nils-herrmann/clean_scirepeval huggingface dataset:
Practical Bayesian optimization with application to tuning machine learning algorithms

Bayesian optimization has recently emerged in the machine learning community as a very effective automatic alternative to the tedious task of handtuning algorithm hyperparameters. Although it is a relatively new aspect of machine learning, it has known roots in the Bayesian experimental design (Lindley, 1956; Chaloner and Verdinelli, 1995) the design and analysis of computer experiments (DACE; Sacks et al. 1989) Kriging (Krige, 1951) and multi armed bandits (Gittins, 1979) In this thesis, we motivate and introduce the model based optimization framework and provide some historical context to the technique that dates back as far as 1933 with application to clinical drug trials (Thompson, 1933) Contributions of this work include a Bayesian gap based exploration policy, inspired by Gabillon et al. (2012) a principled information theoretic portfolio strategy, out performing the portfolio of Hoffman et al. (2011) and a general practical technique circumventing the need for an initial bounding box. These various works each address existing practical challenges in the way of more widespread adoption of probabilistic model based optimization techniques. Finally, we conclude this thesis with important directions for future research, emphasizing scalability and computational feasibility of the approach as a general purpose optimizer.
Multi objective parameter configuration of machine learning algorithms using model based optimization
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

The performance of many machine learning algorithms heavily depends on the setting of their respective hyperparameters. Many different tuning approaches exist, from simple grid or random search approaches to evolutionary algorithms and Bayesian optimization. Often, these algorithms are used to optimize a single performance criterion. But in practical applications, a single criterion may not be sufficient to adequately characterize the behavior of the machine learning method under consideration and the Pareto front of multiple criteria has to be considered. We propose to use model based multi objective optimization to efficiently approximate such Pareto fronts.
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
Venue: NIPS

In many applications of black box optimization, one can evaluate multiple points simultaneously, e.g. when evaluating the performances of several different neural network architectures in a parallel computing environment. In this paper, we develop a novel batch Bayesian optimization algorithm the parallel knowledge gradient method. By construction, this method provides the one step Bayes optimal batch of points to sample. We provide an efficient strategy for computing this Bayes optimal batch of points, and we demonstrate that the parallel knowledge gradient method finds global optima significantly faster than previous batch Bayesian optimization algorithms on both synthetic test functions and when tuning hyperparameters of practical machine learning algorithms, especially when function evaluations are noisy.
Optimization of Statistical Decisions for Age Replacement Problems via a New Pivotal Quantity Averaging Approach

Age replacement strategies, where a unit is replaced upon failure or on reaching a predetermined age, whichever occurs first, provide simple and intuitively attractive replacement guidelines for technical units. Within theory of stochastic processes, the optimal preventive replacement age, in the sense of leading to minimal expected costs per unit of time when the strategy is used for a sequence of similar units over a long period of time, is derived by application of the renewal reward theorem. The mathematical solution to the problem of what is the optimal age for replacement is well known for the case when the parameter values of the underlying lifetime distributions are known with certainty. In actual practice, such is simply not the case. When these models are applied to solve real world problems, the parameters are estimated and then treated as if they were the true values. The risk associated with using estimates rather than the true parameters is called estimation risk and is often ignored. When data are limited and (or) unreliable, estimation risk may be significant, and failure to incorporate it into the model design may lead to serious errors. Its explicit consideration is important since decision rules that are optimal in the absence of uncertainty need not even be approximately optimal in the presence of such uncertainty. In the present paper, for efficient optimization of statistical decisions under parametric uncertainty, the pivotal quantity averaging (PQA) approach is suggested. This approach represents a new simple and computationally attractive statistical technique based on the constructive use of the invariance principle in mathematical statistics. It allows one to carry out the transition from the original problem to the equivalent transformed problem (in terms of pivotal quantities and ancillary factors) via invariant embedding a sample statistic in the original problem. In this case, the statistical optimization of the equivalent transformed problem is carried out via ancillary factors. Unlike the Bayesian approach, the proposed approach is independent of the choice of priors. This approach allows one to eliminate unknown parameters from the problem and to find the better decision rules, which have smaller risk than any of the well known decision rules. To illustrate the proposed approach, the numerical examples are given.
Fault activation by hydraulic fracturing in western Canada
Venue: Science

