3 papers
cs.LG2025
Connecting Independently Trained Modes via Layer-Wise Connectivity
Yongding Tian, Zaid Al-Ars, Maksim Kitsak +1
Empirical studies have shown that continuous low-loss paths can be constructed between independently trained neural network models. This phenomenon, known as mode connectivity, ref…
cs.LG2024
Vanishing Variance Problem in Fully Decentralized Neural-Network Systems
Yongding Tian, Zaid Al-Ars, Maksim Kitsak +1
Federated learning and gossip learning are emerging methodologies designed to mitigate data privacy concerns by retaining training data on client devices and exclusively sharing lo…
cs.PL2023
An Intermediate Representation for Composable Typed Streaming Dataflow Designs
Matthijs A. Reukers, Yongding Tian, Zaid Al-Ars +4
Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred ov…