6 citations · 26 across the 32 of their papers we have counts for
7 papers · 1 filter
Exact Non-Oblivious Performance of Rademacher Random Embeddings
Maciej Skorski, Alessandro Temperoni
This paper revisits the performance of Rademacher random projections, establishing novel statistical guarantees that are numerically sharp and non-oblivious with respect to the inp…
Robust and Provable Guarantees for Sparse Random Embeddings
Maciej Skorski, Alessandro Temperoni, Martin Theobald
In this work, we improve upon the guarantees for sparse random embeddings, as they were recently provided and analyzed by Freksen at al. (NIPS'18) and Jagadeesan (NIPS'19). Specifi…
Confidence-Optimal Random Embeddings
Maciej Skorski
The seminal result of Johnson and Lindenstrauss on random embeddings has been intensively studied in applied and theoretical computer science. Despite that vast body of literature,…
Random Embeddings with Optimal Accuracy
Maciej Skorski
This work constructs Jonson-Lindenstrauss embeddings with best accuracy, as measured by variance, mean-squared error and exponential concentration of the length distortion. Lower b…
Efficient Sampled Softmax for Tensorflow
Maciej Skorski
This short paper discusses an efficient implementation of \emph{sampled softmax loss} for Tensorflow. The speedup over the default implementation is achieved due to simplification…
Revisiting Initialization of Neural Networks
Maciej Skorski, Alessandro Temperoni, Martin Theobald
The proper initialization of weights is crucial for the effective training and fast convergence of deep neural networks (DNNs). Prior work in this area has mostly focused on balanc…
Simple Root Cause Analysis by Separable Likelihoods
Maciej Skorski
Root Cause Analysis for Anomalies is challenging because of the trade-off between the accuracy and its explanatory friendliness, required for industrial applications. In this paper…