5 citations · 5 across the 3 of their papers we have counts for
5 papers
Universal Sample-Based Embeddings of Higher-Order Objects
Radovan Haluška, Christopher Solinas, Nathan R. Sturtevant +2
Neural networks operate naturally on finite-dimensional vectors, yet many problems require reasoning about higher-order objects such as distributions, functions, and graphs. Such o…
Belief Embedding Tree Search
Christopher Solinas, Radovan Haluška, Martin Schmid +3
Beliefs in a Partially Observable Markov Decision Process (POMDP) are posterior distributions over the hidden state given the agent's history of actions and observations. They summ…
Neural Bayesian Filtering
Christopher Solinas, Radovan Haluska, David Sychrovsky +6
Sequential estimation under partial observability requires tracking beliefs that may be high-dimensional, multimodal, and non-Gaussian. Classical Bayesian filters generalize zero-s…
Learning to Beat ByteRL: Exploitability of Collectible Card Game Agents
Radovan Haluska, Martin Schmid
While Poker, as a family of games, has been studied extensively in the last decades, collectible card games have seen relatively little attention. Only recently have we seen an age…
Benchmark of Data Preprocessing Methods for Imbalanced Classification
Radovan Haluška, Jan Brabec, Tomáš Komárek
Severe class imbalance is one of the main conditions that make machine learning in cybersecurity difficult. A variety of dataset preprocessing methods have been introduced over the…