5 citations · 8 across the 6 of their papers we have counts for
7 papers
Joint Nuclear and Regularization for Logistic Matrix Regression with Applications to Brain Imaging
Damian Brzyski, Aaron Cohen, Zijian Wang +3
We introduce a new convex optimization framework for logistic scalar-on-matrix regression which incorporates nuclear and norm penalties to enforce simultaneously low-rank…
Is Textual Similarity Invariant under Machine Translation? Evidence Based on the Political Manifesto Corpus
Daria Boratyn, Damian Brzyski, Albert Leśniak +5
We investigate the extent to which cosine similarity between paragraph embeddings is invariant under machine translation, using the Manifesto Corpus of over 2,800 political party p…
Machine Learning and Statistical Approaches to Measuring Similarity of Political Parties
Daria Boratyn, Damian Brzyski, Beata Kosowska-Gąstoł +3
Mapping political party systems to metric policy spaces is one of the major methodological problems in political science. At present, in most political science project this task is…
A Sparsity Inducing Nuclear-Norm Estimator (SpINNEr) for Matrix-Variate Regression in Brain Connectivity Analysis
Damian Brzyski, Xixi Hu, Joaquin Goni +3
Classical scalar-response regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. In medical applications, however, regresso…
Group SLOPE - adaptive selection of groups of predictors
Damian Brzyski, Alexej Gossmann, Weijie Su +1
Sorted L-One Penalized Estimation (SLOPE) is a relatively new convex optimization procedure which allows for adaptive selection of regressors under sparse high dimensional designs.…
Group SLOPE - adaptive selection of groups of predictors
Damian Brzyski, Weijie Su, Małgorzata Bogdan
Sorted L-One Penalized Estimation is a relatively new convex optimization procedure which allows for adaptive selection of regressors under sparse high dimensional designs. Here we…
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1-Norm
Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan
In this paper we propose a primal-dual proximal extragradient algorithm to solve the generalized Dantzig selector (GDS) estimation problem, based on a new convex-concave saddle-poi…