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Title: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data |
Abstract: When outcomes are missing for reasons beyond an investigator's control, there are two different ways to adjust a parameter estimate for covariates that may be related both to the outcome and to missingness. One approach is to model the relationships between the covariates and the outcome and use those relatio... |
Title: Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data |
Abstract: Comment on ``Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data'' [arXiv:0804.2958] |
Title: Comment: Performance of Double-Robust Estimators When ``Inverse Probability'' Weights Are Highly Variable |
Abstract: Comment on ``Performance of Double-Robust Estimators When ``Inverse Probability'' Weights Are Highly Variable'' [arXiv:0804.2958] |
Title: Comment: Understanding OR, PS and DR |
Abstract: Comment on ``Understanding OR, PS and DR'' [arXiv:0804.2958] |
Title: Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data |
Abstract: Comment on ``Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data'' [arXiv:0804.2958] |
Title: Rejoinder: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data |
Abstract: Rejoinder to ``Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data'' [arXiv:0804.2958] |
Title: Measuring Traffic |
Abstract: A traffic performance measurement system, PeMS, currently functions as a statewide repository for traffic data gathered by thousands of automatic sensors. It has integrated data collection, processing and communications infrastructure with data storage and analytical tools. In this paper, we discuss statistic... |
Title: The Epic Story of Maximum Likelihood |
Abstract: At a superficial level, the idea of maximum likelihood must be prehistoric: early hunters and gatherers may not have used the words ``method of maximum likelihood'' to describe their choice of where and how to hunt and gather, but it is hard to believe they would have been surprised if their method had been d... |
Title: Generalized SURE for Exponential Families: Applications to Regularization |
Abstract: Stein's unbiased risk estimate (SURE) was proposed by Stein for the independent, identically distributed (iid) Gaussian model in order to derive estimates that dominate least-squares (LS). In recent years, the SURE criterion has been employed in a variety of denoising problems for choosing regularization para... |
Title: Bayesian computation for statistical models with intractable normalizing constants |
Abstract: This paper deals with some computational aspects in the Bayesian analysis of statistical models with intractable normalizing constants. In the presence of intractable normalizing constants in the likelihood function, traditional MCMC methods cannot be applied. We propose an approach to sample from such poster... |
Title: On the performance of approximate equilibria in congestion games |
Abstract: We study the performance of approximate Nash equilibria for linear congestion games. We consider how much the price of anarchy worsens and how much the price of stability improves as a function of the approximation factor $\epsilon$. We give (almost) tight upper and lower bounds for both the price of anarchy ... |
Title: Technical Report - Automatic Contour Extraction from 2D Neuron Images |
Abstract: This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods can not be used to characterize such cells because of overlaps between neuronal processes. The proposed ... |
Title: A Conversation with Seymour Geisser |
Abstract: Seymour Geisser received his bachelor's degree in Mathematics from the City College of New York in 1950, and his M.A. and Ph.D. degrees in Mathematical Statistics at the University of North Carolina in 1952 and 1955, respectively. He then held positions at the National Bureau of Standards and the National Ins... |
Title: A Conversation with Monroe Sirken |
Abstract: Born January 11, 1921 in New York City, Monroe Sirken grew up in a suburb of Pasadena, California. He earned B.A. and M.A. degrees in sociology at UCLA in 1946 and 1947, and a Ph.D. in 1950 in sociology with a minor in mathematics at the University of Washington in 1950 where Professor Z. W. Birnbaum was his ... |
Title: Phoneme recognition in TIMIT with BLSTM-CTC |
Abstract: We compare the performance of a recurrent neural network with the best results published so far on phoneme recognition in the TIMIT database. These published results have been obtained with a combination of classifiers. However, in this paper we apply a single recurrent neural network to the same task. Our re... |
Title: A New Approach to Automated Epileptic Diagnosis Using EEG and Probabilistic Neural Network |
Abstract: Epilepsy is one of the most common neurological disorders that greatly impair patient' daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of seizure (ictal) activities. Nowadays, there are many systems helping t... |
Title: A Method of Trend Extraction Using Singular Spectrum Analysis |
Abstract: The paper presents a new method of trend extraction in the framework of the Singular Spectrum Analysis (SSA) approach. This method is easy to use, does not need specification of models of time series and trend, allows to extract trend in the presence of noise and oscillations and has only two parameters (besi... |
Title: Natural pseudo-distance and optimal matching between reduced size functions |
Abstract: This paper studies the properties of a new lower bound for the natural pseudo-distance. The natural pseudo-distance is a dissimilarity measure between shapes, where a shape is viewed as a topological space endowed with a real-valued continuous function. Measuring dissimilarity amounts to minimizing the change... |
Title: Isotropic PCA and Affine-Invariant Clustering |
