9 citations · 12 across the 6 of their papers we have counts for
10 papers
DiffusionGemma Technical Report
DiffusionGemma Team, Adrien Ali Taïga, James Assiene +41
We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rather than decoding one token at…
Large-scale semi-supervised learning with online spectral graph sparsification
Daniele Calandriello, Alessandro Lazaric, Michal Valko
We introduce Sparse-HFS, a scalable algorithm that can compute solutions to SSL problems using only O(n polylog(n)) space and O(m polylog(n)) time.
Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
Daniele Calandriello, Alessandro Lazaric, Michal Valko
One of the major limits of kernel ridge regression (KRR) is that storing and manipulating the kernel matrix K_n for n samples requires O(n^2) space, which rapidly becomes unfeasibl…
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric +1
Graph-based techniques and spectral graph theory have enriched the field of machine learning with a variety of critical advances. A central object in the analysis is the graph Lapl…
Analysis of Nystrom method with sequential ridge leverage scores
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Large-scale kernel ridge regression (KRR) is limited by the need to store a large kernel matrix K_t. To avoid storing the entire matrix K_t, Nystrom methods subsample a subset of c…
Proximal Point Nash Learning from Human Feedback
Daniil Tiapkin, Daniele Calandriello, Denis Belomestny +5
Traditional Reinforcement Learning from Human Feedback (RLHF) often relies on reward models, frequently assuming preference structures like the Bradley--Terry model, which may not…