3 papers
cs.DS2026
Approximating Tensor Network Contraction with Sketches
Mike Heddes, Igor Nunes, Tony Givargis +1
Tensor network contraction is a fundamental mathematical operation that generalizes the dot product and matrix multiplication. It finds applications in numerous domains, such as da…
cs.LG2025
DeepCrossAttention: Supercharging Transformer Residual Connections
Mike Heddes, Adel Javanmard, Kyriakos Axiotis +3
Transformer networks have achieved remarkable success across diverse domains, leveraging a variety of architectural innovations, including residual connections. However, traditiona…
cs.LG2025
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration
Mike Heddes, Narayan Srinivasa, Tony Givargis +1
The excessive computational requirements of modern artificial neural networks (ANNs) are posing limitations on the machines that can run them. Sparsification of ANNs is often motiv…