Triggered quakes get unconventional The big earthquakes induced by human activity are mostly linked with disposal of wastewater. However, Bao and Eaton implicate hydraulic fracturing (or fracking) as the culprit in western Canada (see the Perspective by Elsworth) Fracking near Fox Creek, Alberta, reactivated faults, clustering earthquakes along the old fault traces. Fracking does not appear to cause large earthquakes in many other areas that are prone to induced seismicity. Understanding the underlying causes of seismicity in different localities is vital for developing sound regulation to limit damaging earthquakes. Science, this issue p. 1406; see also p. 1380 Hydraulic fracturing reactivated faults, inducing an earthquake of magnitude 4 in western Canada. Hydraulic fracturing has been inferred to trigger the majority of injection induced earthquakes in western Canada, in contrast to the Midwestern United States, where massive saltwater disposal is the dominant triggering mechanism. A template based earthquake catalog from a seismically active Canadian shale play, combined with comprehensive injection data during a 4 month interval, shows that earthquakes are tightly clustered in space and time near hydraulic fracturing sites. The largest event [moment magnitude (MW) 3.9] occurred several weeks after injection along a fault that appears to extend from the injection zone into crystalline basement. Patterns of seismicity indicate that stress changes during operations can activate fault slip to an offset distance of >1 km, whereas pressurization by hydraulic fracturing into a fault yields episodic seismicity that can persist for months.
The Predictive Processing Paradigm Has Roots in Kant
Venue: Front. Syst. Neurosci.

Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly PP links back to Kant. In this article, I argue that several core aspects of PP were anticipated by Kant (1996/1787) in his works on perception and cognition. Themes from Kant active in PP include: (1) the emphasis on "top down" generation of percepts; (2) the role of "hyperpriors" (3) the general function of "generative models" (4) the process of "analysis by synthesis" and (5) the crucial role of imagination in perception. In addition to these, I also point out that PP echoes Kant's general project in that it aims to explain how minds track causal structure in the world using only sensory data, and that it uses a reverse engineer or "top down" method of analysis. I then locate a possible source of Kant's influence on PP by tracing the paradigm back to Hermann von Helmholtz, who saw himself as providing a scientific implementation of Kant's conclusions. I conclude by arguing that PP should not be regarded as a new paradigm, but is more appropriately understood as the latest incarnation of an approach to perception and cognition initiated by Kant and refined by Helmholtz.
Evaluation of marginal/internal fit of chrome cobalt crowns: Direct laser metal sintering versus computer aided design and computer aided manufacturing.
Venue: Nigerian journal of clinical practice

The purpose of this study was to evaluate the internal and marginal fit of chrome cobalt (Co Cr) crowns were fabricated with laser sintering, computer aided design (CAD) and computer aided manufacturing, and conventional methods.  Polyamide master and working models were designed and fabricated. The models were initially designed with a software application for three dimensional (3D) CAD (Maya, Autodesk Inc. All models were fabricated models were produced by a 3D printer (EOSINT P380 SLS, EOS) 128 1 unit Co Cr fixed dental prostheses were fabricated with four different techniques: Conventional lost wax method, milled wax with lost wax method (MWLW) direct laser metal sintering (DLMS) and milled Co Cr (MCo Cr) The cement film thickness of the marginal and internal gaps was measured by an observer using a stereomicroscope after taking digital photos in x24.  Best fit rates according to mean and standard deviations of all measurements was in DLMS both in premolar (65.84) and molar (58.38) models in mm. A significant difference was found DLMS and the rest of fabrication techniques (P 0.05) No significant difference was found between MCo CR and MWLW in all fabrication techniques both in premolar and molar models (P 0.05) CONCLUSION DMLS was best fitting fabrication techniques for single crown based on the results.The best fit was found in marginal; the larger gap was found in occlusal.All groups were within the clinically acceptable misfit range.
Contribution to ontologies building using the semantic web and web mining
Venue: 2016 International Conference on Engineering MIS (ICEMIS)

The volume of information that is nowadays available on the web makes the limits of the current Web clear for its users, in fact finding information and knowledge between billions of Web pages is very difficult, the Semantic web and data mining are two new fasting developing domains that will resolve this problem and the combination of this tow area will transform the web into a semantically information space in order to make sense of already existing data designed only for human readers and then to extract the knowledge contained within the Web, many experience shows that the ontology engineering is very important to solve the problem of the interoperability between web systems by using the ontology learning from web content in order to develop method of extraction knowledge from web data and the representation of this Knowledge in a form understandable by arbitrary parties (machines, humans This paper will describe the commonalities of the two areas in order to extract useful and shared Knowledge.
Contrastive analysis of bubble merge sort proposing hybrid approach
Venue: 2016 Sixth International Conference on Innovative Computing Technology (INTECH)

A sorting algorithm is one that puts elements of a list in a certain order. It makes easy searching and locating the information. The most used orders are numerical order and lexicographical order. An efficient sorting algorithm is that takes less time and space complexity. In this paper I make contrastive analysis of bubble sort and merge sort and tried to show why required some new approach to get best sorting results. In this regard we proposed a hybrid approach that will take minimum number of comparisons, with less time and space complexity to sort. Divide and conquer (merge sort) with bi directional bubble sort approach is used and an example data is sorted with such hybrid approach.
Top down Modulation of Neural Activity in Anticipatory Visual Attention: Control Mechanisms Revealed by Simultaneous EEG fMRI.
Venue: Cerebral cortex

