173 citations · 320 across the 25 of their papers we have counts for
3 papers · 1 filter
TripleSpin - a generic compact paradigm for fast machine learning computations
Krzysztof Choromanski, Francois Fagan, Cedric Gouy-Pailler +3
We present a generic compact computational framework relying on structured random matrices that can be applied to speed up several machine learning algorithms with almost no loss o…
On the boosting ability of top-down decision tree learning algorithm for multiclass classification
Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski
We analyze the performance of the top-down multiclass classification algorithm for decision tree learning called LOMtree, recently proposed in the literature Choromanska and Langfo…
Fast nonlinear embeddings via structured matrices
Krzysztof Choromanski, Francois Fagan
We present a new paradigm for speeding up randomized computations of several frequently used functions in machine learning. In particular, our paradigm can be applied for improving…