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cs.LG2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs
Christopher Brix, Thomas Noll
Neural networks are commonly used in safety-critical real-world applications. Unfortunately, the predicted output is often highly sensitive to small, and possibly imperceptible, ch…
cs.LG2020
Successfully Applying the Stabilized Lottery Ticket Hypothesis to the Transformer Architecture
Christopher Brix, Parnia Bahar, Hermann Ney
Sparse models require less memory for storage and enable a faster inference by reducing the necessary number of FLOPs. This is relevant both for time-critical and on-device computa…