8 citations · 10 across the 9 of their papers we have counts for
11 papers
Adversarial examples by perturbing high-level features in intermediate decoder layers
Vojtěch Čermák, Lukáš Adam
We propose a novel method for creating adversarial examples. Instead of perturbing pixels, we use an encoder-decoder representation of the input image and perturb intermediate laye…
Solvability of the Power Flow Problem in DC Overhead Wire Circuit
Jakub Ševčík, Lukáš Adam, Jan Přikryl +1
Proper traffic simulation of electric vehicles, which draw energy from overhead wires, requires adequate modeling of traction infrastructure. Such vehicles include trains, trams or…
Double Oracle Algorithm for Computing Equilibria in Continuous Games
Lukáš Adam, Rostislav Horčík, Tomáš Kasl +1
Many efficient algorithms have been designed to recover Nash equilibria of various classes of finite games. Special classes of continuous games with infinite strategy spaces, such…
DeepTopPush: Simple and Scalable Method for Accuracy at the Top
Václav Mácha, Lukáš Adam, Václav Šmídl
Accuracy at the top is a special class of binary classification problems where the performance is evaluated only on a small number of relevant (top) samples. Applications include i…
General Framework for Binary Classification on Top Samples
Lukáš Adam, Václav Mácha, Václav Šmídl +1
Many binary classification problems minimize misclassification above (or below) a threshold. We show that instances of ranking problems, accuracy at the top or hypothesis testing m…
Nonlinear classifiers for ranking problems based on kernelized SVM
Václav Mácha, Lukáš Adam, Václav Šmídl
Many classification problems focus on maximizing the performance only on the samples with the highest relevance instead of all samples. As an example, we can mention ranking proble…
A Simple Yet Effective Approach to Robust Optimization Over Time
Lukáš Adam, Xin Yao
Robust optimization over time (ROOT) refers to an optimization problem where its performance is evaluated over a period of future time. Most of the existing algorithms use particle…
Machine learning approach to chance-constrained problems: An algorithm based on the stochastic gradient descent
Lukáš Adam, Martin Branda
We consider chance-constrained problems with discrete random distribution. We aim for problems with a large number of scenarios. We propose a novel method based on the stochastic g…
Projections onto the canonical simplex with additional linear inequalities
L. Adam, V. Mácha
We consider the distributionally robust optimization and show that computing the distributional worst-case is equivalent to computing the projection onto the canonical simplex with…
The Intermediate Set and Limiting Superdifferential for Coalition Games: Between the Core and the Weber Set
L. Adam, T. Kroupa
We introduce the intermediate set as an interpolating solution concept between the core and the Weber set of a coalitional game. The new solution is defined as the limiting superdi…
Identification of some nonsmooth evolution systems with illustration on adhesive contacts at small strains
L. Adam, J. V. Outrata, T. Roubicek
A class of evolution quasistatic systems which leads, after a suitable time discretization, to recursive nonlinear programs, is considered and optimal control or identification pro…