5 citations · 10 across the 10 of their papers we have counts for
4 papers · 1 filter
MuonBP: Faster Muon via Block-Periodic Orthogonalization
Ahmed Khaled, Kaan Ozkara, Tao Yu +2
Gradient orthogonalization is a simple strategy that shows great utility in speeding up gradient descent. The Muon optimizer (Jordan, Jin, et al., 2024) combines gradient orthogona…
MEL: Multi-level Ensemble Learning for Resource-Constrained Environments
Krishna Praneet Gudipaty, Walid A. Hanafy, Kaan Ozkara +4
AI inference at the edge is becoming increasingly common for low-latency services. However, edge environments are power- and resource-constrained, and susceptible to failures. Conv…
SPIRE: Conditional Personalization for Federated Diffusion Generative Models
Kaan Ozkara, Ruida Zhou, Suhas Diggavi
Recent advances in diffusion models have revolutionized generative AI, but their sheer size makes on device personalization, and thus effective federated learning (FL), infeasible.…
Stochastic Rounding for LLM Training: Theory and Practice
Kaan Ozkara, Tao Yu, Youngsuk Park
As the parameters of Large Language Models (LLMs) have scaled to hundreds of billions, the demand for efficient training methods -- balancing faster computation and reduced memory…