Extraction of Network Information - Quality and Quantity - from Nodes of Neuronal Network. - Sayan Biswas (ICIT, 2016)

Can Musical Emotion Be Quantified With Neural Jitter Or Shimmer? A Novel EEG Based Study With Hindustani Classical Music. - Sayan Nag; Sayan Biswas; Sourya Sengupta; Shankha Sanyal; Archi Banerjee; Ranjan Sengupta; Dipak Ghosh (CoRR, 2017)

Gestalt Phenomenon in Music? A Neurocognitive Physics Study with EEG. - Shankha Sanyal; Archi Banerjee; Souparno Roy; Sourya Sengupta; Sayan Biswas; Sayan Nag; Ranjan Sengupta; Dipak Ghosh (CoRR, 2017)

Establishing the Price of Privacy in Federated Data Trading. - Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi (Protocols, Strands, and Logic, 2021)

An Incentive Mechanism for Trading Personal Data in Data Markets. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (ICTAC, 2021)

Stock Price Prediction using Bidirectional LSTM with Attention. - Sayan Biswas (ICAIC, 2022)

Tight Differential Privacy Blanket for Shuffle Model. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (CoRR, 2022)

Impact of Sampling on Locally Differentially Private Data Collection. - Sayan Biswas; Graham Cormode; Carsten Maple (CoRR, 2022)

A privacy preserving querying mechanism with high utility for electric vehicles. - Ugur-Ilker Atmaca; Sayan Biswas; Carsten Maple; Catuscia Palamidessi (CoRR, 2022)

Three-way optimization of privacy and utility of location data. - Sayan Biswas; Catuscia Palamidessi (CoRR, 2022)

Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (FPS (1), 2023)

Group Privacy for Personalized Federated Learning. - Filippo Galli; Sayan Biswas; Kangsoo Jung; Tommaso Cucinotta; Catuscia Palamidessi (ICISSP, 2023)

Understanding and optimizing the trade-off between privacy and utility from a foundational perspective. (Understanding and optimizing the trade-off between privacy and utility from a foundational perspective). - Sayan Biswas (2023)

Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond. - Filippo Galli; Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi; Tommaso Cucinotta (SN Comput. Sci., 2023)

SERGI: Similar Entity Retrieval using Grouped Images. - Akshit Sarpal; Raviteja Uppalapati; Sayan Biswas; Rajesh Narasimha Reddy; Samrat Kokkula (eCom@SIGIR, 2024)

Low-Cost Privacy-Aware Decentralized Learning. - Sayan Biswas; Davide Frey; Romaric Gaudel; Anne-Marie Kermarrec; Dimitri Lerévérend; Rafael Pires 001; Rishi Sharma 001; François Taïani (CoRR, 2024)

Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes. - Sayan Biswas; Mathieu Even; Anne-Marie Kermarrec; Laurent Massoulié; Rafael Pires 001; Rishi Sharma 001; Martijn de Vos (CoRR, 2024)

Secure Aggregation Meets Sparsification in Decentralized Learning. - Sayan Biswas; Anne-Marie Kermarrec; Rafael Pires 001; Rishi Sharma 001; Milos Vujasinovic (CoRR, 2024)

Bayes' capacity as a measure for reconstruction attacks in federated learning. - Sayan Biswas; Mark Dras; Pedro Faustini; Natasha Fernandes; Annabelle McIver; Catuscia Palamidessi; Parastoo Sadeghi (CoRR, 2024)

Distributed, communication-efficient, and differentially private estimation of KL divergence. - Mary Scott; Sayan Biswas; Graham Cormode; Carsten Maple (CoRR, 2024)

PRIVIC: A privacy-preserving method for incremental collection of location data. - Sayan Biswas; Catuscia Palamidessi (Proc. Priv. Enhancing Technol., 2024)

Fair Decentralized Learning. - Sayan Biswas; Anne-Marie Kermarrec; Rishi Sharma 001; Trinca Thibaud; Martijn de Vos (SaTML, 2025)

Boosting Asynchronous Decentralized Learning with Model Fragmentation. - Sayan Biswas; Anne-Marie Kermarrec; Alexis Marouani; Rafael Pires 001; Rishi Sharma 001; Martijn de Vos (WWW, 2025)

Noiseless Privacy-Preserving Decentralized Learning. - Sayan Biswas; Mathieu Even; Anne-Marie Kermarrec; Laurent Massoulié; Rafael Pires 001; Rishi Sharma 001; Martijn de Vos (Proc. Priv. Enhancing Technol., 2025)

Low-Cost Privacy-Preserving Decentralized Learning. - Sayan Biswas; Davide Frey; Romaric Gaudel; Anne-Marie Kermarrec; Dimitri Lerévérend; Rafael Pires 001; Rishi Sharma 001; François Taïani (Proc. Priv. Enhancing Technol., 2025)

Comparing privacy notions for protection against reconstruction attacks in machine learning. - Sayan Biswas; Mark Dras; Pedro Faustini; Natasha Fernandes; Annabelle McIver; Catuscia Palamidessi; Parastoo Sadeghi (CoRR, 2025)

Mitigating Membership Inference Vulnerability in Personalized Federated Learning. - Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi (CoRR, 2025)

Robust ML Auditing using Prior Knowledge. - Jade Garcia Bourrée; Augustin Godinot; Martijn de Vos; Milos Vujasinovic; Sayan Biswas; Gilles Trédan; Erwan Le Merrer; Anne-Marie Kermarrec (CoRR, 2025)