Akash Balasaheb Dhasade

According to our database, Akash Balasaheb Dhasade authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

Effective LoRA Adapter Routing using Task Representations.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Igor Pavlovic, Diana Petrescu, Rafael Pires, Mathis Randl, Martijn de Vos

CoRR, January, 2026

Efficient Federated Search for Retrieval-Augmented Generation Using Lightweight Routing.

Akash Balasaheb Dhasade, Rachid Guerraoui, Anne-Marie Kermarrec, Diana Petrescu, Rafael Pires, Mathis Randl, Martijn de Vos

Proceedings of the Distributed Applications and Interoperable Systems, 2026

2025

Robust Federated Inference.

Akash Balasaheb Dhasade, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Maxime Jacovella, Anne-Marie Kermarrec, Rafael Pinot

CoRR, October, 2025

Practical and Private Hybrid ML Inference with Fully Homomorphic Encryption.

Sayan Biswas, Philippe Chartier, Akash Balasaheb Dhasade, Tom Jurien, David Kerriou, Anne-Marie Kerrmarec, Mohammed Lemou, Franklin Tranie, Martijn de Vos, Milos Vujasinovic

CoRR, September, 2025

Boosting Resource-Constrained Federated Learning Systems With Guessed Updates.

Mohamed Yassine Boukhari, Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Rafael Pires, Othmane Safsafi, Rishi Sharma

IEEE Trans. Parallel Distributed Syst., August, 2025

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging.

Akash Balasaheb Dhasade, Divyansh Jhunjhunwala, Milos Vujasinovic, Gauri Joshi, Anne-Marie Kermarrec

CoRR, May, 2025

Harnessing Increased Client Participation with Cohort-Parallel Federated Learning.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Tuan-Anh Nguyen, Rafael Pires, Martijn de Vos

Proceedings of the 5th Workshop on Machine Learning and Systems, 2025

Practical Federated Learning without a Server.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Erick Lavoie, Johan Pouwelse, Rishi Sharma, Martijn de Vos

Proceedings of the 5th Workshop on Machine Learning and Systems, 2025

2024

Revisiting Ensembling in One-Shot Federated Learning.

Youssef Allouah, Akash Balasaheb Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation.

Akash Balasaheb Dhasade, Yaohong Ding, Song Guo, Anne-Marie Kermarrec, Martijn de Vos, Leijie Wu

Proceedings of the 25th International Middleware Conference, 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, Rishi Sharma

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

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

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation.

Akash Balasaheb Dhasade, Yaohong Ding, Song Guo, Anne-Marie Kermarrec, Martijn de Vos, Leijie Wu

CoRR, 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

Get More for Less in Decentralized Learning Systems.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma, Milos Vujasinovic, Jeffrey Wigger

Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, 2023

Decentralized Learning Made Easy with DecentralizePy.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma, Milos Vujasinovic

Proceedings of the 3rd Workshop on Machine Learning and Systems, 2023

2022

TEE-based decentralized recommender systems: The raw data sharing redemption.

Akash Balasaheb Dhasade, Nevena Dresevic, Anne-Marie Kermarrec, Rafael Pires

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021

Guess what? You can boost Federated Learning for free.

Akash Balasaheb Dhasade, Anne-Marie Kermarrec, Rafael Pires

CoRR, 2021

2020

Towards Prioritizing GitHub Issues.

Akash Balasaheb Dhasade, Akhila Sri Manasa Venigalla, Sridhar Chimalakonda

Proceedings of the ISEC 2020: 13th Innovations in Software Engineering Conference, 2020

Parallel and Scalable Precise Clustering.

Stuart Byma, Akash Balasaheb Dhasade, Adrian M. Altenhoff, Christophe Dessimoz, James R. Larus

Proceedings of the PACT '20: International Conference on Parallel Architectures and Compilation Techniques, 2020

2019

Parallel and Scalable Precise Clustering for Homologous Protein Discovery.

Stuart Byma, Akash Balasaheb Dhasade, Adrian M. Altenhoff, Christophe Dessimoz, James R. Larus

CoRR, 2019