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Towards Effective Measurement and Interpolation of Bidirectional Texture Functions
Filip, Jiří
2011 - English
Bidirectional texture function (BTF) is acquired by taking thousands of material surface images for different illumination and viewing directions. This function, provided it is measured accurately, is typically exploited for visualization of material appearance in visual accuracy demanding applications. However, accurate measurement of the BTF is time and resources demanding task. While the sampling of illumination and viewing directions is in all known measurement systems done uniformly, we believe that to be more effective the sampling should be tailored specifically to reflectance properties of materials to be measured. Hence, we introduce a novel method of sparse BTF sampling. The method starts with collecting information about material visual behavior by means of small initial subset of reflectance samples measurement and analysis. This information is fed into our heuristic algorithm producing sparse material dependent sampling that is consequently used for BTF measurement and interpolation.
Keywords:
bidirectional texture function; measurement systems; illumination
Available at various institutes of the ASCR
Towards Effective Measurement and Interpolation of Bidirectional Texture Functions
Bidirectional texture function (BTF) is acquired by taking thousands of material surface images for different illumination and viewing directions. This function, provided it is measured accurately, is ...
Comparison of numerical weather prediction models for purposes of atmospheric dispersion modeling within the grant project MV ČR VG20102013018
Hofman, Radek; Pecha, Petr; Hošek, Jiří
2011 - English
This research report concerns numerical weather prediction models and their possible exploitation for purposes of atmospheric dispersion modeling within the grant project VG20102013018 provided by the Ministry of Interior of the Czech Republic. After brief description of numerical weather prediction systems MEDARD and ALADIN, their results are compared in terms of mutual agreement.
Keywords:
numerical weather prediction; ALADIN; MEDARD
Available at various institutes of the ASCR
Comparison of numerical weather prediction models for purposes of atmospheric dispersion modeling within the grant project MV ČR VG20102013018
This research report concerns numerical weather prediction models and their possible exploitation for purposes of atmospheric dispersion modeling within the grant project VG20102013018 provided by the ...
Feature Selection - A Very Compact Survey Over the Diversity of Existing Approaches
Somol, Petr; Novovičová, Jana; Pudil, Pavel; Kittler, J.
2010 - English
Feature Selection has been a subject of extensive research that nowadays extends far beyond the boundaries of statistical pattern recognition. We provide a concise yet wide view of the topic including representative references in an attempt to point out that important results can be easily overlooked or duplicated in a variety of – even indirectly related – research fields.
Keywords:
feature selection; dimensionality reduction; survey
Available at various institutes of the ASCR
Feature Selection - A Very Compact Survey Over the Diversity of Existing Approaches
Feature Selection has been a subject of extensive research that nowadays extends far beyond the boundaries of statistical pattern recognition. We provide a concise yet wide view of the topic ...
Sequential Retreating Search Methods in Feature Selection
Somol, Petr; Pudil, Pavel
2010 - English
Inspired by Floating Search, our new pair of methods, the Sequential Forward Retreating Search (SFRS) and Sequential Backward Retreating Search (SBRS) is exceptionally suitable for Wrapper based feature selection. (Conversely, it cannot be used with monotonic criteria.) Unlike most of other known sub-optimal search methods, both the SFRS and SBRS are parameter-free deterministic sequential procedures that incorporate in the optimization process both the search for the best subset and the determination of the best subset size. The subset yielded by either of the two new methods is to be expected closer to optimum than the best of all subsets yielded in one run of the Floating Search. Retreating Search time complexity is to be expected slightly worse but in the same order of magnitude as that of the Floating Search. In addition to introducing the new methods we provide a testing framework to evaluate them with respect to other existing tools.
Keywords:
feature selection; wrappers; sequential search; subset search; method evaluation; classifier performance; pattern recognition
Available at various institutes of the ASCR
Sequential Retreating Search Methods in Feature Selection
Inspired by Floating Search, our new pair of methods, the Sequential Forward Retreating Search (SFRS) and Sequential Backward Retreating Search (SBRS) is exceptionally suitable for Wrapper based ...
Experiment: Forgetting factor testing
Votava, A.; Zeman, Jan
2009 - English
Presented work deals with forgetting estimation in the frame of dynamic decision making. The main goal is to find the optimal forgetting system for the algorithm for estimation of forgetting factor in time in the optimal way. Further goal is to compare the algorithm with the constant forgetting for various settings. Předložená práce se zabývá odhadováním zapomínacího faktoru v modelu dynamického rozhodování. Hlavním cílem je nalezení optimální zapomínací sítě pro algoritmus pro optimální vývoj zapomínacího faktoru v čase. Dalším cílem je porovnání tohoto algoritmu a konstantního zapomínání pro různá nastavení.
Keywords:
Bayesian estimation (learning); forgetting
Available at various institutes of the ASCR
Experiment: Forgetting factor testing
Presented work deals with forgetting estimation in the frame of dynamic decision making. The main goal is to find the optimal forgetting system for the algorithm for estimation of forgetting factor in ...
On Hurst exponent estimation under heavy-tailed distributions
Baruník, Jozef; Krištoufek, Ladislav
2009 - English
We show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails in the data. Studie ukazuje jak se mění výběrové vlastnosti metod odhadů Hurstova exponentu na datech s těžkými chvosty.
