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Title: Not only a lack of right definitions: Arguments for a shift in information-processing paradigm |
Abstract: Machine Consciousness and Machine Intelligence are not simply new buzzwords that occupy our imagination. Over the last decades, we witness an unprecedented rise in attempts to create machines with human-like features and capabilities. However, despite widespread sympathy and abundant funding, progress in thes... |
Title: Emotional State Categorization from Speech: Machine vs. Human |
Abstract: This paper presents our investigations on emotional state categorization from speech signals with a psychologically inspired computational model against human performance under the same experimental setup. Based on psychological studies, we propose a multistage categorization strategy which allows establishin... |
Title: Exploring Language-Independent Emotional Acoustic Features via Feature Selection |
Abstract: We propose a novel feature selection strategy to discover language-independent acoustic features that tend to be responsible for emotions regardless of languages, linguistics and other factors. Experimental results suggest that the language-independent feature subset discovered yields the performance comparab... |
Title: Fast Overlapping Group Lasso |
Abstract: The group Lasso is an extension of the Lasso for feature selection on (predefined) non-overlapping groups of features. The non-overlapping group structure limits its applicability in practice. There have been several recent attempts to study a more general formulation, where groups of features are given, pote... |
Title: Solving the Resource Constrained Project Scheduling Problem with Generalized Precedences by Lazy Clause Generation |
Abstract: The technical report presents a generic exact solution approach for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedences (Rcpsp/max). The approach uses lazy clause generation, i.e., a hybrid of finite domain and Boolean satisfiability solving, in ... |
Title: Experimental Evaluation of Branching Schemes for the CSP |
Abstract: The search strategy of a CP solver is determined by the variable and value ordering heuristics it employs and by the branching scheme it follows. Although the effects of variable and value ordering heuristics on search effort have been widely studied, the effects of different branching schemes have received l... |
Title: The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning |
Abstract: In this paper, we address the problem of creating believable agents (virtual characters) in video games. We consider only one meaning of believability, ``giving the feeling of being controlled by a player'', and outline the problem of its evaluation. We present several models for agents in games which can pro... |
Title: A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering |
Abstract: We formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. This formulation enables practical and theoretical comparison of different approaches to graph clustering as well as comparison of gr... |
Title: Automatable Evaluation Method Oriented toward Behaviour Believability for Video Games |
Abstract: Classic evaluation methods of believable agents are time-consuming because they involve many human to judge agents. They are well suited to validate work on new believable behaviours models. However, during the implementation, numerous experiments can help to improve agents' believability. We propose a method... |
Title: High-dimensional covariance estimation based on Gaussian graphical models |
Abstract: Undirected graphs are often used to describe high dimensional distributions. Under sparsity conditions, the graph can be estimated using $\ell_1$-penalization methods. We propose and study the following method. We combine a multiple regression approach with ideas of thresholding and refitting: first we infer ... |
Title: Optimizing Selective Search in Chess |
Abstract: In this paper we introduce a novel method for automatically tuning the search parameters of a chess program using genetic algorithms. Our results show that a large set of parameter values can be learned automatically, such that the resulting performance is comparable with that of manually tuned parameters of ... |
Title: Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization |
Abstract: Relative to the large literature on upper bounds on complexity of convex optimization, lesser attention has been paid to the fundamental hardness of these problems. Given the extensive use of convex optimization in machine learning and statistics, gaining an understanding of these complexity-theoretic issues ... |
Title: Gaussian Process Bandits for Tree Search: Theory and Application to Planning in Discounted MDPs |
Abstract: We motivate and analyse a new Tree Search algorithm, GPTS, based on recent theoretical advances in the use of Gaussian Processes for Bandit problems. We consider tree paths as arms and we assume the target/reward function is drawn from a GP distribution. The posterior mean and variance, after observing data, ... |
Title: Weighted Attribute Fusion Model for Face Recognition |
Abstract: Recognizing a face based on its attributes is an easy task for a human to perform as it is a cognitive process. In recent years, Face Recognition is achieved with different kinds of facial features which were used separately or in a combined manner. Currently, Feature fusion methods and parallel methods are t... |
Title: Dynamic interactions in terms of senders, hubs, and receivers (SHR) using the singular value decomposition of time series: Theory and brain connectivity applications |
Abstract: Understanding of normal and pathological brain function requires the identification and localization of functional connections between specialized regions. The availability of high time resolution signals of electric neuronal activity at several regions offers information for quantifying the connections in te... |
Title: Fast Color Space Transformations Using Minimax Approximations |
Abstract: Color space transformations are frequently used in image processing, graphics, and visualization applications. In many cases, these transformations are complex nonlinear functions, which prohibits their use in time-critical applications. In this paper, we present a new approach called Minimax Approximations f... |
Title: On the Estimation of Coherence |