In covert visual attention, frontoparietal attention control areas are thought to issue signals to selectively bias sensory neurons to facilitate behaviorally relevant information and suppress distraction. We investigated the relationship between activity in attention control areas and attention related modulation of posterior alpha activity using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging in humans during cued visual spatial attention. Correlating single trial EEG alpha power with blood oxygen level dependent (BOLD) activity, we found that BOLD in the intraparietal sulcus (IPS) and left middle frontal gyrus was inversely correlated with occipital alpha power. Importantly, in IPS, inverse correlations were stronger for alpha within the hemisphere contralateral to the attended hemifield, implicating the IPS in the enhancement of task relevant sensory areas. Positive BOLD alpha correlations were observed in sensorimotor cortices and the default mode network, suggesting a mechanism of active suppression over task irrelevant areas. The magnitude of cue induced alpha lateralization was positively correlated with BOLD in dorsal anterior cingulate cortex and dorsolateral prefrontal cortex, implicating a role of executive control in attention. These results show that IPS and frontal executive areas are the main sources of biasing influences on task relevant visual cortex, whereas task irrelevant default mode network and sensorimotor cortex are inhibited during visual attention.
Los roles y estereotipos de genero en los comportamientos sexuales de jovenes de Coahuila, Mexico: aproximacion desde la Teoria Fundamentada

This research is a qualitative approach whose objective was to identify the roles and stereotypes of gender and the sexual behaviors of college students. The method of analysis used for this work, was the grounded theory, in particular, the open and axial coding processes. The gathering of the information was through a structured interview, using certain questions such as: What are the men and women's behaviors expected in their sexual encounters? And how much do they agree with these behaviors? We conclude that sexual behavior between men and women keep differences concerning the socialization of gender, based on the traditions of the characters' roles and the stereotypes as well as their transgression.
Perspectiva de genero en Mexico: Analisis de los obstaculos y limitaciones

La relacion asimetrica entre hombres y mujeres en nuestro pais se ha caracterizado por mantener y reproducir los estereotipos, roles, prejuicios y toda serie de causas que promueven la discriminacion y trato desigual; producto de la cultura e idiosincrasia. Sobre las diferencias biologicas se ha construido un esquema sociocultural que incide en la conducta de las mujeres y que controla sus posibilidades de desarrollo social, promoviendo barreras y obstaculos para su participacion en el sector productivo; pero tambien en las normas de vida hacia las mujeres. Este trabajo describe y analiza los factores socioculturales que inciden en los estereotipos y limitaciones hacia la mujer, utiliza los metodos de interpretacion y exposicion para generar conocimiento teorico; para formular propuestas y abrir la discusion en torno a la agenda de acciones a desarrollar.
Pharmacotherapy for Pain in a Family With Inherited Erythromelalgia Guided by Genomic Analysis and Functional Profiling.
Venue: JAMA neurology

There is a need for more effective pharmacotherapy for chronic pain, including pain in inherited erythromelalgia (IEM) in which gain of function mutations of sodium channel NaV1.7 make dorsal root ganglion (DRG) neurons hyperexcitable.  To determine whether pain in IEM can be attenuated via pharmacotherapy guided by genomic analysis and functional profiling.  Pain in 2 patients with IEM due to the NaV1.7 S241T mutation, predicted by structural modeling and functional analysis to be responsive to carbamazepine, was assessed in a double blind, placebo controlled study conducted from September 2014 to April 21, 2015. Functional magnetic resonance imaging assessed patterns of brain activity associated with pain during treatment with placebo or carbamazepine. Multielectrode array technology was used to assess the effect of carbamazepine on firing of DRG neurons carrying S241T mutant channels.  Behavioral assessment of pain; functional magnetic resonance imaging; and assessment of firing in DRG neurons carrying S241T mutant channels.  This study included 2 patients from the same family with IEM and the S241T NaV1.7 mutation. We showed that, as predicted by molecular modeling, thermodynamic analysis, and functional profiling, carbamazepine attenuated pain in patients with IEM due to the S241T NaV1.7 mutation. Patient 1 reported a reduction in mean time in pain (TIP) per day during the 15 day maintenance period, from 424 minutes while taking placebo to 231.9 minutes while taking carbamazepine (400 mg/day) and a reduction in total TIP over the 15 day maintenance period, from 6360 minutes while taking placebo to 3015 minutes while taking carbamazepine. Patient 2 reported a reduction in mean TIP per day during the maintenance period, from 61 minutes while taking placebo to 9.1 minutes while taking carbamazepine (400 mg then 200 mg/day) and a reduction in total TIP, from 915 minutes while taking placebo over the 15 day maintenance period to 136 minutes while taking carbamazepine. Patient 1 reported a reduction of mean episode duration, from 615 minutes while taking placebo to 274.1 minutes while taking carbamazepine, while patient 2 reported a reduction of the mean episode duration from 91.5 minutes while taking placebo to 45.3 minutes while taking carbamazepine. Patient 1, who had a history of night awakenings from pain, reported 101 awakenings owing to pain while taking placebo during the maintenance period and 32 awakenings while taking carbamazepine. Attenuation of pain was paralleled by a shift in brain activity from valuation and pain areas to primary and secondary somatosensory, motor, and parietal attention areas. Firing of DRG neurons expressing the S241T NaV1.7 mutant channel in response to physiologically relevant thermal stimuli was reduced by carbamazepine.  Our results demonstrate that pharmacotherapy guided by genomic analysis, molecular modeling, and functional profiling can attenuate neuropathic pain in patients carrying the S241T mutation.
Increased Variability and Asymmetric Expansion of the Hippocampal Spatial Representation in a Distal Cue Dependent Memory Task
Venue: Hippocampus