Keywords:
Hurst exponent; heavy tails; detrended fluctuation analysis; rescaled range method
Available at various institutes of the ASCR
On Hurst exponent estimation under heavy-tailed distributions
We show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails in the data....
Evaluating Stability of Single and Multiple Feature Selectors that Optimize Feature Subset Cardinality
Somol, Petr; Novovičová, Jana
2009 - English
Stability (robustness) of feature selection methods is a topic of recent interest yet often neglected importance with direct impact on the reliability of machine learning systems. We investigate the problem of evaluating the stability of feature selection processes yielding subsets of varying size. We introduce several novel feature selection stability measures and adjust some existing measures in a unifying framework that offers broad insight into the stability problem. We study in detail the properties of considered measures and demonstrate on various examples what information about the feature selection process can be gained. We also introduce an alternative approach to feature selection evaluation in form of measures that enable comparing the similarity of two feature selection processes. These measures enable comparing, e.g., the output of two feature selection methods or two runs of one method with different parameters. The information obtained using the considered stability and similarity measures is shown usable for assessing feature selection methods (or criteria) as such Stabilita (robustnost) metod výběru příznaků je jedno z aktuálních témat diskutovaných v současné době, neboť má vliv na spolehlivost systémů strojového učení. Byly navrženy nové míry stability procesu výběru příznaků, které vyhodnocují celkový výskyt jednotlivých příznaků ve vybraných podmnožinách příznaků ne nutně stejné kardinality. Podrobně jsou studovány vlastnosti uvažovaných měr a na mnoha příkladech demonstrováno, jaké informace je možné získat o procesu výběru příznaků. V práci je také uvažován alternativní přístup k vyhodnocování výběru příznaků pomocí měr, které umožňují porovnat podobnost dvou procesů výběru příznaků
Keywords:
feature selection; stability measure; consistency measure; feature subset size optimization; sequential search; floating search; individual ranking; feature selection evaluation
Available at various institutes of the ASCR
Evaluating Stability of Single and Multiple Feature Selectors that Optimize Feature Subset Cardinality
Stability (robustness) of feature selection methods is a topic of recent interest yet often neglected importance with direct impact on the reliability of machine learning systems. We investigate the ...
Neural Networks as Semiparametric Option Pricing Tool
Baruník, Jozef; Baruníková, M.
2009 - English
We study the ability of artificial neural networks to price the European style call and put options on the S&P 500 index. Studie schopnosti neuronových sítí odcenit call a put opce na index S&P 500.
Keywords:
option valuation; neural network; S&P 500 index options
Available at various institutes of the ASCR
Neural Networks as Semiparametric Option Pricing Tool
We study the ability of artificial neural networks to price the European style call and put options on the S&P 500 index....
Power Law Behavior of the Central European Stock Markets During the Financial Crisis
Baruník, Jozef; Vácha, Lukáš; Vošvrda, Miloslav
2009 - English
In the paper we research statistical properties of the Central European stock markets. Studujeme statistické vlastnosti středoevropských trhů
Keywords:
power law; stock markets; stable probability distribution
Available at various institutes of the ASCR
Power Law Behavior of the Central European Stock Markets During the Financial Crisis
In the paper we research statistical properties of the Central European stock markets.
Studujeme statistické vlastnosti středoevropských trhů
Transformation of data in the framework of dynamic decision making
Chudoba, M.; Jirsa, Ladislav
2008 - English
In the presented work we are introduced to the problem of optimal decision making while dealing on the exchange with so-called "financial futures", i.e. time financial transaction. This task is transferred into the simplified mathematical model, which is solvable using Bayesian estimation methods. Financial data are modelled by auto-regressive model with normal noise, because the tools, which are exploited for prediction of the price on the market and which assume normal noise, have been already developed. The main goal of this work is the comparison of the efficiency of various transformations on input data, so that their noise had normal distribution, therefore the price prediction was as accurate as possible. The applicable algorithm is programmed in Matlab; the presentation of achieved results forms the final part of this thesis. V přredložené práci je přiblížen problém optimálního rozhodování při burzovním obchodování s tzv. "financial futures", tj. s termínovanými finančními obchody. Tato úloha je převedena do zjednodušeného matematického modelu, který je řešitelný za pomoci metod Bayesovského odhadování. Finanční data jsou modelována autoregresním modelem s normálním šumem, jelikož je již vyvinuta řada nástrojů předpokládajících právě normální šum, které slouží k predikci vývoje ceny na trhu. Hlavním cílem této práce je porovnávání výhodnosti různých transformací vstupních dat tak, aby jejich šum měl normální rozdělení a tudíž aby predikce ceny byla co nejpřesnější. Příslušný algoritmus je naprogramován v jazyce Matlab; prezentace dosažených výsledků tvoří závěrečnou část této práce.
Keywords:
Bayesian estimation; finance; transformation of data; hypothesis testing
Available at various institutes of the ASCR
Transformation of data in the framework of dynamic decision making
In the presented work we are introduced to the problem of optimal decision making while dealing on the exchange with so-called "financial futures", i.e. time financial transaction. This task is ...
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