Search Results for author:
Found 4 papers, 0 papers with code
A Hardware Evaluation Framework for Large Language Model Inference
With the large hardware needed to simply run LLM inference, evaluating different hardware designs becomes a new bottleneck.
Evolving Transferable Neural Pruning Functions
While most prior works in evolutionary learning aim at directly searching the structure of a network, few attempts have been made on another promising track, channel pruning, which recently has made major headway in designing efficient deep learning models.
Class-Discriminative CNN Compression
We then propose a novel layer-adaptive hierarchical pruning approach, where we use a coarse class discrimination scheme for early layers and a fine one for later layers.
Rethinking Class-Discrimination Based CNN Channel Pruning
To this end, we initiate the first study on the effectiveness of a broad range of discriminant functions on channel pruning.
