2 citations · 3 across the 35 of their papers we have counts for
5 papers · 2 filters
Exploiting Biases in Attention for Transformers
Charles Herr, Gabriele Spadaro, Enzo Tartaglione
Attention is known to be sparse in vision transformers. In particular, we analyze the unequal relevance of attention-matrix columns to the final computation and show that this phen…
Validity-Preserving Hierarchical RL for Joint Routing and Switch Placement in EDA
Dorian Gailhard, Ugo Lecerf, Enzo Tartaglione +2
Routing and switch placement are fundamental combinatorial optimization problems in chip design, requiring the joint optimization of routing topology and physical placement under s…
From Deep to Shallow: Unconstrained and Efficient Layer Merging Strategy
Petro Shulzhenko, Gabriele Spadaro, Enzo Tartaglione
Although Deep Neural Networks have become foundational in many areas of Machine Learning, high computational demands limit their application in resource-constrained environments. T…
CutClean: Neural Network Pruning for Privacy-Preserving Inference
Leonardo Magliolo, Vito Paolo Pastore, Giuseppe Valenzise +1
Neural networks are increasingly deployed in high-stakes applications with growing privacy leakage concerns. We show that this privacy leakage can occur even in the absence of repr…
Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models
Ivan Luiz De Moura Matos, Abdel Djalil Sad Saoud, Ekaterina Iakovleva +2
The issue of algorithmic biases in deep learning has led to the development of various debiasing techniques, many of which perform complex training procedures or dataset manipulati…