activity
20172025
most citedThe Tracking Machine Learning challenge : Accuracy phase

65 citations · 105 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

AgentFlux: Decoupled Fine-Tuning & Inference for On-Device Agentic Systems

Rohan Kadekodi, Zhan Jin, Keisuke Kamahori +5

The deployment of Large Language Models (LLMs) as agentic orchestrators has revolutionized task automation, but the need for privacy-preserving, cost-effective solutions demands on…

cs.LG2021★ 26 cited

The Tracking Machine Learning challenge : Throughput phase

Sabrina Amrouche, Laurent Basara, Paolo Calafiura +18

This paper reports on the second "Throughput" phase of the Tracking Machine Learning (TrackML) challenge on the Codalab platform. As in the first "Accuracy" phase, the participants…

hep-ex2019★ 65 cited

The Tracking Machine Learning challenge : Accuracy phase

Sabrina Amrouche, Laurent Basara, Paolo Calafiura +24

This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the tr…

cs.DC2018★ 6 cited

RCanopus: Making Canopus Resilient to Failures and Byzantine Faults

S. Keshav, W. Golab, B. Wong +2

Distributed consensus is a key enabler for many distributed systems including distributed databases and blockchains. Canopus is a scalable distributed consensus protocol that ensur…

cs.CR2017★ 8 cited

StealthDB: a Scalable Encrypted Database with Full SQL Query Support

Alexey Gribov, Dhinakaran Vinayagamurthy, Sergey Gorbunov

Encrypted database systems provide a great method for protecting sensitive data in untrusted infrastructures. These systems are built using either special-purpose cryptographic alg…