1 code implementation • 23 Feb 2024 • Swaroop Nath, Tejpalsingh Siledar, Sankara Sri Raghava Ravindra Muddu, Rupasai Rangaraju, Harshad Khadilkar, Pushpak Bhattacharyya, Suman Banerjee, Amey Patil, Sudhanshu Shekhar Singh, Muthusamy Chelliah, Nikesh Garera
While this strategy has proven to be effective, the training methodology requires a lot of human preference annotation (usually of the order of tens of thousands) to train {$\varphi$}.
1 code implementation • 18 Feb 2024 • Tejpalsingh Siledar, Swaroop Nath, Sankara Sri Raghava Ravindra Muddu, Rupasai Rangaraju, Swaprava Nath, Pushpak Bhattacharyya, Suman Banerjee, Amey Patil, Sudhanshu Shekhar Singh, Muthusamy Chelliah, Nikesh Garera
Evaluation of opinion summaries using conventional reference-based metrics rarely provides a holistic evaluation and has been shown to have a relatively low correlation with human judgments.
no code implementations • 2 Feb 2024 • Dildar Ali, Suman Banerjee, Yamuna Prasad
In the second one, we introduce randomness with the first one, where we perform the marginal gain computation for a sample of randomly chosen billboard slots.
no code implementations • 29 Jan 2024 • Dildar Ali, Suman Banerjee, Yamuna Prasad
In the context of an influence provider, it is a loss for him if he offers more or less views.
no code implementations • 10 Jun 2022 • Varun Chandrasekaran, Suman Banerjee, Diego Perino, Nicolas Kourtellis
Federated learning (FL), where data remains at the federated clients, and where only gradient updates are shared with a central aggregator, was assumed to be private.
no code implementations • 29 Sep 2021 • Jayaram Raghuram, Yijing Zeng, Dolores Garcia, Somesh Jha, Suman Banerjee, Joerg Widmer, Rafael Ruiz
In this paper, we address the setting where the target domain has only limited labeled data from a distribution that is expected to change frequently.
1 code implementation • 2 Aug 2021 • Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Rafael Ruiz Ortiz, Somesh Jha, Joerg Widmer, Suman Banerjee
The problem of end-to-end learning of a communication system using an autoencoder -- consisting of an encoder, channel, and decoder modeled using neural networks -- has recently been shown to be an effective approach.
1 code implementation • 29 Jul 2020 • Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
We propose an unsupervised anomaly detection framework based on the internal DNN layer representations in the form of a meta-algorithm with configurable components.
no code implementations • 8 Apr 2020 • Suman Banerjee, Mamata Jenamani, Dilip Kumar Pratihar
In this paper, we study this problem with a variation, where a set of nodes are designated as target nodes, each of them is assigned with a benefit value, that can be earned by influencing them, and our goal is to maximize the earned benefit by initially activating a set of nodes within the budget.
Social and Information Networks Data Structures and Algorithms Multiagent Systems
no code implementations • ICLR 2019 • Suman Banerjee, Mitesh M. Khapra
Domain specific goal-oriented dialogue systems typically require modeling three types of inputs, viz., (i) the knowledge-base associated with the domain, (ii) the history of the conversation, which is a sequence of utterances and (iii) the current utterance for which the response needs to be generated.
no code implementations • 4 Dec 2018 • Suman Banerjee, Rogers Mathew, Fahad Panolan
We have the following results on the TSS problem: -> It was shown by Nichterlein et al. [Social Network Analysis and Mining, 2013] that it is possible to compute an optimal-sized target set in $O(2^{(2^{t}+1)t}\cdot m)$ time, where $t$ denotes the cardinality of a minimum degree-$0$ modulator of $G$.
Computational Complexity Data Structures and Algorithms Social and Information Networks 68W25, 68Q17, 68R10,
1 code implementation • EMNLP 2018 • Nikita Moghe, Siddhartha Arora, Suman Banerjee, Mitesh M. Khapra
Existing dialog datasets contain a sequence of utterances and responses without any explicit background knowledge associated with them.
no code implementations • 16 Aug 2018 • Suman Banerjee, Mamata Jenamani, Dilip Kumar Pratihar
Given a social network with diffusion probabilities as edge weights and an integer k, which k nodes should be chosen for initial injection of information to maximize influence in the network?
Social and Information Networks
no code implementations • COLING 2018 • Suman Banerjee, Nikita Moghe, Siddhartha Arora, Mitesh M. Khapra
("Can you help me in booking a table at this restaurant?").