Abstract: Low-rank matrix approximations are often used to help scale standard machine learning algorithms to large-scale problems. Recently, matrix coherence has been used to characterize the ability to extract global information from a subset of matrix entries in the context of these low-rank approximations and other... |
Title: A log-Birnbaum-Saunders Regression Model with Asymmetric Errors |
Abstract: The paper by Leiva et al. (2010) introduced a skewed version of the sinh-normal distribution, discussed some of its properties and characterized an extension of the Birnbaum-Saunders distribution associated with this distribution. In this paper, we introduce a skewed log-Birnbaum-Saunders regression model bas... |
Title: Predicting Sequences of Progressive Events Times with Time-dependent Covariates |
Abstract: This paper presents an approach to modeling progressive event-history data when the overall objective is prediction based on time-dependent covariates. This approach does not model the hazard function directly. Instead, it models the process of the state indicators of the event history so that the time-depend... |
Title: Effective Pedestrian Detection Using Center-symmetric Local Binary/Trinary Patterns |
Abstract: Accurately detecting pedestrians in images plays a critically important role in many computer vision applications. Extraction of effective features is the key to this task. Promising features should be discriminative, robust to various variations and easy to compute. In this work, we present novel features, t... |
Title: Fitting birth-death processes to panel data with applications to bacterial DNA fingerprinting |
Abstract: Continuous-time linear birth-death-immigration (BDI) processes are frequently used in ecology and epidemiology to model stochastic dynamics of the population of interest. In clinical settings, multiple birth-death processes can describe disease trajectories of individual patients, allowing for estimation of t... |
Title: Memristor Crossbar-based Hardware Implementation of Fuzzy Membership Functions |
Abstract: In May 1, 2008, researchers at Hewlett Packard (HP) announced the first physical realization of a fundamental circuit element called memristor that attracted so much interest worldwide. This newly found element can easily be combined with crossbar interconnect technology which this new structure has opened a ... |
Title: Bayesian theory of systematic measurement deviations |
Abstract: Concerning systematic effects, the recommendation given in the GUM is to correct for them, but unfortunately no detailed information is available, how to do this. This publication will show, how systematic measurement deviations can be handled correctly based on the Bayesian probability theory. After a short ... |
Title: Distance Measures for Reduced Ordering Based Vector Filters |
Abstract: Reduced ordering based vector filters have proved successful in removing long-tailed noise from color images while preserving edges and fine image details. These filters commonly utilize variants of the Minkowski distance to order the color vectors with the aim of distinguishing between noisy and noise-free v... |
Title: Real-Time Implementation of Order-Statistics Based Directional Filters |
Abstract: Vector filters based on order-statistics have proved successful in removing impulsive noise from color images while preserving edges and fine image details. Among these filters, the ones that involve the cosine distance function (directional filters) have particularly high computational requirements, which li... |
Title: Cost-Effective Implementation of Order-Statistics Based Vector Filters Using Minimax Approximations |
Abstract: Vector operators based on robust order statistics have proved successful in digital multichannel imaging applications, particularly color image filtering and enhancement, in dealing with impulsive noise while preserving edges and fine image details. These operators often have very high computational requireme... |
Title: A Fast Switching Filter for Impulsive Noise Removal from Color Images |
Abstract: In this paper, we present a fast switching filter for impulsive noise removal from color images. The filter exploits the HSL color space, and is based on the peer group concept, which allows for the fast detection of noise in a neighborhood without resorting to pairwise distance computations between each pixe... |
Title: Nonlinear Vector Filtering for Impulsive Noise Removal from Color Images |
Abstract: In this paper, a comprehensive survey of 48 filters for impulsive noise removal from color images is presented. The filters are formulated using a uniform notation and categorized into 8 families. The performance of these filters is compared on a large set of images that cover a variety of domains using three... |
Title: Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images |
Abstract: Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, s... |
Title: An Improved Objective Evaluation Measure for Border Detection in Dermoscopy Images |
Abstract: Background: Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, dermoscopy image analysis has become an important research area. One of the most important steps in dermoscopy image... |
Title: Constructions d\'efinitoires des tables du Lexique-Grammaire |
Abstract: Lexicon-Grammar tables are a very rich syntactic lexicon for the French language. This linguistic database is nevertheless not directly suitable for use by computer programs, as it is incomplete and lacks consistency. Tables are defined on the basis of features which are not explicitly recorded in the lexicon... |
Title: Parameterized Complexity Results in Symmetry Breaking |
Abstract: Symmetry is a common feature of many combinatorial problems. Unfortunately eliminating all symmetry from a problem is often computationally intractable. This paper argues that recent parameterized complexity results provide insight into that intractability and help identify special cases in which symmetry can... |
Title: Estimating Discrete Markov Models From Various Incomplete Data Schemes |
Abstract: The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of individuals over the whole observation period. In such a case, the estimation of transition probabilities is straightforwardly mad... |
Title: Optimizing an Organized Modularity Measure for Topographic Graph Clustering: a Deterministic Annealing Approach |
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