Abstract: We present a new algorithm for clustering points in R^n. The key property of the algorithm is that it is affine-invariant, i.e., it produces the same partition for any affine transformation of the input. It has strong guarantees when the input is drawn from a mixture model. For a mixture of two arbitrary Gaus... |
Title: Respect My Authority! HITS Without Hyperlinks, Utilizing Cluster-Based Language Models |
Abstract: We present an approach to improving the precision of an initial document ranking wherein we utilize cluster information within a graph-based framework. The main idea is to perform re-ranking based on centrality within bipartite graphs of documents (on one side) and clusters (on the other side), on the premise... |
Title: Causal inference using the algorithmic Markov condition |
Abstract: Inferring the causal structure that links n observables is usually based upon detecting statistical dependences and choosing simple graphs that make the joint measure Markovian. Here we argue why causal inference is also possible when only single observations are present. We develop a theory how to generate c... |
Title: Multiple Random Oracles Are Better Than One |
Abstract: We study the problem of learning k-juntas given access to examples drawn from a number of different product distributions. Thus we wish to learn a function f : -1,1^n -> -1,1 that depends on k (unknown) coordinates. While the best known algorithms for the general problem of learning a k-junta require running ... |
Title: A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning |
Abstract: We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by generalizing three components of BFGS to subdifferentials: the local quadratic model, the identification of a descent direction, and ... |
Title: Modelling coloured residual noise in gravitational-wave signal processing |
Abstract: We introduce a signal processing model for signals in non-white noise, where the exact noise spectrum is a priori unknown. The model is based on a Student's t distribution and constitutes a natural generalization of the widely used normal (Gaussian) model. This way, it allows for uncertainty in the noise spec... |
Title: Image Processing in Optical Guidance for Autonomous Landing of Lunar Probe |
Abstract: Because of the communication delay between earth and moon, the GNC technology of lunar probe is becoming more important than ever. Current navigation technology is not able to provide precise motion estimation for probe landing control system Computer vision offers a new approach to solve this problem. In thi... |
Title: Hardware In The Loop Simulator in UAV Rapid Development Life Cycle |
Abstract: Field trial is very critical and high risk in autonomous UAV development life cycle. Hardware in the loop (HIL) simulation is a computer simulation that has the ability to simulate UAV flight characteristic, sensor modeling and actuator modeling while communicating in real time with the UAV autopilot hardware... |
Title: Effects of Leaders Position and Shape on Aerodynamic Performances of V Flight Formation |
Abstract: The influences of the leader in a group of V flight formation are dealt with. The investigation is focused on the effect of its position and shape on aerodynamics performances of a given V flight formation. Vortices generated the wing tip of the leader moves downstream forming a pair of opposite rotating line... |
Title: Automated Flight Test and System Identification for Rotary Wing Small Aerial Platform using Frequency Responses Analysis |
Abstract: This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency swept is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consisten... |
Title: Virtual Reality Simulation of Fire Fighting Robot Dynamic and Motion |
Abstract: This paper presents one approach in designing a Fire Fighting Robot which has been contested annually in a robotic student competition in many countries following the rules initiated at the Trinity College. The approach makes use of computer simulation and animation in a virtual reality environment. In the si... |
Title: Heading Lock Maneuver Testing of Autonomous Underwater Vehicle |
Abstract: In recent years, Autonomous Underwater Vehicle (UAV) research and development at Bandung Institute of Technology in Indonesia has achieved the testing stage in the field. This testing was still being classified as the early testing, since some of the preliminary tests were carried out in the scale of the labo... |
Title: Development of Architectures for Internet Telerobotics Systems |
Abstract: This paper presents our experience in developing and implementing Internet telerobotics system. Internet telerobotics system refers to a robot system controlled and monitored remotely through the Internet. A robot manipulator with five degrees of freedom, called Mentor, is employed. Client-server architecture... |
Title: Unmanned Aerial Vehicle Instrumentation for Rapid Aerial Photo System |
Abstract: This research will proposed a new kind of relatively low cost autonomous UAV that will enable farmers to make just in time mosaics of aerial photo of their crop. These mosaics of aerial photo should be able to be produced with relatively low cost and within the 24 hours of acquisition constraint. The autonomo... |
Title: First Principle Approach to Modeling of Small Scale Helicopter |
Abstract: The establishment of global helicopter linear model is very precious and useful for the design of the linear control laws, since it is never afforded in the published literatures. In the first principle approach, the mathematical model was developed using basic helicopter theory accounting for particular char... |
Title: Optimal Tracking Controller Design for a Small Scale Helicopter |
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