Parallel and Scalable Precise Clustering for Homologous Protein Discovery. - Stuart Byma; Akash Balasaheb Dhasade; Adrian M. Altenhoff; Christophe Dessimoz; James R. Larus (CoRR, 2019)

Parallel and Scalable Precise Clustering. - Stuart Byma; Akash Balasaheb Dhasade; Adrian M. Altenhoff; Christophe Dessimoz; James R. Larus (PACT, 2020)

Towards Prioritizing GitHub Issues. - Akash Balasaheb Dhasade; Akhila Sri Manasa Venigalla; Sridhar Chimalakonda (ISEC, 2020)

Guess what? You can boost Federated Learning for free. - Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Rafael Pires 001 (CoRR, 2021)

TEE-based decentralized recommender systems: The raw data sharing redemption. - Akash Balasaheb Dhasade; Nevena Dresevic; Anne-Marie Kermarrec; Rafael Pires 001 (IPDPS, 2022)

Decentralized Learning Made Easy with DecentralizePy. - Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Rafael Pires 001; Rishi Sharma 001; Milos Vujasinovic (EuroMLSys@EuroSys, 2023)

Get More for Less in Decentralized Learning Systems. - Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Rafael Pires 001; Rishi Sharma 001; Milos Vujasinovic; Jeffrey Wigger (ICDCS, 2023)

MoDeST: Bridging the Gap between Federated and Decentralized Learning with Decentralized Sampling. - Martijn de Vos; Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Erick Lavoie; Johan Pouwelse (CoRR, 2023)

QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation. - Akash Balasaheb Dhasade; Yaohong Ding; Song Guo 001; Anne-Marie Kermarrec; Martijn de Vos; Leijie Wu (CoRR, 2023)

Fairness Auditing with Multi-Agent Collaboration. - Martijn de Vos; Akash Balasaheb Dhasade; Jade Garcia Bourrée; Anne-Marie Kermarrec; Erwan Le Merrer; Benoît Rottembourg; Gilles Trédan (ECAI, 2024)

Energy-Aware Decentralized Learning with Intermittent Model Training. - Martijn de Vos; Akash Balasaheb Dhasade; Paolo Dini; Elia Guerra; Anne-Marie Kermarrec; Marco Miozzo; Rafael Pires 001; Rishi Sharma 001 (IPDPS (Workshops), 2024)

QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation. - Akash Balasaheb Dhasade; Yaohong Ding; Song Guo 001; Anne-Marie Kermarrec; Martijn de Vos; Leijie Wu (Middleware, 2024)

Revisiting Ensembling in One-Shot Federated Learning. - Youssef Allouah; Akash Balasaheb Dhasade; Rachid Guerraoui; Nirupam Gupta; Anne-Marie Kermarrec; Rafael Pinot; Rafael Pires 001; Rishi Sharma 001 (NeurIPS, 2024)

Practical Federated Learning without a Server. - Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Erick Lavoie; Johan Pouwelse; Rishi Sharma 001; Martijn de Vos (EuroMLSys, 2025)

Harnessing Increased Client Participation with Cohort-Parallel Federated Learning. - Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Tuan-Anh Nguyen; Rafael Pires 001; Martijn de Vos (EuroMLSys, 2025)

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging. - Akash Balasaheb Dhasade; Divyansh Jhunjhunwala; Milos Vujasinovic; Gauri Joshi; Anne-Marie Kermarrec (CoRR, 2025)

Boosting Resource-Constrained Federated Learning Systems With Guessed Updates. - Mohamed Yassine Boukhari; Akash Balasaheb Dhasade; Anne-Marie Kermarrec; Rafael Pires 001; Othmane Safsafi; Rishi Sharma 001 (IEEE Trans. Parallel Distributed Syst., 2025)