1 code implementation • 16 Apr 2023 • Navid Seidi, Ardhendu Tripathy, Sajal K. Das
Time elapsed till an event of interest is often modeled using the survival analysis methodology, which estimates a survival score based on the input features.
no code implementations • 28 Sep 2022 • Priyesh Ranjan, Ashish Gupta, Federico Corò, Sajal K. Das
While relaxing this assumption that anyway does not hold in reality due to the heterogeneous nature of devices, federated learning (FL) has emerged as a privacy-preserving solution to train a collaborative model over non-iid data distributed across a massive number of devices.
no code implementations • 3 Sep 2022 • Rahul Mishra, Hari Prabhat Gupta, Tanima Dutta, Sajal K. Das
In this paper, we propose a federated learning approach to suppress the unequal distribution of the noisy labels in the dataset of each participant.
no code implementations • 3 Sep 2022 • Ashish Gupta, Hari Prabhat Gupta, Sajal K. Das
With the enhancement of people's living standards and rapid growth of communication technologies, residential environments are becoming smart and well-connected, increasing overall energy consumption substantially.
1 code implementation • 14 Aug 2022 • Ashish Gupta, Tie Luo, Mao V. Ngo, Sajal K. Das
Not only this, but we can also distinguish between targeted and untargeted attacks among malicious clients, unlike most prior works which only consider one type of the attacks.
no code implementations • 2 Apr 2022 • Yeahia Sarker, Abdullah-Al-Zubaer Imran, Md Hafiz Ahamed, Ripon K. Chakrabortty, Michael J. Ryan, Sajal K. Das
To harvest maximum details for various receptive regions and high-quality synthetic images, \texttt{NLVAE} is introduced as a self-supervised strategy that reconstructs high-resolution images using disentangled information from the non-local neighbourhood.
no code implementations • 10 Feb 2021 • Francesco Betti Sorbelli, Sajal K. Das, Cristina M. Pinotti, Giulio Rigoni
For improving the performance, we propose range-based (RB) variants of the compared algorithms in which, instead of using the observed or the manufacturer radii, the actual measured distances between the MA and the GD are used.
no code implementations • 15 Dec 2020 • Francesco Betti Sorbelli, Cristina M. Pinotti, Simone Silvestri, Sajal K. Das
We validate our theoretical analysis and compare the observed localization error of the algorithms after collecting data from a testbed using ten GDs and one drone, equipped with ultra wide band (UWB) antennas and operating in an open field.
no code implementations • 15 Nov 2017 • Jiang Bian, Haoyi Xiong, Yanjie Fu, Sajal K. Das
In this paper, we present a novel community sensing paradigm -- {C}ommunity {S}ensing {W}ithout {A}ggregation}.