6 citations · 26 across the 32 of their papers we have counts for
10 papers · 1 filter
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…
A Modern Analysis of Hutchinson's Trace Estimator
Maciej Skorski
The paper establishes the new state-of-art in the accuracy analysis of Hutchinson's trace estimator. Leveraging tools that have not been previously used in this context, particular…
Handy Formulas for Binomial Moments
Maciej Skorski
Despite the relevance of the binomial distribution for probability theory and applied statistical inference, its higher-order moments are poorly understood. The existing formulas a…
Simple Analysis of Johnson-Lindenstrauss Transform under Neuroscience Constraints
Maciej Skorski
The paper re-analyzes a version of the celebrated Johnson-Lindenstrauss Lemma, in which matrices are subjected to constraints that naturally emerge from neuroscience applications:…
Concentration Bounds for the Collision Estimator
Maciej Skorski
We prove a strong concentration result about the natural collision estimator, which counts the number of collisions that occur within an iid sample. This estimator is at the heart…
Revisiting Concentration of Missing Mass
Maciej Skorski
We revisit the problem of \emph{missing mass concentration}, developing a new method of estimating concentration of heterogenic sums, in spirit of celebrated Rosenthal's inequality…
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…
Practical Estimation of Renyi Entropy
Maciej Skorski
Entropy Estimation is an important problem with many applications in cryptography, statistic,machine learning. Although the estimators optimal with respect to the sample complexity…
Missing Mass Concentration for Markov Chains
Maciej Skorski
The problem of missing mass in statistical inference (posed by McAllester and Ortiz, NIPS'02; most recently revisited by Changa and Thangaraj, ISIT'2019) seeks to estimate the weig…