI
TL;DR: An innovative method that learns parameters specific to the latent states using a graph‐theoretic model (temporal Multiple Kernel Learning, tMKL) that inherently links dynamics to the structure and finally predicts the grand average FC of the test subjects by leveraging a state transition Markov model.

17 citations

Proceedings ArticleDOI
06 Jul 2020
TL;DR: A blockchain-based access control scheme for the SDN framework that has the capability to resist various well-known attacks and alleviate the existing single point of controller failure issue in SDN is proposed.
Abstract: Software Defined Networking (SDN) becomes a de facto standard for the future Internet. SDN decouples the control plane from the data plane of a proprietary network asset to ensure better programmability and security for designing more innovative future network applications. Presently, the SDN framework does not have proper access control mechanism among different entities, namely SDN applications, SDN controllers and switches. To achieve this goal, this paper proposes a blockchain-based access control scheme for the SDN framework. The proposed scheme has the capability to resist various well-known attacks and alleviate the existing single point of controller failure issue in SDN.

17 citations

Posted Content
TL;DR: In this article, the authors formalize autonomous driving in a crowded environment as a Partially Observable Markov Decision Process (POMDP) and solve it through online belief-tree search.
Abstract: Autonomous driving in a crowded environment, e.g., a busy traffic intersection, is an unsolved challenge for robotics. The robot vehicle must contend with a dynamic and partially observable environment, noisy sensors, and many agents. A principled approach is to formalize it as a Partially Observable Markov Decision Process (POMDP) and solve it through online belief-tree search. To handle a large crowd and achieve real-time performance in this very challenging setting, we propose LeTS-Drive, which integrates online POMDP planning and deep learning. It consists of two phases. In the offline phase, we learn a policy and the corresponding value function by imitating the belief tree search. In the online phase, the learned policy and value function guide the belief tree search. LeTS-Drive leverages the robustness of planning and the runtime efficiency of learning to enhance the performance of both. Experimental results in simulation show that LeTS-Drive outperforms either planning or imitation learning alone and develops sophisticated driving skills.

17 citations

Proceedings Article
01 Jan 2018
TL;DR: In this paper, an auto-encoder based architecture is proposed for phase retrieval under both low overlap, where traditional techniques completely fail, and at higher levels of overlap, and for the high overlap case, optimizing the generator for reducing the forward model error is an appropriate choice.
Abstract: Fourier Ptychography is a recently proposed imaging technique that yields high-resolution images by computationally transcending the diffraction blur of an optical system. At the crux of this method is the phase retrieval algorithm, which is used for computationally stitching together low-resolution images taken under varying illumination angles of a coherent light source. However, the traditional iterative phase retrieval technique relies heavily on the initialization and also need a good amount of overlap in the Fourier domain for the successively captured low-resolution images, thus increasing the acquisition time and data. We show that an auto-encoder based architecture can be adaptively trained for phase retrieval under both low overlap, where traditional techniques completely fail, and at higher levels of overlap. For the low overlap case we show that a supervised deep learning technique using an autoencoder generator is a good choice for solving the Fourier ptychography problem. And for the high overlap case, we show that optimizing the generator for reducing the forward model error is an appropriate choice. Using simulations for the challenging case of uncorrelated phase and amplitude, we show that our method outperforms many of the previously proposed Fourier ptychography phase retrieval techniques.

17 citations


Authors

Showing all 2066 results

NameH-indexPapersCitations
Ravi Shankar6667219326
Joakim Nivre6129517203
Aravind K. Joshi5924916417
Ashok Kumar Das562789166
Malcolm F. White5517210762
B. Yegnanarayana5434012861
Ram Bilas Pachori481828140
C. V. Jawahar454799582
Saurabh Garg402066738
Himanshu Thapliyal362013992
Monika Sharma362384412
Ponnurangam Kumaraguru332696849
Abhijit Mitra332407795
Ramanathan Sowdhamini332564458
Helmut Schiessel321173527
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202310
202229
2021373
2020440
2019367
2018364