508 citations · 748 across the 20 of their papers we have counts for
5 papers · 1 filter
A deeper look at depth pruning of LLMs
Shoaib Ahmed Siddiqui, Xin Dong, Greg Heinrich +4
Large Language Models (LLMs) are not only resource-intensive to train but even more costly to deploy in production. Therefore, recent work has attempted to prune blocks of LLMs bas…
Identifying Layers Susceptible to Adversarial Attacks
Shoaib Ahmed Siddiqui, Thomas Breuel
In this paper, we investigate the use of pretraining with adversarial networks, with the objective of discovering the relationship between network depth and robustness. For this pu…
Efficient Estimation of k for the Nearest Neighbors Class of Methods
Aleksander Lodwich, Faisal Shafait, Thomas Breuel
The k Nearest Neighbors (kNN) method has received much attention in the past decades, where some theoretical bounds on its performance were identified and where practical optimizat…
Deep Self-Taught Learning for Handwritten Character Recognition
Frédéric Bastien, Yoshua Bengio, Arnaud Bergeron +14
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtained…
On the Relationship between the Posterior and Optimal Similarity
Thomas M. Breuel
For a classification problem described by the joint density , models of $P(ω\eqω'|x,x')$ (the ``Bayesian similarity measure'') have been shown to be an optimal similarity m…