Place cells in the hippocampus fire at specific positions in space, and distal cues in the environment play critical roles in determining the spatial firing patterns of place cells. Many studies have shown that place fields are influenced by distal cues in foraging animals. However, it is largely unknown whether distal cue dependent changes in place fields appear in different ways in a memory task if distal cues bear direct significance to achieving goals. We investigated this possibility in this study. Rats were trained to choose different spatial positions in a radial arm in association with distal cue configurations formed by visual cue sets attached to movable curtains around the apparatus. The animals were initially trained to associate readily discernible distal cue configurations (0deg vs. 80deg angular separation between distal cue sets) with different food well positions and then later experienced ambiguous cue configurations (14deg and 66deg) intermixed with the original cue configurations. Rats showed no difficulty in transferring the associated memory formed for the original cue configurations when similar cue configurations were presented. Place field positions remained at the same locations across different cue configurations, whereas stability and coherence of spatial firing patterns were significantly disrupted when ambiguous cue configurations were introduced. Furthermore, the spatial representation was extended backward and skewed more negatively at the population level when processing ambiguous cue configurations, compared with when processing the original cue configurations only. This effect was more salient for large cue separation conditions than for small cue separation conditions. No significant rate remapping was observed across distal cue configurations. These findings suggest that place cells in the hippocampus dynamically change their detailed firing characteristics in response to a modified cue environment and that some of the firing properties previously reported in a foraging task might carry more functional weight than others when tested in a distal cue dependent memory task.
A weight based map matching algorithm for vehicle navigation in complex urban networks
Venue: J. Intell. Transp. Syst.

A map matching algorithm is an integral part of every navigation system and reconciles raw and inaccurate positional data (usually from a global positioning system [GPS] with digital road network data. Since both performance (speed) and accuracy are equally important in real time map matching, an accurate and efficient map matching algorithm is presented in this article. The proposed algorithm has three steps: initialization, same segment, and next segment. Distance between the GPS point and road segments, difference between the heading of the GPS point and direction of road segments, and difference between the direction of consecutive GPS points and direction of road segments are used to identify the best segment among candidates near intersections. In contrast to constant weights applied in existing algorithms, the weight of each criterion in this algorithm is dynamic. The weights of criteria are calculated for each GPS point based on its: (a) positional accuracy, (b) speed, and (c) traveled distance from previous GPS point. The algorithm considers a confidence level on the assigned segment to each GPS point, which is calculated based on the density and complexity of roads around the GPS point. The evaluation results indicate 95.34% correct segment identification and 92.19% correct segment assignment. The most important feature of our algorithm is that the high correct segment identification percentage achieved in urban areas is through a simple and efficient weight based method that does not depend on any additional data or positioning sensors other than digital road network and GPS.
1.3 Evolution of 5G mobile technology toward 1 2020 and beyond
Venue: 2016 IEEE International Solid State Circuits Conference (ISSCC)

Recently, LTE has become the mainstream of mobile technologies, and global expectations for 5G toward 2020 and beyond are rapidly growing. It is expected that 5G will cover a wide variety of use cases and a wide range of frequency bands. Today, some promising technologies are emerging, especially those using new technology combinations. Through such combinations, things which were considered impossible today will be achieved in the 5G era. Together, let us envision a new world: Wider coverage cellular systems even at higher frequencies, and single RAT 5G system which covers all 5G use cases and spectrum bands.